diff --git a/cases/MirrorRollingBall/scene_360_in/reference/artifacts/actions.txt b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..e6e58b678c5972ebced481841e85b903ccdd54e0 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/actions.txt @@ -0,0 +1,8 @@ +# table7.camera.360_in_v1 -- generated action trajectory. +# Provenance: camera_360_in.yaml (semantic SHA-256: 16008bd3e1bd2b5497b424eab147eda7a7858572ce3d1afb5ccb62d509e9d6c4) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 10.0 -36.0 + +# Project Genie browser actions: +{"keys": ["ArrowLeft"], "ms": 10000, "op": "hold", "target_yaw_deg": -360.0} diff --git a/cases/MirrorRollingBall/scene_360_in/reference/artifacts/intrinsics.npy b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..32f2beb7dde66893fdfe8356ecf3594d8a1d6944 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a4a57878b36cd3932c31e80e060366699469469a0ae3698c5a474107ecf3636 +size 9728 diff --git a/cases/MirrorRollingBall/scene_360_in/reference/artifacts/object_diameters.json b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/object_diameters.json new file mode 100644 index 0000000000000000000000000000000000000000..edfa9b6965bc4615e56d6f447bfeab80507905d4 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_in/reference/artifacts/object_diameters.json @@ -0,0 +1,5 @@ +{ + "yellow sphere": 1.3814, + "yellow sphere left foreground": 1.3814, + "yellow sphere right foreground": 1.3814 +} diff --git a/cases/MirrorRollingBall/scene_360_in/reference/artifacts/object_transforms.json 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+schema_version: 1 +trajectory_id: table7.camera.360_in_v1 +description: Nominal counter-clockwise full-yaw proxy for the paper's inward-facing condition. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 10.0, values: {yaw_rate_deg_s: -36.0}} +paper_alignment: + status: reconstructed + matched: [full_360_degree_camera_rotation, inward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes inward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git 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+8df3be99fa27f63d19ebac27891999db1ad8f6a29943d992c6c78bbe45b2612c reference/artifacts/object_transforms.json +a24246bb2eb0c5d08decaee31d3eff5292d1d29751715a444321a51f0ab6ea71 reference/artifacts/poses.npy +7bdc622be132bd0a4d13dca4bb93a1444e6cb85f8ee368fff90d56d23d2e6930 reference/artifacts/table_cell.json +16008bd3e1bd2b5497b424eab147eda7a7858572ce3d1afb5ccb62d509e9d6c4 reference/artifacts/trajectory.yaml +be9b5d8c0c8708a9d05644f39803024888d9830e734672e33ba7d9ffaa8b2fa4 reference/ref.png +f8f76184bf0f00f9b9c12ac731999ca0f96eb3df8b38ed3bf8f136711276edcf reference/reference.mp4 diff --git a/cases/MirrorRollingBall/scene_360_in/reference/ref.png b/cases/MirrorRollingBall/scene_360_in/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..cef53b361925e1ce05addaa2c43883de0977c1c9 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_in/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:be9b5d8c0c8708a9d05644f39803024888d9830e734672e33ba7d9ffaa8b2fa4 +size 413293 diff --git a/cases/MirrorRollingBall/scene_360_in/reference/reference.mp4 b/cases/MirrorRollingBall/scene_360_in/reference/reference.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..c986ef71efae4753e249e88a96710e41f2ac7985 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_in/reference/reference.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f8f76184bf0f00f9b9c12ac731999ca0f96eb3df8b38ed3bf8f136711276edcf +size 2953543 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npy b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..8798a3b24eb9f78f5158c973b343fad5ca80f8cb --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:242e5eac182551cc84ce4deb884905055a82aa62054c4b8523444fd1d35a4822 +size 928 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npz b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..bb4103314405fbedc2323fce157a2fd60bf472b0 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ddcda933deb456dbdc4ba913a4482a380b6af669534a1267d3be449489d534d +size 1558 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.jsonl b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..44d5b4904887601489fb1f5d5782249ac30bdcd3 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.jsonl @@ -0,0 +1 @@ +{"keys": ["ArrowRight"], "ms": 10000, "op": "hold", "target_yaw_deg": 360.0} diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.txt b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff19e91ba197f0397bb83d57a23339060e7e9fe6 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/actions.txt @@ -0,0 +1,8 @@ +# table7.camera.360_out_v1 -- generated action trajectory. +# Provenance: camera_360_out.yaml (semantic SHA-256: de3cce86bcf6f0ce53780a43057eaddae92d32fcc8df443a00de5ec28eb07d97) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 10.0 36.0 + +# Project Genie browser actions: +{"keys": ["ArrowRight"], "ms": 10000, "op": "hold", "target_yaw_deg": 360.0} diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/intrinsics.npy b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..32f2beb7dde66893fdfe8356ecf3594d8a1d6944 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a4a57878b36cd3932c31e80e060366699469469a0ae3698c5a474107ecf3636 +size 9728 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/object_diameters.json b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/object_diameters.json new file mode 100644 index 0000000000000000000000000000000000000000..edfa9b6965bc4615e56d6f447bfeab80507905d4 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/artifacts/object_diameters.json @@ -0,0 +1,5 @@ +{ + "yellow sphere": 1.3814, + "yellow sphere left foreground": 1.3814, + "yellow sphere right foreground": 1.3814 +} diff --git a/cases/MirrorRollingBall/scene_360_out/reference/artifacts/object_transforms.json 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+schema_version: 1 +trajectory_id: table7.camera.360_out_v1 +description: Nominal clockwise full-yaw proxy for the paper's outward-facing condition. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 10.0, values: {yaw_rate_deg_s: 36.0}} +paper_alignment: + status: reconstructed + matched: [full_360_degree_camera_rotation, outward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes outward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/MirrorRollingBall/scene_360_out/reference/checksums.sha256 b/cases/MirrorRollingBall/scene_360_out/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..a9a5e18aa9261d42db6a54d8f25ec33735fc27b5 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/checksums.sha256 @@ -0,0 +1,12 @@ +242e5eac182551cc84ce4deb884905055a82aa62054c4b8523444fd1d35a4822 reference/artifacts/action.npy +3ddcda933deb456dbdc4ba913a4482a380b6af669534a1267d3be449489d534d reference/artifacts/action.npz +3bc11afbe77c6fe29f9e26d1e5f6a7fcdeddbf3fe06119e2e2efbaa9cf401471 reference/artifacts/actions.jsonl +96bd8bc4f87eed01fac4cab5c7cea77727025f5af2fd642b412839789b4cf599 reference/artifacts/actions.txt +2a4a57878b36cd3932c31e80e060366699469469a0ae3698c5a474107ecf3636 reference/artifacts/intrinsics.npy +9778353bc1a415d80a06220d02f527ff8844e4cccf04aced4a38fada2958de1d reference/artifacts/object_diameters.json +01ca1ce6ebb7711912f24ad22606e6f3c1ab01d21858ede8ee4821faeb28922b reference/artifacts/object_transforms.json +398c0268af9f8f8e7394729ea6e9155724937275a40150840738a70bc1f3270d reference/artifacts/poses.npy +17f32c3c23cd60673f6b54ea1457d883c068f9805a80d1f232f6afa8a6527107 reference/artifacts/table_cell.json +de3cce86bcf6f0ce53780a43057eaddae92d32fcc8df443a00de5ec28eb07d97 reference/artifacts/trajectory.yaml +68e32f3eefb828f471afb38dd86f08dadd557d287b971979a22b52551eb950bd reference/ref.png +74718edb61a9c5a272afdae62c5df25f4ccef65c194b211ca84ec4a9b8aa972d reference/reference.mp4 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/ref.png b/cases/MirrorRollingBall/scene_360_out/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..f92ce40d826a680f0f21cb58e673fd1be22ebbc7 --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:68e32f3eefb828f471afb38dd86f08dadd557d287b971979a22b52551eb950bd +size 489706 diff --git a/cases/MirrorRollingBall/scene_360_out/reference/reference.mp4 b/cases/MirrorRollingBall/scene_360_out/reference/reference.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..344a4bea978f4acae9d284201e976845a587785f --- /dev/null +++ b/cases/MirrorRollingBall/scene_360_out/reference/reference.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:74718edb61a9c5a272afdae62c5df25f4ccef65c194b211ca84ec4a9b8aa972d +size 3068460 diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npy b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..2211e9b91c679a2e844b7b1e79010a0118a626e5 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:55171151a4042416c87105acbfe5f1017aa9e5340a6f73320bad60f84b1da6dc +size 928 diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npz b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..1145453953fcc8e4c6fbb355d6842bdd5ce43d3f --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbcc9bbb0473106a99b4c3907860d25cf7b5ca75d48d027053672649dff6eb4b +size 1557 diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.jsonl b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..de550e084831ef9b829588ed14d50c801d032fab --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.jsonl @@ -0,0 +1,2 @@ +{"keys": ["ArrowLeft"], "ms": 1250, "op": "hold", "target_yaw_deg": -45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.txt b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..054bde7c9929a52fa4bbd69c01510e5e43ebcaec --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/actions.txt @@ -0,0 +1,10 @@ +# table7.camera.perturb_in_v1 -- generated action trajectory. +# Provenance: camera_perturb_in.yaml (semantic SHA-256: ae53bd32c4359f1a1471b5dfa584ad4c27d41171eba55541e2b52e5e3993a1cf) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 1.25 -36.0 +1.25 10.0 0.0 + +# Project Genie browser actions: +{"keys": ["ArrowLeft"], "ms": 1250, "op": "hold", "target_yaw_deg": -45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/intrinsics.npy b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..32f2beb7dde66893fdfe8356ecf3594d8a1d6944 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a4a57878b36cd3932c31e80e060366699469469a0ae3698c5a474107ecf3636 +size 9728 diff --git a/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/object_diameters.json b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/object_diameters.json new file mode 100644 index 0000000000000000000000000000000000000000..edfa9b6965bc4615e56d6f447bfeab80507905d4 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_in/reference/artifacts/object_diameters.json @@ -0,0 +1,5 @@ +{ + "yellow sphere": 1.3814, + "yellow sphere left foreground": 1.3814, + 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+size 1558 diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.jsonl b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cb966160697781be73ea32d5a50eb82f0ae8971b --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.jsonl @@ -0,0 +1,2 @@ +{"keys": ["ArrowRight"], "ms": 1250, "op": "hold", "target_yaw_deg": 45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.txt b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec26e338d528541e98d3fe3a460f5ea066e41738 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/actions.txt @@ -0,0 +1,10 @@ +# table7.camera.perturb_out_v1 -- generated action trajectory. +# Provenance: camera_perturb_out.yaml (semantic SHA-256: 8f6169a0bd84b9f2ebadb8877086a985d8f6aa5affd0747dd974a96707ccee2f) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 1.25 36.0 +1.25 10.0 0.0 + +# Project Genie browser actions: +{"keys": ["ArrowRight"], "ms": 1250, "op": "hold", "target_yaw_deg": 45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/intrinsics.npy b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..32f2beb7dde66893fdfe8356ecf3594d8a1d6944 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:2a4a57878b36cd3932c31e80e060366699469469a0ae3698c5a474107ecf3636 +size 9728 diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_diameters.json b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_diameters.json new file mode 100644 index 0000000000000000000000000000000000000000..edfa9b6965bc4615e56d6f447bfeab80507905d4 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_diameters.json @@ -0,0 +1,5 @@ +{ + "yellow sphere": 1.3814, + "yellow sphere left foreground": 1.3814, + "yellow sphere right foreground": 1.3814 +} diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_transforms.json b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_transforms.json new file mode 100644 index 0000000000000000000000000000000000000000..ef1407f9576b89ecbfb69ab1bda239cb588c47ac --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/artifacts/object_transforms.json @@ -0,0 +1,5435 @@ +{ + "objects": { + "yellow sphere": { + "frames": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 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+description: Nominal clockwise 45-degree yaw proxy for the paper's outward-facing condition, then hold. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 1.25, values: {yaw_rate_deg_s: 36.0}} + - {start_sec: 1.25, end_sec: 10.0, values: {yaw_rate_deg_s: 0.0}} +paper_alignment: + status: reconstructed + matched: [camera_perturbation, nominal_45_degrees, outward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes outward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: 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sha256:68e32f3eefb828f471afb38dd86f08dadd557d287b971979a22b52551eb950bd +size 489706 diff --git a/cases/MirrorRollingBall/scene_perturb_out/reference/reference.mp4 b/cases/MirrorRollingBall/scene_perturb_out/reference/reference.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..20dc7598df5c08fc11667a4e837f8833ae50bf86 --- /dev/null +++ b/cases/MirrorRollingBall/scene_perturb_out/reference/reference.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:feeb92c00c995c0b2ff55c5b152c28a27f5bb788208d0552fa3bf1b0172d9256 +size 596893 diff --git a/cases/RacingCar/kinematics_third/reference/artifacts/action.npy b/cases/RacingCar/kinematics_third/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..03c07ebd559b641a59bb8a27017c90d0ce759991 --- /dev/null +++ b/cases/RacingCar/kinematics_third/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:62497898bad2ece4a9092e71fd4228daac8683a8b2aeaddb35763a1f58e64f57 +size 3728 diff --git a/cases/RacingCar/kinematics_third/reference/artifacts/action.npz b/cases/RacingCar/kinematics_third/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..a5fb866354d052ae9786081103fc738376ed95f8 --- /dev/null +++ b/cases/RacingCar/kinematics_third/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dc30f4a4d5751341705cfa1f8ea8c57dbbf86039955b0a5d43b49390fcf87324 +size 1869 diff --git a/cases/RacingCar/kinematics_third/reference/artifacts/actions.jsonl b/cases/RacingCar/kinematics_third/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..8c3e09d3b7d60b0c0db571038ff7878db304f458 --- /dev/null +++ b/cases/RacingCar/kinematics_third/reference/artifacts/actions.jsonl @@ -0,0 +1,8 @@ +{"ms": 1000, "op": "wait"} +{"keys": ["KeyW"], "ms": 2000, "op": "hold"} +{"keys": ["KeyD", "KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyW"], "ms": 2000, "op": "hold"} +{"keys": ["KeyA", "KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyS"], "ms": 1000, "op": "hold"} +{"ms": 1000, "op": "wait"} diff --git a/cases/RacingCar/kinematics_third/reference/artifacts/actions.txt b/cases/RacingCar/kinematics_third/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..0a3457908881968097b476712af29bb37ec4d96c --- /dev/null +++ b/cases/RacingCar/kinematics_third/reference/artifacts/actions.txt @@ -0,0 +1,22 @@ +# table4.racing_car.drive_v1 -- generated action trajectory. +# Provenance: racing_car_drive.yaml (semantic SHA-256: 34df3d31dfef5c0613d5536159b9f20d63bbbd0ad0c1a93408b491e960b79448) +# Alignment: reconstructed; 300 steps; channels: steer, throttle, brake +# start_s end_s steer throttle brake +0.0 1.0 0.0 0.0 0 +1.0 3.0 0.0 0.8 0 +3.0 4.0 0.5 0.6 0 +4.0 6.0 0.0 0.8 0 +6.0 7.0 -0.5 0.6 0 +7.0 8.0 0.0 0.8 0 +8.0 9.0 0.0 0.0 1 +9.0 10.0 0.0 0.0 0 + +# Project Genie browser actions: +{"ms": 1000, "op": "wait"} +{"keys": ["KeyW"], "ms": 2000, "op": "hold"} +{"keys": ["KeyD", "KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyW"], "ms": 2000, "op": "hold"} +{"keys": ["KeyA", "KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyW"], "ms": 1000, "op": "hold"} +{"keys": ["KeyS"], "ms": 1000, "op": "hold"} +{"ms": 1000, "op": "wait"} diff --git a/cases/RacingCar/kinematics_third/reference/artifacts/intrinsics.npy b/cases/RacingCar/kinematics_third/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..67d72d20aa472c24d8da8cb8be174843b4c8deee --- /dev/null +++ b/cases/RacingCar/kinematics_third/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dc51c0c86fbb9f0781d16cd266805d3d3928788f04c81165cc1cd9d67fdf5e5d +size 9728 diff --git 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end_sec: 4.0, values: {steer: 0.5, throttle: 0.6, brake: 0}} + - {start_sec: 4.0, end_sec: 6.0, values: {steer: 0.0, throttle: 0.8, brake: 0}} + - {start_sec: 6.0, end_sec: 7.0, values: {steer: -0.5, throttle: 0.6, brake: 0}} + - {start_sec: 7.0, end_sec: 8.0, values: {steer: 0.0, throttle: 0.8, brake: 0}} + - {start_sec: 8.0, end_sec: 9.0, values: {steer: 0.0, throttle: 0.0, brake: 1}} + - {start_sec: 9.0, end_sec: 10.0, values: {steer: 0.0, throttle: 0.0, brake: 0}} +paper_alignment: + status: reconstructed + matched: [scene, action_space, first_and_third_person_views, five_generations, metrics] + missing: The paper source does not publish its numeric per-step control timeline. + source: ../../../../_arxiv__WorldModel_Eval/text/7_appendix_scenes.tex + repository_context: >- + The Lite RacingCar action.npy has five model-adapter channels and its + actions.txt describes a camera turn; it is not the Unity CarAgent action + schema. 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"setview", "key": "first", "note": "start in first-person (car model hidden)"}, + {"op": "hold", "key": "ArrowLeft", "ms": 10000, "note": "rotate left for 10 seconds"} +] diff --git a/cases/RacingCar/prompt_first/reference/artifacts/intrinsics.npy b/cases/RacingCar/prompt_first/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..4e80238e8d4b0e89280c57fcdab408f1097f541e --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:09a931870011be953373d75242851177e9667607b4b0856ee85800d70c6edffb +size 164 diff --git a/cases/RacingCar/prompt_first/reference/artifacts/poses.npy b/cases/RacingCar/prompt_first/reference/artifacts/poses.npy new file mode 100644 index 0000000000000000000000000000000000000000..184cd4ed8c368bf02b7d86347b7c30620661d5a6 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/artifacts/poses.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f5ec3c693442cf6955934f66c69de94dc012aa0efbc1009b0b56db832a6e82f2 +size 19328 diff --git a/cases/RacingCar/prompt_first/reference/artifacts/reference_scores.json b/cases/RacingCar/prompt_first/reference/artifacts/reference_scores.json new file mode 100644 index 0000000000000000000000000000000000000000..ac02155e1069a12f01abe55770dec6a649c69c12 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/artifacts/reference_scores.json @@ -0,0 +1,1116 @@ +{ + "case_id": "RacingCar/prompt_first", + "created_utc": "2026-10-14T07:11:42+00:00", + "dimension": "prompt_scene_consistency", + "judge": { + "alpha": 0.6, + "first_frame_sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f", + "model": "gpt-5.4", + "prompt_version": "v0", + "provider": "openai", + "rubric": "reference/artifacts/rubrics/RacingCar_first/openai_gpt-5-4_v0.json", + "rubric_sha256": "3c680e5db7e22656e87e494fd4bcad7a730c5fdfe9d87ba1a3ee2c41d9927398", + "sample_duration_sec": 10.0, + "sample_frames": 18, + "system_prompt_sha256": { + "environment": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "object": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2" + } + }, + "judge_model_resolved": [ + "gpt-5.4-2026-03-05" + ], + "passes": [ + { + "env_score": 0.8, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Roadside symmetry breaks in the middle frames, with one side opening to sky instead of showing matching trees and barriers.", + "Green grass is not clearly established as a consistent roadside ground feature.", + "Several frames show abrupt vertical cutoffs of the tree wall against the sky, reducing environmental realism and cleanliness." + ], + "summary": "The video matches the prompt well on the wide straight highway, clear blue sky, suspended-road starting point, and bright daytime look. The main weakness is inconsistency in the roadside environment, especially the loss of trees/barriers on one side in the middle section and visible hard-edged scene artifacts." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The video consistently depicts a straight paved roadway with multiple lanes and lane markings. In the opening and closing centered views, the highway appears very wide and extends straight to the horizon, matching the prompt well (frame_t=0.0s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). During the mid-video lateral pan, the camera shifts toward the side, so the full width is less visible, but the road surface remains broad and straight with no curves introduced (frame_t=1.1s, frame_t=1.7s, frame_t=6.7s, frame_t=7.2s). Because width is most evident in several frames and straightness is maintained throughout, this is a strong match.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "Across all sampled frames, the sky remains a bright, clear blue with no visible clouds, storminess, sunset tones, or darkening. This is evident in the centered highway views (frame_t=0.0s, frame_t=8.9s) and also in the suspended-road views where the sky dominates the frame (frame_t=3.9s, frame_t=4.4s, frame_t=5.0s). There is no meaningful color shift or weather change across time.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt asks for both sides to consistently show dark barriers, green grass, and long symmetrical rows of tall trees. Dark roadside barriers and tall tree rows are clearly present in many frames, especially at the start and end where both sides are visible symmetrically (frame_t=0.0s, frame_t=8.3s, frame_t=8.9s). However, the video becomes inconsistent in the middle: several frames show only one side with trees, while the other side drops away into open sky as the road appears suspended (frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s). Also, green grass is not clearly visible as a distinct roadside ground feature; only sparse low vegetation appears beneath trees in some frames. Because the full both-sides configuration is missing in a substantial portion of the video, this only partially matches.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s" + ], + "judged_score": 3, + "reasoning": "This attribute is strongly supported in the middle section. Several frames clearly show the road ending abruptly at a starting edge, with open sky behind it and no ground visible beyond the edge, creating the suspended-in-space look described in the prompt (frame_t=3.9s, frame_t=4.4s, frame_t=5.0s). Earlier and later frames show the camera away from that starting edge, so the abrupt beginning is not always visible, but when relevant it is depicted clearly and consistently. Since the prompt describes a specific environmental feature rather than something that must dominate every frame, the visible representation is strong.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=5.0s", + "frame_t=6.7s", + "frame_t=8.3s" + ], + "judged_score": 2, + "reasoning": "The scene maintains bright daytime illumination throughout. The road, barriers, and trees are evenly lit without nighttime darkness or dramatic shadow shifts (frame_t=0.0s, frame_t=1.1s, frame_t=8.3s). The overall style is sparse and uncluttered, with a minimal environment made up mainly of road, barriers, trees, and sky. However, there are noticeable environmental artifacts in the middle frames, including hard cut-like vertical edges where tree walls terminate abruptly against empty sky, which slightly reduces the clean look (frame_t=2.2s, frame_t=2.8s, frame_t=5.0s, frame_t=6.7s). So the match is strong but not perfect.", + "rubric_id": "env_05" + } + ], + "score": 0.8 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f" + }, + { + "label": "frame_t=0.0s", + "sha256": "d47ace44980ed2301e0bdba813617fd4f8c734e233cf9f8c6418e604a6a48290" + }, + { + "label": "frame_t=0.6s", + "sha256": "6f045138b6e7fd617eacea49743d8e58a7acf96ae29f1a077ba36331eb6ab623" + }, + { + "label": "frame_t=1.1s", + "sha256": "927201c13d02bd37962d617a59c8128e87f3f2347bfda0c2998ea5163d682840" + }, + { + "label": "frame_t=1.7s", + "sha256": "5f921f012e6dd548baf4f5aea54cf60e3912609d03ebbe4d38dd1580eefdb97b" + }, + { + "label": "frame_t=2.2s", + "sha256": "7e54bb28614ad256d33996b4316ce37131f0fb29b34c8ba45dfc793e06f4dc4c" + }, + { + "label": "frame_t=2.8s", + "sha256": "350244b241c2fcb42118b7360aa80c2e54508805335e0a5a8be35085e5398820" + }, + { + "label": "frame_t=3.3s", + "sha256": "c275d4422524c646aad93670ab63e23076576ed0ec906470353d41cb08cbaf43" + }, + { + "label": "frame_t=3.9s", + "sha256": "1b6433e6089837c604a58fceb9d700398cdee2e3c015988b6da494d59c81d019" + }, + { + "label": "frame_t=4.4s", + "sha256": "6ffa612eee55482a4ff3c2c637f77b9a5bee443d347042b27c446542651b46aa" + }, + { + "label": "frame_t=5.0s", + "sha256": "1341cb2da73ba88bc004594d05f47de9de90f1f1379b5b98a812cb6fb24090df" + }, + { + "label": "frame_t=5.6s", + "sha256": "b93356c5a57afe65207cb72cb67b083f57318d8523319e60e19fcf3f38e9b595" + }, + { + "label": "frame_t=6.1s", + "sha256": "68f93a161c3aa6e574913bfed0b7ec403015b6c8ce0a1bbc93309cff5df660ce" + }, + { + "label": "frame_t=6.7s", + "sha256": "a3ab1dbf1cd293c9f0f2d6db5588fb9859cec3a3816ad34071cd8658ba1f3fa0" + }, + { + "label": "frame_t=7.2s", + "sha256": "15934cfb9cda87760b7469d5d83e520aeae30ea48d36f5177bbbe4d8b880bce3" + }, + { + "label": "frame_t=7.8s", + "sha256": "0feea8aee060858bab2a8809e37f440eebd655c6e7fbd18ed24e78d80c897e4d" + }, + { + "label": "frame_t=8.3s", + "sha256": "dbde9ced874c027d1e53fd2e9977714076412601d9c01faacaef27a0309db73a" + }, + { + "label": "frame_t=8.9s", + "sha256": "c02f06f0bfe36999e8c03b7227ac2ad7befc73cf6233ad443515c503743edc16" + }, + { + "label": "frame_t=9.4s", + "sha256": "32331d3e7e63347b98fe0cb0edbf6e7c73cc42626ebcb80859d58c5413579213" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway across all frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?\n\n### env_04\nRubric: Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?\n\n### env_05\nRubric: Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961878, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The video consistently depicts a straight paved roadway with multiple lanes and lane markings. In the opening and closing centered views, the highway appears very wide and extends straight to the horizon, matching the prompt well (frame_t=0.0s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). During the mid-video lateral pan, the camera shifts toward the side, so the full width is less visible, but the road surface remains broad and straight with no curves introduced (frame_t=1.1s, frame_t=1.7s, frame_t=6.7s, frame_t=7.2s). Because width is most evident in several frames and straightness is maintained throughout, this is a strong match.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"Across all sampled frames, the sky remains a bright, clear blue with no visible clouds, storminess, sunset tones, or darkening. This is evident in the centered highway views (frame_t=0.0s, frame_t=8.9s) and also in the suspended-road views where the sky dominates the frame (frame_t=3.9s, frame_t=4.4s, frame_t=5.0s). There is no meaningful color shift or weather change across time.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt asks for both sides to consistently show dark barriers, green grass, and long symmetrical rows of tall trees. Dark roadside barriers and tall tree rows are clearly present in many frames, especially at the start and end where both sides are visible symmetrically (frame_t=0.0s, frame_t=8.3s, frame_t=8.9s). However, the video becomes inconsistent in the middle: several frames show only one side with trees, while the other side drops away into open sky as the road appears suspended (frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s). Also, green grass is not clearly visible as a distinct roadside ground feature; only sparse low vegetation appears beneath trees in some frames. Because the full both-sides configuration is missing in a substantial portion of the video, this only partially matches.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_04\",\"reasoning\":\"This attribute is strongly supported in the middle section. Several frames clearly show the road ending abruptly at a starting edge, with open sky behind it and no ground visible beyond the edge, creating the suspended-in-space look described in the prompt (frame_t=3.9s, frame_t=4.4s, frame_t=5.0s). Earlier and later frames show the camera away from that starting edge, so the abrupt beginning is not always visible, but when relevant it is depicted clearly and consistently. Since the prompt describes a specific environmental feature rather than something that must dominate every frame, the visible representation is strong.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\"],\"judged_score\":3},{\"rubric_id\":\"env_05\",\"reasoning\":\"The scene maintains bright daytime illumination throughout. The road, barriers, and trees are evenly lit without nighttime darkness or dramatic shadow shifts (frame_t=0.0s, frame_t=1.1s, frame_t=8.3s). The overall style is sparse and uncluttered, with a minimal environment made up mainly of road, barriers, trees, and sky. However, there are noticeable environmental artifacts in the middle frames, including hard cut-like vertical edges where tree walls terminate abruptly against empty sky, which slightly reduces the clean look (frame_t=2.2s, frame_t=2.8s, frame_t=5.0s, frame_t=6.7s). So the match is strong but not perfect.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=5.0s\",\"frame_t=6.7s\",\"frame_t=8.3s\"],\"judged_score\":2}],\"explanations\":{\"summary\":\"The video matches the prompt well on the wide straight highway, clear blue sky, suspended-road starting point, and bright daytime look. The main weakness is inconsistency in the roadside environment, especially the loss of trees/barriers on one side in the middle section and visible hard-edged scene artifacts.\",\"issues\":[\"Roadside symmetry breaks in the middle frames, with one side opening to sky instead of showing matching trees and barriers.\",\"Green grass is not clearly established as a consistent roadside ground feature.\",\"Several frames show abrupt vertical cutoffs of the tree wall against the sky, reducing environmental realism and cleanliness.\"]}}", + "provider": "openai", + "response_id": "resp_0f20b02dca2f4530006acf2b16388087d0a174101d1c1e3fd5", + "usage": { + "input_tokens": 22512, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 0 + }, + "output_tokens": 1190, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23702 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "(no object rubrics to evaluate)" + }, + "item_scores": [], + "score": null + }, + "overall_score": 0.8, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 5 + }, + "scene_name": "RacingCar_first" + }, + "obj_score": null, + "overall_score": 0.8, + "pass": 1 + }, + { + "env_score": 0.9333, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Green grass is weak or ambiguous; low vegetation is visible but not a clear grassy strip.", + "Both sides of the roadside environment are not visible in a substantial middle portion of the clip, limiting verification of continuous symmetry across all frames." + ], + "summary": "The video aligns well with the prompt overall: it shows a wide straight highway, clear blue sky, bright daytime lighting, and the suspended-road starting point effectively. The main weakness is that the grass component is not clearly visible and both roadside symmetry cannot be verified in every frame due to the camera angle." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The road is clearly a wide multi-lane highway and remains straight throughout the clip. In the centered views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, the highway extends straight to a central vanishing point and appears very wide. During the side-looking portions at frame_t=1.1s through frame_t=7.2s, the camera angle shifts, but the visible lane markings and barrier alignment still indicate a straight roadway rather than a curved one. Width also remains substantial in these oblique views. There is no evidence of bends or narrowing; only the camera pans laterally.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The sky appears consistently clear and blue in every sampled frame. At frame_t=0.0s and frame_t=8.9s the sky is a uniform light blue over the full road scene. In the suspended-road views around frame_t=3.9s to frame_t=5.6s, the large visible sky area remains clear, without clouds, darkening, or color shifts. No frame shows overcast conditions or a different sky palette.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=6.7s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "The prompt asks for both sides to consistently show dark barriers, green grass, and long symmetrical rows of tall trees. In the balanced highway views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, both sides do show dark roadside barriers and long rows of tall green trees in a highly symmetrical arrangement. However, during many middle frames, only one side is visible because of the camera angle, so both sides cannot be verified there. Also, the green grass is not clearly visible as a distinct grassy strip; instead there are dark barriers with some low vegetation/bushes at the base of the trees. Because the barriers and trees match strongly but the explicit grass component is weak/ambiguous and both-side visibility is incomplete for a substantial portion, this is a partial rather than perfect match.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=5.6s" + ], + "judged_score": 3, + "reasoning": "This attribute is well supported in the middle of the clip. Around frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, and frame_t=5.0s, the road reaches an abrupt edge with open sky beyond it and no visible ground behind, strongly matching the suspended-in-space starting-point concept. The effect is especially clear at frame_t=4.4s where both left and right road edges terminate against open sky. Earlier and later frames return to the normal forward-facing highway view, so the abrupt starting point is not visible at all times, but when the relevant starting-point region is shown, it matches the prompt very well.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The video maintains bright daytime lighting and a clean, minimal environment across all frames. The road, trees, and barriers are evenly lit with no nighttime or dim conditions, as seen at frame_t=0.0s, frame_t=4.4s, and frame_t=8.9s. The scene remains sparse and uncluttered, with only the highway, barriers, trees, and sky visible. No environmental debris, weather effects, or complex background structures appear. The overall palette and rendering stay consistent with a minimal daytime scene.", + "rubric_id": "env_05" + } + ], + "score": 0.9333 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f" + }, + { + "label": "frame_t=0.0s", + "sha256": "d47ace44980ed2301e0bdba813617fd4f8c734e233cf9f8c6418e604a6a48290" + }, + { + "label": "frame_t=0.6s", + "sha256": "6f045138b6e7fd617eacea49743d8e58a7acf96ae29f1a077ba36331eb6ab623" + }, + { + "label": "frame_t=1.1s", + "sha256": "927201c13d02bd37962d617a59c8128e87f3f2347bfda0c2998ea5163d682840" + }, + { + "label": "frame_t=1.7s", + "sha256": "5f921f012e6dd548baf4f5aea54cf60e3912609d03ebbe4d38dd1580eefdb97b" + }, + { + "label": "frame_t=2.2s", + "sha256": "7e54bb28614ad256d33996b4316ce37131f0fb29b34c8ba45dfc793e06f4dc4c" + }, + { + "label": "frame_t=2.8s", + "sha256": "350244b241c2fcb42118b7360aa80c2e54508805335e0a5a8be35085e5398820" + }, + { + "label": "frame_t=3.3s", + "sha256": "c275d4422524c646aad93670ab63e23076576ed0ec906470353d41cb08cbaf43" + }, + { + "label": "frame_t=3.9s", + "sha256": "1b6433e6089837c604a58fceb9d700398cdee2e3c015988b6da494d59c81d019" + }, + { + "label": "frame_t=4.4s", + "sha256": "6ffa612eee55482a4ff3c2c637f77b9a5bee443d347042b27c446542651b46aa" + }, + { + "label": "frame_t=5.0s", + "sha256": "1341cb2da73ba88bc004594d05f47de9de90f1f1379b5b98a812cb6fb24090df" + }, + { + "label": "frame_t=5.6s", + "sha256": "b93356c5a57afe65207cb72cb67b083f57318d8523319e60e19fcf3f38e9b595" + }, + { + "label": "frame_t=6.1s", + "sha256": "68f93a161c3aa6e574913bfed0b7ec403015b6c8ce0a1bbc93309cff5df660ce" + }, + { + "label": "frame_t=6.7s", + "sha256": "a3ab1dbf1cd293c9f0f2d6db5588fb9859cec3a3816ad34071cd8658ba1f3fa0" + }, + { + "label": "frame_t=7.2s", + "sha256": "15934cfb9cda87760b7469d5d83e520aeae30ea48d36f5177bbbe4d8b880bce3" + }, + { + "label": "frame_t=7.8s", + "sha256": "0feea8aee060858bab2a8809e37f440eebd655c6e7fbd18ed24e78d80c897e4d" + }, + { + "label": "frame_t=8.3s", + "sha256": "dbde9ced874c027d1e53fd2e9977714076412601d9c01faacaef27a0309db73a" + }, + { + "label": "frame_t=8.9s", + "sha256": "c02f06f0bfe36999e8c03b7227ac2ad7befc73cf6233ad443515c503743edc16" + }, + { + "label": "frame_t=9.4s", + "sha256": "32331d3e7e63347b98fe0cb0edbf6e7c73cc42626ebcb80859d58c5413579213" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway across all frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?\n\n### env_04\nRubric: Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?\n\n### env_05\nRubric: Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961880, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The road is clearly a wide multi-lane highway and remains straight throughout the clip. In the centered views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, the highway extends straight to a central vanishing point and appears very wide. During the side-looking portions at frame_t=1.1s through frame_t=7.2s, the camera angle shifts, but the visible lane markings and barrier alignment still indicate a straight roadway rather than a curved one. Width also remains substantial in these oblique views. There is no evidence of bends or narrowing; only the camera pans laterally.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The sky appears consistently clear and blue in every sampled frame. At frame_t=0.0s and frame_t=8.9s the sky is a uniform light blue over the full road scene. In the suspended-road views around frame_t=3.9s to frame_t=5.6s, the large visible sky area remains clear, without clouds, darkening, or color shifts. No frame shows overcast conditions or a different sky palette.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt asks for both sides to consistently show dark barriers, green grass, and long symmetrical rows of tall trees. In the balanced highway views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, both sides do show dark roadside barriers and long rows of tall green trees in a highly symmetrical arrangement. However, during many middle frames, only one side is visible because of the camera angle, so both sides cannot be verified there. Also, the green grass is not clearly visible as a distinct grassy strip; instead there are dark barriers with some low vegetation/bushes at the base of the trees. Because the barriers and trees match strongly but the explicit grass component is weak/ambiguous and both-side visibility is incomplete for a substantial portion, this is a partial rather than perfect match.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=6.7s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":2},{\"rubric_id\":\"env_04\",\"reasoning\":\"This attribute is well supported in the middle of the clip. Around frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, and frame_t=5.0s, the road reaches an abrupt edge with open sky beyond it and no visible ground behind, strongly matching the suspended-in-space starting-point concept. The effect is especially clear at frame_t=4.4s where both left and right road edges terminate against open sky. Earlier and later frames return to the normal forward-facing highway view, so the abrupt starting point is not visible at all times, but when the relevant starting-point region is shown, it matches the prompt very well.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=5.6s\"],\"judged_score\":3},{\"rubric_id\":\"env_05\",\"reasoning\":\"The video maintains bright daytime lighting and a clean, minimal environment across all frames. The road, trees, and barriers are evenly lit with no nighttime or dim conditions, as seen at frame_t=0.0s, frame_t=4.4s, and frame_t=8.9s. The scene remains sparse and uncluttered, with only the highway, barriers, trees, and sky visible. No environmental debris, weather effects, or complex background structures appear. The overall palette and rendering stay consistent with a minimal daytime scene.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=8.9s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video aligns well with the prompt overall: it shows a wide straight highway, clear blue sky, bright daytime lighting, and the suspended-road starting point effectively. The main weakness is that the grass component is not clearly visible and both roadside symmetry cannot be verified in every frame due to the camera angle.\",\"issues\":[\"Green grass is weak or ambiguous; low vegetation is visible but not a clear grassy strip.\",\"Both sides of the roadside environment are not visible in a substantial middle portion of the clip, limiting verification of continuous symmetry across all frames.\"]}}", + "provider": "openai", + "response_id": "resp_0bc7ff8ffd724755006acf2b18d6c887d0bce9788c431244b8", + "usage": { + "input_tokens": 22512, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1079, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23591 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "(no object rubrics to evaluate)" + }, + "item_scores": [], + "score": null + }, + "overall_score": 0.9333, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 5 + }, + "scene_name": "RacingCar_first" + }, + "obj_score": null, + "overall_score": 0.9333, + "pass": 2 + }, + { + "env_score": 0.8667, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Symmetrical tree-lined roadside on both sides is not maintained clearly across the full video, especially in the middle frames.", + "Green grass is only weakly visible and not consistently distinct as a roadside element.", + "Some frames show abrupt environmental edge geometry where the tree line ends, creating mild artificiality." + ], + "summary": "The video matches the prompt well on highway width/straightness, clear blue sky, suspended starting-point effect, and bright minimal daytime lighting. The main weakness is inconsistent visibility of the full symmetrical two-sided roadside environment across the middle frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.7s", + "frame_t=4.4s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The video consistently depicts a straight multi-lane highway. In the opening frames, the road is very wide and clearly straight, receding to a central vanishing point in frame_t=0.0s, frame_t=0.6s, and frame_t=8.9s. During the lateral camera sweep, the road remains flat and straight even when only one side is emphasized, as seen in frame_t=1.7s, frame_t=6.7s, and frame_t=7.8s. However, around the middle section, the framing focuses strongly on the road edge and horizon, reducing clear visibility of the full highway width; still, the visible roadway remains broad rather than narrow in frame_t=3.9s and frame_t=4.4s. Overall the environmental attribute is present throughout with only minor framing ambiguity.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "Across all sampled frames, the sky remains a uniform clear blue. It is visibly bright and cloudless in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=6.7s, and frame_t=9.4s. There are no transitions to darker lighting, no visible clouds, and no major hue shifts. The mid-video frames with large open-sky regions especially confirm this consistency, such as frame_t=3.9s and frame_t=4.4s.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=6.7s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt asks for dark barriers, green grass, and long symmetrical rows of tall trees on both sides. The opening and closing frames match this well: frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s show dark roadside barriers on both sides and long rows of tall green trees arranged symmetrically. However, the middle portion becomes inconsistent. In frame_t=2.2s through frame_t=6.7s, the camera reveals only one tree-lined side prominently while the opposite side often drops out of view and is replaced by open sky at the horizon edge, which breaks the sense of both-sided symmetry across all frames. Also, green grass is only weakly visible as sparse low vegetation rather than clearly readable grass strips in many frames. Because the attribute matches strongly in some frames but not consistently across the whole video, the score should be reduced.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies that the road begins abruptly at a starting point with no ground behind it, only open sky, as if suspended in space. This unusual environmental condition is clearly visible in the middle of the sequence. Frame_t=3.3s, frame_t=3.9s, and especially frame_t=4.4s show the highway cresting into empty sky with no terrain behind it, closely matching the suspended-starting-point description. Earlier and later frames return to the standard long-highway view, but they do not contradict the attribute; they simply show the road after the start point from a different angle. The open-sky-behind-road effect is clear and well represented where relevant.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The environment remains brightly lit with a clean, minimal daytime appearance throughout. The road, barriers, trees, and sky are evenly illuminated in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. There are no nighttime conditions, dramatic shadows, haze, clutter, or additional environmental elements that would break the minimal style. The mid-sequence open-sky views even reinforce the sparse, minimal aesthetic. The only minor issue is some artificial-looking geometry at the tree-wall edges, but brightness and overall clean daytime styling remain consistent.", + "rubric_id": "env_05" + } + ], + "score": 0.8667 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f" + }, + { + "label": "frame_t=0.0s", + "sha256": "d47ace44980ed2301e0bdba813617fd4f8c734e233cf9f8c6418e604a6a48290" + }, + { + "label": "frame_t=0.6s", + "sha256": "6f045138b6e7fd617eacea49743d8e58a7acf96ae29f1a077ba36331eb6ab623" + }, + { + "label": "frame_t=1.1s", + "sha256": "927201c13d02bd37962d617a59c8128e87f3f2347bfda0c2998ea5163d682840" + }, + { + "label": "frame_t=1.7s", + "sha256": "5f921f012e6dd548baf4f5aea54cf60e3912609d03ebbe4d38dd1580eefdb97b" + }, + { + "label": "frame_t=2.2s", + "sha256": "7e54bb28614ad256d33996b4316ce37131f0fb29b34c8ba45dfc793e06f4dc4c" + }, + { + "label": "frame_t=2.8s", + "sha256": "350244b241c2fcb42118b7360aa80c2e54508805335e0a5a8be35085e5398820" + }, + { + "label": "frame_t=3.3s", + "sha256": "c275d4422524c646aad93670ab63e23076576ed0ec906470353d41cb08cbaf43" + }, + { + "label": "frame_t=3.9s", + "sha256": "1b6433e6089837c604a58fceb9d700398cdee2e3c015988b6da494d59c81d019" + }, + { + "label": "frame_t=4.4s", + "sha256": "6ffa612eee55482a4ff3c2c637f77b9a5bee443d347042b27c446542651b46aa" + }, + { + "label": "frame_t=5.0s", + "sha256": "1341cb2da73ba88bc004594d05f47de9de90f1f1379b5b98a812cb6fb24090df" + }, + { + "label": "frame_t=5.6s", + "sha256": "b93356c5a57afe65207cb72cb67b083f57318d8523319e60e19fcf3f38e9b595" + }, + { + "label": "frame_t=6.1s", + "sha256": "68f93a161c3aa6e574913bfed0b7ec403015b6c8ce0a1bbc93309cff5df660ce" + }, + { + "label": "frame_t=6.7s", + "sha256": "a3ab1dbf1cd293c9f0f2d6db5588fb9859cec3a3816ad34071cd8658ba1f3fa0" + }, + { + "label": "frame_t=7.2s", + "sha256": "15934cfb9cda87760b7469d5d83e520aeae30ea48d36f5177bbbe4d8b880bce3" + }, + { + "label": "frame_t=7.8s", + "sha256": "0feea8aee060858bab2a8809e37f440eebd655c6e7fbd18ed24e78d80c897e4d" + }, + { + "label": "frame_t=8.3s", + "sha256": "dbde9ced874c027d1e53fd2e9977714076412601d9c01faacaef27a0309db73a" + }, + { + "label": "frame_t=8.9s", + "sha256": "c02f06f0bfe36999e8c03b7227ac2ad7befc73cf6233ad443515c503743edc16" + }, + { + "label": "frame_t=9.4s", + "sha256": "32331d3e7e63347b98fe0cb0edbf6e7c73cc42626ebcb80859d58c5413579213" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway across all frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?\n\n### env_04\nRubric: Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?\n\n### env_05\nRubric: Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961880, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The video consistently depicts a straight multi-lane highway. In the opening frames, the road is very wide and clearly straight, receding to a central vanishing point in frame_t=0.0s, frame_t=0.6s, and frame_t=8.9s. During the lateral camera sweep, the road remains flat and straight even when only one side is emphasized, as seen in frame_t=1.7s, frame_t=6.7s, and frame_t=7.8s. However, around the middle section, the framing focuses strongly on the road edge and horizon, reducing clear visibility of the full highway width; still, the visible roadway remains broad rather than narrow in frame_t=3.9s and frame_t=4.4s. Overall the environmental attribute is present throughout with only minor framing ambiguity.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.7s\",\"frame_t=4.4s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"Across all sampled frames, the sky remains a uniform clear blue. It is visibly bright and cloudless in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=6.7s, and frame_t=9.4s. There are no transitions to darker lighting, no visible clouds, and no major hue shifts. The mid-video frames with large open-sky regions especially confirm this consistency, such as frame_t=3.9s and frame_t=4.4s.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt asks for dark barriers, green grass, and long symmetrical rows of tall trees on both sides. The opening and closing frames match this well: frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s show dark roadside barriers on both sides and long rows of tall green trees arranged symmetrically. However, the middle portion becomes inconsistent. In frame_t=2.2s through frame_t=6.7s, the camera reveals only one tree-lined side prominently while the opposite side often drops out of view and is replaced by open sky at the horizon edge, which breaks the sense of both-sided symmetry across all frames. Also, green grass is only weakly visible as sparse low vegetation rather than clearly readable grass strips in many frames. Because the attribute matches strongly in some frames but not consistently across the whole video, the score should be reduced.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=6.7s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt specifies that the road begins abruptly at a starting point with no ground behind it, only open sky, as if suspended in space. This unusual environmental condition is clearly visible in the middle of the sequence. Frame_t=3.3s, frame_t=3.9s, and especially frame_t=4.4s show the highway cresting into empty sky with no terrain behind it, closely matching the suspended-starting-point description. Earlier and later frames return to the standard long-highway view, but they do not contradict the attribute; they simply show the road after the start point from a different angle. The open-sky-behind-road effect is clear and well represented where relevant.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\"],\"judged_score\":3},{\"rubric_id\":\"env_05\",\"reasoning\":\"The environment remains brightly lit with a clean, minimal daytime appearance throughout. The road, barriers, trees, and sky are evenly illuminated in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. There are no nighttime conditions, dramatic shadows, haze, clutter, or additional environmental elements that would break the minimal style. The mid-sequence open-sky views even reinforce the sparse, minimal aesthetic. The only minor issue is some artificial-looking geometry at the tree-wall edges, but brightness and overall clean daytime styling remain consistent.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=9.4s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt well on highway width/straightness, clear blue sky, suspended starting-point effect, and bright minimal daytime lighting. The main weakness is inconsistent visibility of the full symmetrical two-sided roadside environment across the middle frames.\",\"issues\":[\"Symmetrical tree-lined roadside on both sides is not maintained clearly across the full video, especially in the middle frames.\",\"Green grass is only weakly visible and not consistently distinct as a roadside element.\",\"Some frames show abrupt environmental edge geometry where the tree line ends, creating mild artificiality.\"]}}", + "provider": "openai", + "response_id": "resp_05b35a36739620a7006acf2b18720c87d09af2260c97396f27", + "usage": { + "input_tokens": 22512, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1176, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23688 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "(no object rubrics to evaluate)" + }, + "item_scores": [], + "score": null + }, + "overall_score": 0.8667, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 5 + }, + "scene_name": "RacingCar_first" + }, + "obj_score": null, + "overall_score": 0.8667, + "pass": 3 + }, + { + "env_score": 0.9333, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Green grass is not clearly visible in most frames; low brownish vegetation appears instead.", + "Both-side symmetry is harder to verify in several middle frames because the camera pans to one side.", + "Some mid-clip views simplify the environment composition, reducing visibility of full roadside context." + ], + "summary": "The video matches the prompt’s overall highway environment well: a wide straight road, clear blue sky, bright daytime lighting, dark barriers, tall tree rows, and the suspended abrupt road-start are all strongly present. The main weakness is that green grass is not clearly visible and bilateral tree/barrier symmetry is less consistently verifiable during side-panned frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The highway is clearly very wide and straight in the opening and closing views: frame_t=0.0s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s all show a broad multi-lane roadway extending straight toward the horizon. During the middle section, the camera pans toward the side, so less of the full width is visible, but the visible road surface and lane markings still remain straight rather than curved, as seen in frame_t=1.1s, frame_t=1.7s, frame_t=7.2s, and frame_t=7.8s. Around the abrupt-start segment, frame_t=3.9s and frame_t=4.4s still show the road surface as straight, though the full width is less legible due to perspective. Overall, the environment consistently supports a very wide, straight highway.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=7.2s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "Across all sampled frames, the sky remains a uniform light-to-medium blue with no clouds, storminess, or major color shift. This is evident in the centered highway views at frame_t=0.0s and frame_t=8.9s, the side-looking views at frame_t=2.8s and frame_t=7.2s, and the suspended-road/start-point views at frame_t=3.9s and frame_t=4.4s. There is no visible deviation into gray, orange, or dark tones. The clear blue sky is stable throughout.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=6.1s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "The prompt calls for both sides to show dark barriers, green grass, and long symmetrical rows of tall trees. In the balanced wide views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, both sides do show dark roadside barriers and long, symmetrical rows of tall green trees. However, the green grass is not clearly visible in most frames; instead, there are mostly barriers with some low brownish vegetation at the tree bases. Also, in many middle frames only one side is visible because of the camera pan, such as frame_t=1.7s, frame_t=2.2s, frame_t=6.1s, and frame_t=7.2s, so the full bilateral symmetry is not consistently verifiable across all frames. The tree rows and barriers are strong matches, but the grass component is weak/unclear and both-side visibility is inconsistent in a notable portion.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=5.6s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies that the road begins abruptly at a starting point, with no ground behind it and only open sky, as if suspended in space. This unusual environmental feature is clearly present in the middle sequence: frame_t=3.9s and especially frame_t=4.4s show the roadway ending abruptly with open sky beyond the edge, and no terrain behind it. Frame_t=5.0s and frame_t=5.6s continue to show this suspended-start effect from offset angles. Earlier and later frames depict the normal forward roadway and side surroundings, which is compatible with moving around the start area rather than contradicting it. The starting-point environment is therefore well represented and consistent where relevant.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "Lighting remains bright and clearly daytime throughout the clip. The road, barriers, and trees are all evenly lit with no nighttime, dusk, or dim transitions, as seen in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. The environment also maintains a clean, minimal aesthetic: simple highway, barriers, trees, and clear sky with little clutter. There are no major environmental intrusions. The only slight caveat is some visual simplification/artificiality in the side/start-point views, but it does not materially undermine the bright, minimal daytime look.", + "rubric_id": "env_05" + } + ], + "score": 0.9333 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f" + }, + { + "label": "frame_t=0.0s", + "sha256": "d47ace44980ed2301e0bdba813617fd4f8c734e233cf9f8c6418e604a6a48290" + }, + { + "label": "frame_t=0.6s", + "sha256": "6f045138b6e7fd617eacea49743d8e58a7acf96ae29f1a077ba36331eb6ab623" + }, + { + "label": "frame_t=1.1s", + "sha256": "927201c13d02bd37962d617a59c8128e87f3f2347bfda0c2998ea5163d682840" + }, + { + "label": "frame_t=1.7s", + "sha256": "5f921f012e6dd548baf4f5aea54cf60e3912609d03ebbe4d38dd1580eefdb97b" + }, + { + "label": "frame_t=2.2s", + "sha256": "7e54bb28614ad256d33996b4316ce37131f0fb29b34c8ba45dfc793e06f4dc4c" + }, + { + "label": "frame_t=2.8s", + "sha256": "350244b241c2fcb42118b7360aa80c2e54508805335e0a5a8be35085e5398820" + }, + { + "label": "frame_t=3.3s", + "sha256": "c275d4422524c646aad93670ab63e23076576ed0ec906470353d41cb08cbaf43" + }, + { + "label": "frame_t=3.9s", + "sha256": "1b6433e6089837c604a58fceb9d700398cdee2e3c015988b6da494d59c81d019" + }, + { + "label": "frame_t=4.4s", + "sha256": "6ffa612eee55482a4ff3c2c637f77b9a5bee443d347042b27c446542651b46aa" + }, + { + "label": "frame_t=5.0s", + "sha256": "1341cb2da73ba88bc004594d05f47de9de90f1f1379b5b98a812cb6fb24090df" + }, + { + "label": "frame_t=5.6s", + "sha256": "b93356c5a57afe65207cb72cb67b083f57318d8523319e60e19fcf3f38e9b595" + }, + { + "label": "frame_t=6.1s", + "sha256": "68f93a161c3aa6e574913bfed0b7ec403015b6c8ce0a1bbc93309cff5df660ce" + }, + { + "label": "frame_t=6.7s", + "sha256": "a3ab1dbf1cd293c9f0f2d6db5588fb9859cec3a3816ad34071cd8658ba1f3fa0" + }, + { + "label": "frame_t=7.2s", + "sha256": "15934cfb9cda87760b7469d5d83e520aeae30ea48d36f5177bbbe4d8b880bce3" + }, + { + "label": "frame_t=7.8s", + "sha256": "0feea8aee060858bab2a8809e37f440eebd655c6e7fbd18ed24e78d80c897e4d" + }, + { + "label": "frame_t=8.3s", + "sha256": "dbde9ced874c027d1e53fd2e9977714076412601d9c01faacaef27a0309db73a" + }, + { + "label": "frame_t=8.9s", + "sha256": "c02f06f0bfe36999e8c03b7227ac2ad7befc73cf6233ad443515c503743edc16" + }, + { + "label": "frame_t=9.4s", + "sha256": "32331d3e7e63347b98fe0cb0edbf6e7c73cc42626ebcb80859d58c5413579213" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway across all frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?\n\n### env_04\nRubric: Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?\n\n### env_05\nRubric: Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961881, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The highway is clearly very wide and straight in the opening and closing views: frame_t=0.0s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s all show a broad multi-lane roadway extending straight toward the horizon. During the middle section, the camera pans toward the side, so less of the full width is visible, but the visible road surface and lane markings still remain straight rather than curved, as seen in frame_t=1.1s, frame_t=1.7s, frame_t=7.2s, and frame_t=7.8s. Around the abrupt-start segment, frame_t=3.9s and frame_t=4.4s still show the road surface as straight, though the full width is less legible due to perspective. Overall, the environment consistently supports a very wide, straight highway.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"Across all sampled frames, the sky remains a uniform light-to-medium blue with no clouds, storminess, or major color shift. This is evident in the centered highway views at frame_t=0.0s and frame_t=8.9s, the side-looking views at frame_t=2.8s and frame_t=7.2s, and the suspended-road/start-point views at frame_t=3.9s and frame_t=4.4s. There is no visible deviation into gray, orange, or dark tones. The clear blue sky is stable throughout.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=7.2s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt calls for both sides to show dark barriers, green grass, and long symmetrical rows of tall trees. In the balanced wide views at frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, both sides do show dark roadside barriers and long, symmetrical rows of tall green trees. However, the green grass is not clearly visible in most frames; instead, there are mostly barriers with some low brownish vegetation at the tree bases. Also, in many middle frames only one side is visible because of the camera pan, such as frame_t=1.7s, frame_t=2.2s, frame_t=6.1s, and frame_t=7.2s, so the full bilateral symmetry is not consistently verifiable across all frames. The tree rows and barriers are strong matches, but the grass component is weak/unclear and both-side visibility is inconsistent in a notable portion.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=6.1s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":2},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt specifies that the road begins abruptly at a starting point, with no ground behind it and only open sky, as if suspended in space. This unusual environmental feature is clearly present in the middle sequence: frame_t=3.9s and especially frame_t=4.4s show the roadway ending abruptly with open sky beyond the edge, and no terrain behind it. Frame_t=5.0s and frame_t=5.6s continue to show this suspended-start effect from offset angles. Earlier and later frames depict the normal forward roadway and side surroundings, which is compatible with moving around the start area rather than contradicting it. The starting-point environment is therefore well represented and consistent where relevant.\",\"frame_evidence\":[\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=5.6s\"],\"judged_score\":3},{\"rubric_id\":\"env_05\",\"reasoning\":\"Lighting remains bright and clearly daytime throughout the clip. The road, barriers, and trees are all evenly lit with no nighttime, dusk, or dim transitions, as seen in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. The environment also maintains a clean, minimal aesthetic: simple highway, barriers, trees, and clear sky with little clutter. There are no major environmental intrusions. The only slight caveat is some visual simplification/artificiality in the side/start-point views, but it does not materially undermine the bright, minimal daytime look.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=9.4s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt’s overall highway environment well: a wide straight road, clear blue sky, bright daytime lighting, dark barriers, tall tree rows, and the suspended abrupt road-start are all strongly present. The main weakness is that green grass is not clearly visible and bilateral tree/barrier symmetry is less consistently verifiable during side-panned frames.\",\"issues\":[\"Green grass is not clearly visible in most frames; low brownish vegetation appears instead.\",\"Both-side symmetry is harder to verify in several middle frames because the camera pans to one side.\",\"Some mid-clip views simplify the environment composition, reducing visibility of full roadside context.\"]}}", + "provider": "openai", + "response_id": "resp_00e8002f20cab8fa006acf2b195dcc87d09f4892ac98bd255a", + "usage": { + "input_tokens": 22512, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1255, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23767 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "(no object rubrics to evaluate)" + }, + "item_scores": [], + "score": null + }, + "overall_score": 0.9333, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 5 + }, + "scene_name": "RacingCar_first" + }, + "obj_score": null, + "overall_score": 0.9333, + "pass": 4 + }, + { + "env_score": 0.6667, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Roadside trees and barriers lose symmetry in several middle frames due to abrupt cropped edges and missing continuation on one side.", + "Green grass is not clearly and consistently visible across the frames.", + "The abrupt suspended-road starting-point effect appears only intermittently rather than remaining consistently established.", + "Mid-clip environmental geometry shows hard boundaries/cutoffs that reduce scene cleanliness and continuity." + ], + "summary": "The video matches the prompt well on highway width/straightness, clear blue sky, and bright daytime lighting, but it is less consistent on the roadside symmetry and the suspended starting-point concept due to visible mid-clip environmental cutoffs and incomplete bilateral tree/barrier continuity." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The video consistently depicts a broad paved roadway with multiple lanes and a straight alignment. In frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, the highway is clearly very wide and extends straight toward the horizon. During the lateral camera pan in frame_t=1.1s through frame_t=7.2s, only part of the roadway is visible at times, but the visible lane markings and barrier alignment still indicate a straight highway rather than a curved or narrow road. There is no meaningful evidence of the road bending or changing type across frames.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The sky remains a uniform light-to-medium clear blue throughout the sampled frames. In frame_t=0.0s, frame_t=4.4s, frame_t=5.0s, and frame_t=8.9s, the sky is cloudless and bright with no darkening, storminess, or color shift. Even when the camera shows mostly sky around frame_t=3.9s to frame_t=5.6s, the sky stays consistent in tone and clarity. I do not observe clouds or other atmospheric changes.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=2.8s", + "frame_t=5.0s", + "frame_t=6.7s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The intended roadside environment is present only part of the time. Early and late frames such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s show dark barriers on both sides and long rows of tall trees that read as broadly symmetrical. However, in the middle section, the camera reveals an abrupt cutoff where one side or both sides lose the expected mirrored tree rows; for example frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=5.0s, and frame_t=6.7s show a vertical edge/cropped boundary and large open sky area where continued roadside structure should be. Green grass is also not clearly visible across all frames, only sparse vegetation near tree bases. Because the barriers and tree rows are not consistently maintained on both sides across the whole clip, alignment is only partial.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt specifies a starting-point environment where the road begins abruptly with only open sky behind it, as if suspended in space. This effect is visible most strongly in the middle frames: frame_t=3.9s and frame_t=4.4s show the roadway ending at a horizon-like edge with open sky beyond, and frame_t=5.0s also preserves that suspended-space look. However, this is not consistent as the defining environmental state across all relevant frames because the video begins and ends with a normal extended highway scene in frame_t=0.0s and frame_t=8.9s, where the road stretches conventionally into the distance rather than reading as an abrupt starting point. The abrupt-start concept appears intermittently rather than being stably realized.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=7.8s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "Across the sampled frames, lighting remains bright and daytime-like, with strong visibility and no nighttime or dim conditions. Frame_t=0.0s, frame_t=4.4s, frame_t=7.8s, and frame_t=8.9s all show a bright blue sky and evenly lit road and trees. The scene also maintains a sparse, uncluttered composition with minimal extraneous background elements. There are some noticeable environmental artifacts in the middle frames, including hard cutoffs in the roadside/tree geometry, which slightly detract from the 'clean' appearance, but the overall palette and lighting stay consistent and minimal.", + "rubric_id": "env_05" + } + ], + "score": 0.6667 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f" + }, + { + "label": "frame_t=0.0s", + "sha256": "d47ace44980ed2301e0bdba813617fd4f8c734e233cf9f8c6418e604a6a48290" + }, + { + "label": "frame_t=0.6s", + "sha256": "6f045138b6e7fd617eacea49743d8e58a7acf96ae29f1a077ba36331eb6ab623" + }, + { + "label": "frame_t=1.1s", + "sha256": "927201c13d02bd37962d617a59c8128e87f3f2347bfda0c2998ea5163d682840" + }, + { + "label": "frame_t=1.7s", + "sha256": "5f921f012e6dd548baf4f5aea54cf60e3912609d03ebbe4d38dd1580eefdb97b" + }, + { + "label": "frame_t=2.2s", + "sha256": "7e54bb28614ad256d33996b4316ce37131f0fb29b34c8ba45dfc793e06f4dc4c" + }, + { + "label": "frame_t=2.8s", + "sha256": "350244b241c2fcb42118b7360aa80c2e54508805335e0a5a8be35085e5398820" + }, + { + "label": "frame_t=3.3s", + "sha256": "c275d4422524c646aad93670ab63e23076576ed0ec906470353d41cb08cbaf43" + }, + { + "label": "frame_t=3.9s", + "sha256": "1b6433e6089837c604a58fceb9d700398cdee2e3c015988b6da494d59c81d019" + }, + { + "label": "frame_t=4.4s", + "sha256": "6ffa612eee55482a4ff3c2c637f77b9a5bee443d347042b27c446542651b46aa" + }, + { + "label": "frame_t=5.0s", + "sha256": "1341cb2da73ba88bc004594d05f47de9de90f1f1379b5b98a812cb6fb24090df" + }, + { + "label": "frame_t=5.6s", + "sha256": "b93356c5a57afe65207cb72cb67b083f57318d8523319e60e19fcf3f38e9b595" + }, + { + "label": "frame_t=6.1s", + "sha256": "68f93a161c3aa6e574913bfed0b7ec403015b6c8ce0a1bbc93309cff5df660ce" + }, + { + "label": "frame_t=6.7s", + "sha256": "a3ab1dbf1cd293c9f0f2d6db5588fb9859cec3a3816ad34071cd8658ba1f3fa0" + }, + { + "label": "frame_t=7.2s", + "sha256": "15934cfb9cda87760b7469d5d83e520aeae30ea48d36f5177bbbe4d8b880bce3" + }, + { + "label": "frame_t=7.8s", + "sha256": "0feea8aee060858bab2a8809e37f440eebd655c6e7fbd18ed24e78d80c897e4d" + }, + { + "label": "frame_t=8.3s", + "sha256": "dbde9ced874c027d1e53fd2e9977714076412601d9c01faacaef27a0309db73a" + }, + { + "label": "frame_t=8.9s", + "sha256": "c02f06f0bfe36999e8c03b7227ac2ad7befc73cf6233ad443515c503743edc16" + }, + { + "label": "frame_t=9.4s", + "sha256": "32331d3e7e63347b98fe0cb0edbf6e7c73cc42626ebcb80859d58c5413579213" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway across all frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?\n\n### env_04\nRubric: Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?\n\n### env_05\nRubric: Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961880, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The video consistently depicts a broad paved roadway with multiple lanes and a straight alignment. In frame_t=0.0s, frame_t=8.3s, and frame_t=8.9s, the highway is clearly very wide and extends straight toward the horizon. During the lateral camera pan in frame_t=1.1s through frame_t=7.2s, only part of the roadway is visible at times, but the visible lane markings and barrier alignment still indicate a straight highway rather than a curved or narrow road. There is no meaningful evidence of the road bending or changing type across frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The sky remains a uniform light-to-medium clear blue throughout the sampled frames. In frame_t=0.0s, frame_t=4.4s, frame_t=5.0s, and frame_t=8.9s, the sky is cloudless and bright with no darkening, storminess, or color shift. Even when the camera shows mostly sky around frame_t=3.9s to frame_t=5.6s, the sky stays consistent in tone and clarity. I do not observe clouds or other atmospheric changes.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The intended roadside environment is present only part of the time. Early and late frames such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s show dark barriers on both sides and long rows of tall trees that read as broadly symmetrical. However, in the middle section, the camera reveals an abrupt cutoff where one side or both sides lose the expected mirrored tree rows; for example frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=5.0s, and frame_t=6.7s show a vertical edge/cropped boundary and large open sky area where continued roadside structure should be. Green grass is also not clearly visible across all frames, only sparse vegetation near tree bases. Because the barriers and tree rows are not consistently maintained on both sides across the whole clip, alignment is only partial.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=2.8s\",\"frame_t=5.0s\",\"frame_t=6.7s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt specifies a starting-point environment where the road begins abruptly with only open sky behind it, as if suspended in space. This effect is visible most strongly in the middle frames: frame_t=3.9s and frame_t=4.4s show the roadway ending at a horizon-like edge with open sky beyond, and frame_t=5.0s also preserves that suspended-space look. However, this is not consistent as the defining environmental state across all relevant frames because the video begins and ends with a normal extended highway scene in frame_t=0.0s and frame_t=8.9s, where the road stretches conventionally into the distance rather than reading as an abrupt starting point. The abrupt-start concept appears intermittently rather than being stably realized.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_05\",\"reasoning\":\"Across the sampled frames, lighting remains bright and daytime-like, with strong visibility and no nighttime or dim conditions. Frame_t=0.0s, frame_t=4.4s, frame_t=7.8s, and frame_t=8.9s all show a bright blue sky and evenly lit road and trees. The scene also maintains a sparse, uncluttered composition with minimal extraneous background elements. There are some noticeable environmental artifacts in the middle frames, including hard cutoffs in the roadside/tree geometry, which slightly detract from the 'clean' appearance, but the overall palette and lighting stay consistent and minimal.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=7.8s\",\"frame_t=8.9s\"],\"judged_score\":2}],\"explanations\":{\"summary\":\"The video matches the prompt well on highway width/straightness, clear blue sky, and bright daytime lighting, but it is less consistent on the roadside symmetry and the suspended starting-point concept due to visible mid-clip environmental cutoffs and incomplete bilateral tree/barrier continuity.\",\"issues\":[\"Roadside trees and barriers lose symmetry in several middle frames due to abrupt cropped edges and missing continuation on one side.\",\"Green grass is not clearly and consistently visible across the frames.\",\"The abrupt suspended-road starting-point effect appears only intermittently rather than remaining consistently established.\",\"Mid-clip environmental geometry shows hard boundaries/cutoffs that reduce scene cleanliness and continuity.\"]}}", + "provider": "openai", + "response_id": "resp_07ccf0009837cba8006acf2b18790887d08c3c5036a519caa3", + "usage": { + "input_tokens": 22512, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1181, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23693 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "(no object rubrics to evaluate)" + }, + "item_scores": [], + "score": null + }, + "overall_score": 0.6667, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 5 + }, + "scene_name": "RacingCar_first" + }, + "obj_score": null, + "overall_score": 0.6667, + "pass": 5 + } + ], + "reference_video": "reference/unity_groundtruth.mp4", + "reference_video_sha256": "c7c1d40f9fe0bc6df9aa537ec9ad52194e69c232ce3a1ed841719250b23eccd0", + "schema_version": 1, + "summary": { + "env_score": { + "max": 0.9333, + "mean": 0.84, + "min": 0.6667, + "n": 5, + "std": 0.1115 + }, + "obj_score": { + "max": null, + "mean": null, + "min": null, + "n": 0, + "std": null + }, + "overall_score": { + "max": 0.9333, + "mean": 0.84, + "min": 0.6667, + "n": 5, + "std": 0.1115 + } + } +} diff --git a/cases/RacingCar/prompt_first/reference/artifacts/rubrics/RacingCar_first/openai_gpt-5-4_v0.json b/cases/RacingCar/prompt_first/reference/artifacts/rubrics/RacingCar_first/openai_gpt-5-4_v0.json new file mode 100644 index 0000000000000000000000000000000000000000..efc394c76ddecc25619c02ca8d2d79e83b00ceeb --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/artifacts/rubrics/RacingCar_first/openai_gpt-5-4_v0.json @@ -0,0 +1,42 @@ +{ + "scene_name": "RacingCar_first", + "prompt_text": "A very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long symmetrical rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. Bright daytime lighting, clean and minimal environment. First person view.", + "rubric_items": [ + { + "rubric_id": "env_01", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the environment consistently show a very wide, straight highway across all frames?" + }, + { + "rubric_id": "env_02", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the sky stay clear blue across all frames without becoming cloudy, dark, or differently colored?" + }, + { + "rubric_id": "env_03", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Do both sides of the highway consistently show dark barriers, green grass, and long symmetrical rows of tall trees across all frames?" + }, + { + "rubric_id": "env_04", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Is the starting-point environment consistent with the road beginning abruptly and having only open sky behind it, as if suspended in space?" + }, + { + "rubric_id": "env_05", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the environment remain brightly lit in daytime with a clean, minimal look across all frames?" + } + ], + "metadata": { + "generator_provider": "openai", + "generator_model": "gpt-5.4", + "generated_at": "2026-05-06T10:08:24.358079+00:00", + "num_candidates_generated": 5 + } +} \ No newline at end of file diff --git a/cases/RacingCar/prompt_first/reference/artifacts/trajectory.yaml b/cases/RacingCar/prompt_first/reference/artifacts/trajectory.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c9c9f5c33ee71578ff0395782d976d495481804 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/artifacts/trajectory.yaml @@ -0,0 +1,20 @@ +schema_version: 1 +trajectory_id: prompt.camera.left_turn_v1 +description: Continuous left (counter-clockwise) camera turn of the prompt-scene consistency cases (hold ArrowLeft for 10 s); in place in first person, around the character in third person. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 10.0, values: {yaw_rate_deg_s: -40.0}} +paper_alignment: + status: reconstructed + matched: [ten_second_left_camera_turn, unity_reference_turn_rate] + missing: The paper specifies a 10 s camera turn but no rate; 40 deg/s is the turn measured in every case's Unity reference poses. + source: ../../../eval_sets/wmeval_lite_v1/cases/ChessBoard/prompt_first/reference/artifacts/poses.npy +adapters: + unity: {status: reference, channel: yaw_rate_deg_s} + project_genie: + status: nominal + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/RacingCar/prompt_first/reference/checksums.sha256 b/cases/RacingCar/prompt_first/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..06ca10ee12bb425df01577d76a4c8a0f4eac8111 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/checksums.sha256 @@ -0,0 +1,11 @@ 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reference/ref.png +c7c1d40f9fe0bc6df9aa537ec9ad52194e69c232ce3a1ed841719250b23eccd0 reference/unity_groundtruth.mp4 diff --git a/cases/RacingCar/prompt_first/reference/ref.png b/cases/RacingCar/prompt_first/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..1fd821e6e6032003c8916309cff0b8372d963191 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:ba2171756cb838714f6a2335622ba66e46b82909933e47dbadd5339b5353da6f +size 777323 diff --git a/cases/RacingCar/prompt_first/reference/unity_groundtruth.mp4 b/cases/RacingCar/prompt_first/reference/unity_groundtruth.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..2287f4ad9092198441fb23376a6174430efbae78 --- /dev/null +++ b/cases/RacingCar/prompt_first/reference/unity_groundtruth.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:c7c1d40f9fe0bc6df9aa537ec9ad52194e69c232ce3a1ed841719250b23eccd0 +size 3596114 diff --git a/cases/RacingCar/prompt_third/reference/artifacts/action.npy b/cases/RacingCar/prompt_third/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..8edcbefbf5086514471e6b40452681126dae48fe --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:402da2a8afaa4fbbe3bea7a22c3b7ab1bbe7a933d2682be371aef670b90ed7a7 +size 6128 diff --git a/cases/RacingCar/prompt_third/reference/artifacts/action.npz b/cases/RacingCar/prompt_third/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..bc095cf26cf8d0640e6606383b0ad8a0f0dbd8e4 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:35a052e6999a15f1138f0baf229eda4561574e0076b2349b3d01d653b417492e +size 1564 diff --git a/cases/RacingCar/prompt_third/reference/artifacts/actions.jsonl b/cases/RacingCar/prompt_third/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..c58c0675ee371f0deb1255a8a75dd5ed140e594e --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/actions.jsonl @@ -0,0 +1 @@ +{"keys": ["ArrowLeft"], "ms": 10000, "op": "hold", "target_yaw_deg": -400.0} diff --git a/cases/RacingCar/prompt_third/reference/artifacts/actions.txt b/cases/RacingCar/prompt_third/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..5f37c73fe1428efefc06b2cd4b8f7e735385fa24 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/actions.txt @@ -0,0 +1,4 @@ +[ + {"op": "setview", "key": "third", "note": "start in third-person"}, + {"op": "hold", "key": "ArrowLeft", "ms": 10000, "note": "rotate left for 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diff --git a/cases/RacingCar/prompt_third/reference/artifacts/reference_scores.json b/cases/RacingCar/prompt_third/reference/artifacts/reference_scores.json new file mode 100644 index 0000000000000000000000000000000000000000..f5501e70174cadcc6c73fe354aa68562e0996fe4 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/reference_scores.json @@ -0,0 +1,1882 @@ +{ + "case_id": "RacingCar/prompt_third", + "created_utc": "2026-10-14T07:12:36+00:00", + "dimension": "prompt_scene_consistency", + "judge": { + "alpha": 0.6, + "first_frame_sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea", + "model": "gpt-5.4", + "prompt_version": "v0", + "provider": "openai", + "rubric": "reference/artifacts/rubrics/RacingCar/openai_gpt-5-4_v0.json", + "rubric_sha256": "24406bb6a7fc85d9b6390009c6e445b8cc07f2d661381873983817bf271d305c", + "sample_duration_sec": 10.0, + "sample_frames": 18, + "system_prompt_sha256": { + "environment": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "object": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2" + } + }, + "judge_model_resolved": [ + "gpt-5.4-2026-03-05" + ], + "passes": [ + { + "env_score": 0.8, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "The abrupt starting edge with open sky behind it is only directly visible in the middle portion of the video, not across most frames.", + "Both roadside tree/barrier/grass sides are not equally visible in some middle frames near the road start edge, reducing consistency for the full bilateral roadside view." + ], + "summary": "The video matches the prompt well at the environment level: it shows a wide straight highway, clear blue sky, bright daytime lighting, and a sparse stylized roadside setting. The main weakness is that the suspended-road starting edge is only clearly shown in part of the clip rather than throughout all sampled frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The highway is clearly very wide and multi-lane in the opening and closing views, and it remains straight toward the horizon whenever the forward/backward direction is visible. This is evident in frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s, where the lane markings run parallel into the distance with no visible curvature. In the side-oriented frames, the visible road surface also remains broad and flat, with no sign of bends. The only limitation is that during some middle frames the camera angle emphasizes the start edge rather than the forward extension, but the road still appears wide and straight when visible.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "Across all sampled frames, the sky appears uniformly clear and blue with no clouds, weather effects, or color shifts. This is visible in the opening rear view, the middle side/front views near the road start, and the return to the rear view near the end. Frames such as frame_t=0.0s, frame_t=4.4s, frame_t=5.6s, and frame_t=8.9s all show the same clear blue sky condition.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "The prompt calls for both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. This is strongly matched in many frames: frame_t=0.0s and frame_t=8.9s clearly show both left and right sides with dark barriers, green strips, and long dense tree rows. In side views such as frame_t=1.7s and frame_t=7.8s, the near side still shows the same barrier-grass-tree combination consistently. However, during the middle section near the road start edge, both sides are not consistently visible together, and some frames show truncated tree walls or mostly open sky on one side because of the abrupt edge view. Since the attribute is well matched in most frames but not cleanly maintained across all sampled frames, this is slightly less than perfect.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=5.6s" + ], + "judged_score": 1, + "reasoning": "This attribute is present clearly in the middle sequence. Frames near the road start, including frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, and frame_t=5.6s, show the road ending abruptly with open sky beyond it and no ground behind the starting edge, matching the suspended-in-space description. However, this feature is not visible in most of the earlier and later frames because the camera is oriented down the highway rather than toward the start edge. Since the rubric asks for this across all sampled frames, the attribute is only directly verifiable in part of the video rather than consistently shown throughout.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=4.4s", + "frame_t=6.7s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The environment maintains bright daytime lighting throughout: the road, barriers, grass, and trees are evenly lit, and the sky remains bright. The scene also keeps a simple, uncluttered composition with only the highway, barriers, grass, trees, and sky visible, consistent with a clean minimal look. This is consistent from frame_t=0.0s through the middle frames around the road edge and back to the final rear views. No notable lighting instability, weather, or environmental clutter appears.", + "rubric_id": "env_05" + } + ], + "score": 0.8 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all sampled frames?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?\n\n### env_04\nRubric: Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?\n\n### env_05\nRubric: Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961936, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The highway is clearly very wide and multi-lane in the opening and closing views, and it remains straight toward the horizon whenever the forward/backward direction is visible. This is evident in frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s, where the lane markings run parallel into the distance with no visible curvature. In the side-oriented frames, the visible road surface also remains broad and flat, with no sign of bends. The only limitation is that during some middle frames the camera angle emphasizes the start edge rather than the forward extension, but the road still appears wide and straight when visible.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"Across all sampled frames, the sky appears uniformly clear and blue with no clouds, weather effects, or color shifts. This is visible in the opening rear view, the middle side/front views near the road start, and the return to the rear view near the end. Frames such as frame_t=0.0s, frame_t=4.4s, frame_t=5.6s, and frame_t=8.9s all show the same clear blue sky condition.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt calls for both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. This is strongly matched in many frames: frame_t=0.0s and frame_t=8.9s clearly show both left and right sides with dark barriers, green strips, and long dense tree rows. In side views such as frame_t=1.7s and frame_t=7.8s, the near side still shows the same barrier-grass-tree combination consistently. However, during the middle section near the road start edge, both sides are not consistently visible together, and some frames show truncated tree walls or mostly open sky on one side because of the abrupt edge view. Since the attribute is well matched in most frames but not cleanly maintained across all sampled frames, this is slightly less than perfect.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=8.9s\"],\"judged_score\":2},{\"rubric_id\":\"env_04\",\"reasoning\":\"This attribute is present clearly in the middle sequence. Frames near the road start, including frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, and frame_t=5.6s, show the road ending abruptly with open sky beyond it and no ground behind the starting edge, matching the suspended-in-space description. However, this feature is not visible in most of the earlier and later frames because the camera is oriented down the highway rather than toward the start edge. Since the rubric asks for this across all sampled frames, the attribute is only directly verifiable in part of the video rather than consistently shown throughout.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=5.6s\"],\"judged_score\":1},{\"rubric_id\":\"env_05\",\"reasoning\":\"The environment maintains bright daytime lighting throughout: the road, barriers, grass, and trees are evenly lit, and the sky remains bright. The scene also keeps a simple, uncluttered composition with only the highway, barriers, grass, trees, and sky visible, consistent with a clean minimal look. This is consistent from frame_t=0.0s through the middle frames around the road edge and back to the final rear views. No notable lighting instability, weather, or environmental clutter appears.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=4.4s\",\"frame_t=6.7s\",\"frame_t=9.4s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt well at the environment level: it shows a wide straight highway, clear blue sky, bright daytime lighting, and a sparse stylized roadside setting. The main weakness is that the suspended-road starting edge is only clearly shown in part of the clip rather than throughout all sampled frames.\",\"issues\":[\"The abrupt starting edge with open sky behind it is only directly visible in the middle portion of the video, not across most frames.\",\"Both roadside tree/barrier/grass sides are not equally visible in some middle frames near the road start edge, reducing consistency for the full bilateral roadside view.\"]}}", + "provider": "openai", + "response_id": "resp_0a6c67b6733432e3006acf2b50613c87d0bc3826023d89cb7c", + "usage": { + "input_tokens": 22551, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1091, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23642 + } + } + }, + { + "agent": "object", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Object Rubric Items\n\n### obj_01\nRubric: When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?\n\n### obj_02\nRubric: When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?\n\n### obj_03\nRubric: When the car is visible and judgeable, are there exactly two black racing stripes on it?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961935, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"obj_01\",\"reasoning\":\"The only salient object throughout the sampled frames is the main vehicle. In rear view at frame_t=0.0s and frame_t=8.9s, it has a low-slung coupe profile, wide stance, and sporty rear fascia. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=5.6s, and frame_t=7.2s, the vehicle remains a two-door, low-height performance-style coupe rather than a sedan, SUV, truck, or van. No frames show a conflicting vehicle type. Thus the vehicle is consistently readable as a sports car.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=5.6s\",\"frame_t=7.2s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"obj_02\",\"reasoning\":\"Across all visible frames, the car body is predominantly bright yellow. This is clear in the rear view at frame_t=0.0s, side views at frame_t=2.2s and frame_t=6.7s, and front/three-quarter views at frame_t=4.4s and frame_t=5.0s. Black areas are limited to racing stripes, windows, and small trim sections, so they do not outweigh the yellow body color. There is no visible color drift or replacement with another dominant body color.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=6.7s\"],\"judged_score\":3},{\"rubric_id\":\"obj_03\",\"reasoning\":\"The prompt specifies exactly two black racing stripes. In multiple clear views, two parallel black stripes are visible running along the hood/roof/trunk area: frame_t=0.0s shows two stripes on the roof/trunk from behind, frame_t=2.8s and frame_t=3.9s show two distinct hood stripes plus continuation over the roof, and frame_t=4.4s and frame_t=5.6s show the pair clearly from the front and front-left angles. The stripes remain consistently two in number rather than one, three, or a merged ambiguous band. No judgeable frame contradicts this.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.3s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The main object is highly consistent with the prompt: a yellow sports car that remains visibly sporty, predominantly yellow, and marked with two black racing stripes throughout the sampled frames.\",\"issues\":[]}}", + "provider": "openai", + "response_id": "resp_0dd7ae2834620caf006acf2b4f6d5087d0a69febeed1fbb52f", + "usage": { + "input_tokens": 22571, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 632, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23203 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "The main object is highly consistent with the prompt: a yellow sports car that remains visibly sporty, predominantly yellow, and marked with two black racing stripes throughout the sampled frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=5.6s", + "frame_t=7.2s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The only salient object throughout the sampled frames is the main vehicle. In rear view at frame_t=0.0s and frame_t=8.9s, it has a low-slung coupe profile, wide stance, and sporty rear fascia. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=5.6s, and frame_t=7.2s, the vehicle remains a two-door, low-height performance-style coupe rather than a sedan, SUV, truck, or van. No frames show a conflicting vehicle type. Thus the vehicle is consistently readable as a sports car.", + "rubric_id": "obj_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=6.7s" + ], + "judged_score": 3, + "reasoning": "Across all visible frames, the car body is predominantly bright yellow. This is clear in the rear view at frame_t=0.0s, side views at frame_t=2.2s and frame_t=6.7s, and front/three-quarter views at frame_t=4.4s and frame_t=5.0s. Black areas are limited to racing stripes, windows, and small trim sections, so they do not outweigh the yellow body color. There is no visible color drift or replacement with another dominant body color.", + "rubric_id": "obj_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.3s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies exactly two black racing stripes. In multiple clear views, two parallel black stripes are visible running along the hood/roof/trunk area: frame_t=0.0s shows two stripes on the roof/trunk from behind, frame_t=2.8s and frame_t=3.9s show two distinct hood stripes plus continuation over the roof, and frame_t=4.4s and frame_t=5.6s show the pair clearly from the front and front-left angles. The stripes remain consistently two in number rather than one, three, or a merged ambiguous band. No judgeable frame contradicts this.", + "rubric_id": "obj_03" + } + ], + "score": 1.0 + }, + "overall_score": 0.88, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 8 + }, + "scene_name": "RacingCar" + }, + "obj_score": 1.0, + "overall_score": 0.88, + "pass": 1 + }, + { + "env_score": 0.7333, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Both sides of the highway are not consistently visible with barriers, grass, and tall tree rows in the middle frames.", + "The abrupt road start with open sky behind is only clearly shown in part of the sequence, not across all sampled frames.", + "Some middle frames emphasize one side and open sky, reducing full bilateral environmental consistency." + ], + "summary": "The video matches the prompt well on the main environmental setup: a wide straight highway, clear blue sky, bright daytime lighting, and a sparse clean look. The main weaknesses are inconsistency in showing both tree-lined sides in all frames and only intermittent visibility of the abrupt suspended road start." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.1s", + "frame_t=7.8s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The prompt calls for a very wide, straight highway extending forward. In the early frames, the highway is clearly very wide with many lanes and strong linear perspective stretching into the distance, e.g. frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. In the later frames, the same highway remains straight and wide, with parallel lane markings and barriers continuing into the distance, e.g. frame_t=7.8s, frame_t=8.3s, and frame_t=8.9s. Even when the camera angle shifts to the side around frame_t=2.2s to frame_t=6.7s, the visible road surface still appears broad and straight rather than curved. The attribute is consistent across the sampled frames.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=8.3s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies a clear blue sky. Across the full sequence, the sky appears uniformly blue and cloudless, including the initial rear-view frames such as frame_t=0.0s and frame_t=0.6s, the middle side/front views such as frame_t=3.9s and frame_t=4.4s, and the return to rearward highway views in frame_t=8.3s and frame_t=9.4s. There are no visible clouds, weather effects, or color shifts that would contradict a clear blue sky. This attribute is consistent throughout.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt asks for both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. This is clearly present in the opening frames: frame_t=0.0s shows dark barriers on both sides, grass strips beyond them, and long symmetric rows of tall trees. Frame_t=0.6s and frame_t=1.1s continue this look. However, in the middle portion of the clip, the camera rotates near the road start and only one side is prominently visible while the opposite side opens into sky; for example frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, and frame_t=5.6s do not consistently show both sides with barriers, grass, and tree rows. Later, the full bilateral tree-lined highway reappears in frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s. Because the prompt specifically requires both sides across all sampled frames, this is only partially satisfied.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=6.1s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt describes the road beginning abruptly at a starting point with no ground behind it, only open sky, as if suspended in space. This is not visible in the initial frames, where the camera faces forward down the highway from behind the car and the road appears continuous into the distance rather than emphasizing the start edge, e.g. frame_t=0.0s through frame_t=1.7s. The abrupt road start becomes clearly visible in the middle sequence: frame_t=2.8s, frame_t=3.3s, frame_t=4.4s, frame_t=5.0s, and frame_t=6.1s show the road terminating at an edge with open sky beyond and no supporting ground behind it. Later frames rotate away and return to the forward highway view, so the suspended start is no longer visible, e.g. frame_t=8.3s and frame_t=8.9s. Since this environment trait is present in some frames but not consistently verifiable across all sampled frames, the match is partial.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The prompt calls for bright daytime lighting and a clean, minimal environment. Across the sequence, lighting is consistently bright and even, with no night conditions, dramatic shadows, or weather changes; this is visible in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, and frame_t=8.9s. The environment is also sparse and uncluttered: mostly road, barriers, grass, trees, and sky, with no extraneous environmental detail. The only notable issue is the somewhat game-like simplified rendering and the abrupt edge geometry near the road start, but these do not break the bright daytime, clean minimal environmental description. Overall this attribute is strongly maintained.", + "rubric_id": "env_05" + } + ], + "score": 0.7333 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all sampled frames?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?\n\n### env_04\nRubric: Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?\n\n### env_05\nRubric: Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961934, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The prompt calls for a very wide, straight highway extending forward. In the early frames, the highway is clearly very wide with many lanes and strong linear perspective stretching into the distance, e.g. frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. In the later frames, the same highway remains straight and wide, with parallel lane markings and barriers continuing into the distance, e.g. frame_t=7.8s, frame_t=8.3s, and frame_t=8.9s. Even when the camera angle shifts to the side around frame_t=2.2s to frame_t=6.7s, the visible road surface still appears broad and straight rather than curved. The attribute is consistent across the sampled frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.1s\",\"frame_t=7.8s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The prompt specifies a clear blue sky. Across the full sequence, the sky appears uniformly blue and cloudless, including the initial rear-view frames such as frame_t=0.0s and frame_t=0.6s, the middle side/front views such as frame_t=3.9s and frame_t=4.4s, and the return to rearward highway views in frame_t=8.3s and frame_t=9.4s. There are no visible clouds, weather effects, or color shifts that would contradict a clear blue sky. This attribute is consistent throughout.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=8.3s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt asks for both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. This is clearly present in the opening frames: frame_t=0.0s shows dark barriers on both sides, grass strips beyond them, and long symmetric rows of tall trees. Frame_t=0.6s and frame_t=1.1s continue this look. However, in the middle portion of the clip, the camera rotates near the road start and only one side is prominently visible while the opposite side opens into sky; for example frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, and frame_t=5.6s do not consistently show both sides with barriers, grass, and tree rows. Later, the full bilateral tree-lined highway reappears in frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s. Because the prompt specifically requires both sides across all sampled frames, this is only partially satisfied.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt describes the road beginning abruptly at a starting point with no ground behind it, only open sky, as if suspended in space. This is not visible in the initial frames, where the camera faces forward down the highway from behind the car and the road appears continuous into the distance rather than emphasizing the start edge, e.g. frame_t=0.0s through frame_t=1.7s. The abrupt road start becomes clearly visible in the middle sequence: frame_t=2.8s, frame_t=3.3s, frame_t=4.4s, frame_t=5.0s, and frame_t=6.1s show the road terminating at an edge with open sky beyond and no supporting ground behind it. Later frames rotate away and return to the forward highway view, so the suspended start is no longer visible, e.g. frame_t=8.3s and frame_t=8.9s. Since this environment trait is present in some frames but not consistently verifiable across all sampled frames, the match is partial.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=6.1s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_05\",\"reasoning\":\"The prompt calls for bright daytime lighting and a clean, minimal environment. Across the sequence, lighting is consistently bright and even, with no night conditions, dramatic shadows, or weather changes; this is visible in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, and frame_t=8.9s. The environment is also sparse and uncluttered: mostly road, barriers, grass, trees, and sky, with no extraneous environmental detail. The only notable issue is the somewhat game-like simplified rendering and the abrupt edge geometry near the road start, but these do not break the bright daytime, clean minimal environmental description. Overall this attribute is strongly maintained.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt well on the main environmental setup: a wide straight highway, clear blue sky, bright daytime lighting, and a sparse clean look. The main weaknesses are inconsistency in showing both tree-lined sides in all frames and only intermittent visibility of the abrupt suspended road start.\",\"issues\":[\"Both sides of the highway are not consistently visible with barriers, grass, and tall tree rows in the middle frames.\",\"The abrupt road start with open sky behind is only clearly shown in part of the sequence, not across all sampled frames.\",\"Some middle frames emphasize one side and open sky, reducing full bilateral environmental consistency.\"]}}", + "provider": "openai", + "response_id": "resp_07ca4ce0a7f87045006acf2b4eb86487d09ce30a1a888cd8d8", + "usage": { + "input_tokens": 22551, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1348, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23899 + } + } + }, + { + "agent": "object", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Object Rubric Items\n\n### obj_01\nRubric: When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?\n\n### obj_02\nRubric: When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?\n\n### obj_03\nRubric: When the car is visible and judgeable, are there exactly two black racing stripes on it?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961936, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"obj_01\",\"reasoning\":\"The main vehicle is visible and judgeable in all sampled frames. In rear views at frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, it has a low, compact coupe profile with sporty proportions, wide stance, and performance-style rear fascia. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.8s, it consistently appears as a two-door, low-slung sports coupe rather than a sedan, SUV, truck, or other vehicle type. No frames suggest a conflicting vehicle identity.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=6.7s\",\"frame_t=7.8s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"obj_02\",\"reasoning\":\"The car is clearly visible throughout the clip. Across rear, side, and front three-quarter views, the body color remains predominantly bright yellow. This is evident in frame_t=0.0s and frame_t=0.6s from the rear, frame_t=2.2s and frame_t=6.1s from the side, and frame_t=4.4s and frame_t=5.0s from the front. Black accents and windows do not dominate the body; yellow is consistently the main body color in all judgeable frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=6.1s\"],\"judged_score\":3},{\"rubric_id\":\"obj_03\",\"reasoning\":\"The prompt specifies exactly two black racing stripes. In most judgeable views, the car shows two parallel black stripes running along the hood/roof/trunk area. This is clearly visible in frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=4.4s, frame_t=5.6s, and frame_t=8.3s. However, there is a recurring extra small black stripe/block visible on the rear deck/trunk center area in rear-facing views, such as frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, making the stripe pattern appear not strictly limited to exactly two stripes over the whole car. Because the main two stripes are present but the design includes an additional black marking that conflicts with 'exactly two,' this is a non-trivial attribute mismatch.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":1}],\"explanations\":{\"summary\":\"The video shows a consistent yellow sports car that matches the prompt well in vehicle type and body color. The main object-level issue is the stripe pattern, which includes extra black marking beyond the specified two racing stripes.\",\"issues\":[\"The car's stripe design is not strictly limited to exactly two black racing stripes; an additional black rear/trunk marking is visible in multiple frames.\"]}}", + "provider": "openai", + "response_id": "resp_0309dc1e92172521006acf2b507a3887d0854421e3ec6f421f", + "usage": { + "input_tokens": 22571, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 768, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23339 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [ + "The car's stripe design is not strictly limited to exactly two black racing stripes; an additional black rear/trunk marking is visible in multiple frames." + ], + "summary": "The video shows a consistent yellow sports car that matches the prompt well in vehicle type and body color. The main object-level issue is the stripe pattern, which includes extra black marking beyond the specified two racing stripes." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=6.7s", + "frame_t=7.8s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The main vehicle is visible and judgeable in all sampled frames. In rear views at frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, it has a low, compact coupe profile with sporty proportions, wide stance, and performance-style rear fascia. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.8s, it consistently appears as a two-door, low-slung sports coupe rather than a sedan, SUV, truck, or other vehicle type. No frames suggest a conflicting vehicle identity.", + "rubric_id": "obj_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=6.1s" + ], + "judged_score": 3, + "reasoning": "The car is clearly visible throughout the clip. Across rear, side, and front three-quarter views, the body color remains predominantly bright yellow. This is evident in frame_t=0.0s and frame_t=0.6s from the rear, frame_t=2.2s and frame_t=6.1s from the side, and frame_t=4.4s and frame_t=5.0s from the front. Black accents and windows do not dominate the body; yellow is consistently the main body color in all judgeable frames.", + "rubric_id": "obj_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 1, + "reasoning": "The prompt specifies exactly two black racing stripes. In most judgeable views, the car shows two parallel black stripes running along the hood/roof/trunk area. This is clearly visible in frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=4.4s, frame_t=5.6s, and frame_t=8.3s. However, there is a recurring extra small black stripe/block visible on the rear deck/trunk center area in rear-facing views, such as frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, making the stripe pattern appear not strictly limited to exactly two stripes over the whole car. Because the main two stripes are present but the design includes an additional black marking that conflicts with 'exactly two,' this is a non-trivial attribute mismatch.", + "rubric_id": "obj_03" + } + ], + "score": 0.7778 + }, + "overall_score": 0.7511, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 8 + }, + "scene_name": "RacingCar" + }, + "obj_score": 0.7778, + "overall_score": 0.7511, + "pass": 2 + }, + { + "env_score": 0.8, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Both sides of the roadside barriers/grass/tree rows are not visible in every frame due to camera angle.", + "The abrupt suspended road-start edge is only directly visible in the middle portion of the clip, not across all frames.", + "The suspended edge looks somewhat artificial/game-like in some frames, slightly reducing the clean minimal realism." + ], + "summary": "The video matches the prompt’s highway environment well overall: wide straight road, clear blue sky, bright daytime lighting, and the tree-lined barrier setup are mostly consistent. The main weaknesses are partial visibility of both roadside details in some angles and the fact that the suspended road-start feature is only verifiable in the middle frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.1s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The prompt asks for a very wide, straight highway extending forward. In the early and late frames, the road is clearly very wide with multiple lanes and a long straight perspective vanishing into the distance, matching the prompt well (frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). In the middle segment, the camera rotates around the car and the vanishing-point view is partially lost, but the visible lane markings and road geometry still indicate a straight, wide highway rather than a curved or narrow road (frame_t=1.1s through frame_t=7.8s). There is no strong contradiction to straightness; the main limitation is that some frames show only a partial side view of the road, making the long forward extension less directly visible.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The sky is consistently a clear light blue in every sampled frame. There are no clouds, haze, sunset colors, or weather changes visible from beginning to end. This remains true both in the standard rear view and during the middle section where the road edge and open sky are prominent (frame_t=0.0s, frame_t=3.9s, frame_t=4.4s, frame_t=5.6s, frame_t=8.9s).", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=3.3s", + "frame_t=4.4s", + "frame_t=6.7s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "The prompt specifies both sides should show dark roadside barriers, green grass, and long rows of tall trees. This is clearly true in many frames, especially at the start and end where both sides are visible symmetrically (frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). However, in the middle frames, one side or the far side is often out of view due to camera angle, and the road-start edge with open sky reduces visibility of full bilateral roadside detail (frame_t=3.3s through frame_t=6.7s). There is no obvious replacement of these elements with something incorrect, but both sides are not consistently verifiable across all frames.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=5.6s", + "frame_t=6.1s" + ], + "judged_score": 2, + "reasoning": "This attribute is strongly supported in the middle portion of the video. Multiple frames clearly show the road beginning abruptly with no ground behind it, only open sky beyond the starting edge, creating the suspended-in-space effect described in the prompt (frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s). In earlier and later frames, the camera looks down the highway so the start edge is not visible, meaning the attribute cannot be verified there (frame_t=0.0s, frame_t=0.6s, frame_t=8.9s, frame_t=9.4s). Since the feature is clearly correct when visible but not consistently visible across all sampled frames, a slightly reduced score is appropriate.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=7.8s", + "frame_t=9.4s" + ], + "judged_score": 2, + "reasoning": "The scene maintains bright daytime lighting throughout: the sky is bright, the road and trees are evenly lit, and there is no night/dusk shift or dramatic shadow inconsistency (frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, frame_t=7.8s, frame_t=9.4s). The overall style is clean and minimal, with a sparse environment consisting mainly of highway, barriers, grass, trees, and sky. However, the middle section exposes some environment artificiality at the road start/edge, where the suspended-space boundary looks somewhat abrupt and game-like rather than fully naturalistic (frame_t=3.3s through frame_t=6.1s). This is a minor style issue, not a lighting failure.", + "rubric_id": "env_05" + } + ], + "score": 0.8 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all sampled frames?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?\n\n### env_04\nRubric: Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?\n\n### env_05\nRubric: Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961936, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The prompt asks for a very wide, straight highway extending forward. In the early and late frames, the road is clearly very wide with multiple lanes and a long straight perspective vanishing into the distance, matching the prompt well (frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). In the middle segment, the camera rotates around the car and the vanishing-point view is partially lost, but the visible lane markings and road geometry still indicate a straight, wide highway rather than a curved or narrow road (frame_t=1.1s through frame_t=7.8s). There is no strong contradiction to straightness; the main limitation is that some frames show only a partial side view of the road, making the long forward extension less directly visible.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.1s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The sky is consistently a clear light blue in every sampled frame. There are no clouds, haze, sunset colors, or weather changes visible from beginning to end. This remains true both in the standard rear view and during the middle section where the road edge and open sky are prominent (frame_t=0.0s, frame_t=3.9s, frame_t=4.4s, frame_t=5.6s, frame_t=8.9s).\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt specifies both sides should show dark roadside barriers, green grass, and long rows of tall trees. This is clearly true in many frames, especially at the start and end where both sides are visible symmetrically (frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s). However, in the middle frames, one side or the far side is often out of view due to camera angle, and the road-start edge with open sky reduces visibility of full bilateral roadside detail (frame_t=3.3s through frame_t=6.7s). There is no obvious replacement of these elements with something incorrect, but both sides are not consistently verifiable across all frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=3.3s\",\"frame_t=4.4s\",\"frame_t=6.7s\",\"frame_t=8.9s\"],\"judged_score\":2},{\"rubric_id\":\"env_04\",\"reasoning\":\"This attribute is strongly supported in the middle portion of the video. Multiple frames clearly show the road beginning abruptly with no ground behind it, only open sky beyond the starting edge, creating the suspended-in-space effect described in the prompt (frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s). In earlier and later frames, the camera looks down the highway so the start edge is not visible, meaning the attribute cannot be verified there (frame_t=0.0s, frame_t=0.6s, frame_t=8.9s, frame_t=9.4s). Since the feature is clearly correct when visible but not consistently visible across all sampled frames, a slightly reduced score is appropriate.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=5.6s\",\"frame_t=6.1s\"],\"judged_score\":2},{\"rubric_id\":\"env_05\",\"reasoning\":\"The scene maintains bright daytime lighting throughout: the sky is bright, the road and trees are evenly lit, and there is no night/dusk shift or dramatic shadow inconsistency (frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, frame_t=7.8s, frame_t=9.4s). The overall style is clean and minimal, with a sparse environment consisting mainly of highway, barriers, grass, trees, and sky. However, the middle section exposes some environment artificiality at the road start/edge, where the suspended-space boundary looks somewhat abrupt and game-like rather than fully naturalistic (frame_t=3.3s through frame_t=6.1s). This is a minor style issue, not a lighting failure.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=7.8s\",\"frame_t=9.4s\"],\"judged_score\":2}],\"explanations\":{\"summary\":\"The video matches the prompt’s highway environment well overall: wide straight road, clear blue sky, bright daytime lighting, and the tree-lined barrier setup are mostly consistent. The main weaknesses are partial visibility of both roadside details in some angles and the fact that the suspended road-start feature is only verifiable in the middle frames.\",\"issues\":[\"Both sides of the roadside barriers/grass/tree rows are not visible in every frame due to camera angle.\",\"The abrupt suspended road-start edge is only directly visible in the middle portion of the clip, not across all frames.\",\"The suspended edge looks somewhat artificial/game-like in some frames, slightly reducing the clean minimal realism.\"]}}", + "provider": "openai", + "response_id": "resp_072b0ac1301f4ae9006acf2b504e4087d09f9117f140a9effd", + "usage": { + "input_tokens": 22551, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1275, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23826 + } + } + }, + { + "agent": "object", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Object Rubric Items\n\n### obj_01\nRubric: When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?\n\n### obj_02\nRubric: When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?\n\n### obj_03\nRubric: When the car is visible and judgeable, are there exactly two black racing stripes on it?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961936, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"obj_01\",\"reasoning\":\"The main vehicle is visible and judgeable in all sampled frames. In rear views at frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, it has a low, compact coupe profile with wide stance and sporty rear styling. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s, it consistently appears as a two-door, low-slung performance coupe rather than a sedan, SUV, truck, or other vehicle class. The shape remains stable throughout the clip.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=6.7s\",\"frame_t=7.2s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"obj_02\",\"reasoning\":\"The car is clearly visible across the sequence, and its body is consistently predominantly yellow. This is evident in rear view at frame_t=0.0s, side views at frame_t=2.2s and frame_t=6.7s, front view at frame_t=4.4s, and rear three-quarter views at frame_t=8.3s and frame_t=9.4s. Black accents and stripes are present, but they do not dominate the body color; yellow remains the primary body color in all judgeable frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=6.7s\",\"frame_t=8.3s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"obj_03\",\"reasoning\":\"Across the visible frames, the car consistently shows two black racing stripes running along the car body. In rear and top-rear views at frame_t=0.0s, frame_t=0.6s, and frame_t=8.9s, two parallel black stripes are visible on the roof/trunk area. In side and front-three-quarter views at frame_t=2.2s, frame_t=3.9s, frame_t=5.6s, and frame_t=7.8s, the hood and roof also show exactly two black stripes. A small separate black patch near the rear/trunk area appears in some angles, but it does not read as an additional full racing stripe; the primary stripe count remains clearly two throughout.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=2.2s\",\"frame_t=3.9s\",\"frame_t=5.6s\",\"frame_t=7.8s\",\"frame_t=8.9s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The main object is highly consistent with the prompt: the vehicle is clearly a yellow sports car and it consistently carries two black racing stripes when visible.\",\"issues\":[]}}", + "provider": "openai", + "response_id": "resp_0936f2f93b40ec28006acf2b50439487d087d3630b3dc73104", + "usage": { + "input_tokens": 22571, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 678, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23249 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "The main object is highly consistent with the prompt: the vehicle is clearly a yellow sports car and it consistently carries two black racing stripes when visible." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=6.7s", + "frame_t=7.2s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The main vehicle is visible and judgeable in all sampled frames. In rear views at frame_t=0.0s, frame_t=8.9s, and frame_t=9.4s, it has a low, compact coupe profile with wide stance and sporty rear styling. In side and three-quarter views at frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s, it consistently appears as a two-door, low-slung performance coupe rather than a sedan, SUV, truck, or other vehicle class. The shape remains stable throughout the clip.", + "rubric_id": "obj_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=6.7s", + "frame_t=8.3s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The car is clearly visible across the sequence, and its body is consistently predominantly yellow. This is evident in rear view at frame_t=0.0s, side views at frame_t=2.2s and frame_t=6.7s, front view at frame_t=4.4s, and rear three-quarter views at frame_t=8.3s and frame_t=9.4s. Black accents and stripes are present, but they do not dominate the body color; yellow remains the primary body color in all judgeable frames.", + "rubric_id": "obj_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=2.2s", + "frame_t=3.9s", + "frame_t=5.6s", + "frame_t=7.8s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "Across the visible frames, the car consistently shows two black racing stripes running along the car body. In rear and top-rear views at frame_t=0.0s, frame_t=0.6s, and frame_t=8.9s, two parallel black stripes are visible on the roof/trunk area. In side and front-three-quarter views at frame_t=2.2s, frame_t=3.9s, frame_t=5.6s, and frame_t=7.8s, the hood and roof also show exactly two black stripes. A small separate black patch near the rear/trunk area appears in some angles, but it does not read as an additional full racing stripe; the primary stripe count remains clearly two throughout.", + "rubric_id": "obj_03" + } + ], + "score": 1.0 + }, + "overall_score": 0.88, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 8 + }, + "scene_name": "RacingCar" + }, + "obj_score": 1.0, + "overall_score": 0.88, + "pass": 3 + }, + { + "env_score": 0.7333, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "Both sides of the highway do not consistently show barriers, grass, and tree rows in all frames, especially near the road start views.", + "The abrupt starting edge of the road with open sky behind is only clearly visible in the middle portion of the clip, not throughout all sampled frames." + ], + "summary": "The video matches the prompt well on the wide straight highway, clear blue sky, and bright minimal daytime look. The main weaknesses are inconsistent visibility of the full two-sided roadside tree/grass/barrier setup and the abrupt suspended road start, which appears clearly only in part of the clip." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The prompt calls for a very wide, straight highway extending forward. In the early rear-view frames, the highway is clearly very wide with many lanes and a straight vanishing point ahead, visible in frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. Mid and late frames continue to show the same broad straight roadway from changing camera angles, including frame_t=7.8s, frame_t=8.3s, and frame_t=8.9s. Even when the camera rotates toward the road start, the visible lane markings remain parallel and the roadway structure stays straight rather than curving, as seen in frame_t=4.4s and frame_t=5.0s. This attribute is consistently present across the clip.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.3s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies a clear blue sky. Across all sampled frames, the background sky is a uniform light blue with no clouds or weather effects. This is visible at the start in frame_t=0.0s, during the side/start-point views in frame_t=2.8s, frame_t=4.4s, and frame_t=5.6s, and again in the later rear-view frames such as frame_t=8.3s and frame_t=9.4s. There is no meaningful change in sky color or clarity.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=2.8s", + "frame_t=3.9s", + "frame_t=5.6s", + "frame_t=8.9s" + ], + "judged_score": 1, + "reasoning": "The prompt asks for dark roadside barriers, green grass, and long rows of tall trees on both sides. In the opening and closing rear-oriented frames, both sides of the highway clearly contain all three elements: dark barriers, narrow green grass strips, and dense tall trees extending into the distance, as shown in frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s. However, when the camera moves near the starting edge of the road, both sides are not consistently visible and the left side especially drops out into open sky in several frames such as frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, and frame_t=5.6s. Because the rubric asks for consistency across all sampled frames and both sides are not maintained visually in a non-trivial portion, this is only a partial match.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.1s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=6.1s" + ], + "judged_score": 1, + "reasoning": "The prompt specifies that the road begins abruptly with no ground behind it, only open sky, giving a suspended-in-space effect. This feature is absent in the opening frames, where the highway appears to continue normally behind the camera viewpoint rather than showing an obvious starting edge, as in frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. The abrupt road start with open sky behind becomes clearly visible only in the middle portion of the clip, especially frame_t=2.8s through frame_t=6.1s, where the road edge ends against open sky. Since this defining environmental attribute is visible only in some frames and not across all sampled frames, consistency is weak.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=4.4s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The prompt asks for bright daytime lighting and a clean, minimal environment. Throughout the clip, illumination is bright and even, with no nighttime, dusk, or harsh weather changes. The road, barriers, grass, and trees are rendered simply with little clutter, visible in frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, and frame_t=8.9s. The environment remains sparse and uncluttered with no extra structures or distracting background elements. Despite some geometric oddity near the road start, the overall lighting and minimal style remain consistent.", + "rubric_id": "env_05" + } + ], + "score": 0.7333 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all sampled frames?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?\n\n### env_04\nRubric: Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?\n\n### env_05\nRubric: Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961936, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The prompt calls for a very wide, straight highway extending forward. In the early rear-view frames, the highway is clearly very wide with many lanes and a straight vanishing point ahead, visible in frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. Mid and late frames continue to show the same broad straight roadway from changing camera angles, including frame_t=7.8s, frame_t=8.3s, and frame_t=8.9s. Even when the camera rotates toward the road start, the visible lane markings remain parallel and the roadway structure stays straight rather than curving, as seen in frame_t=4.4s and frame_t=5.0s. This attribute is consistently present across the clip.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The prompt specifies a clear blue sky. Across all sampled frames, the background sky is a uniform light blue with no clouds or weather effects. This is visible at the start in frame_t=0.0s, during the side/start-point views in frame_t=2.8s, frame_t=4.4s, and frame_t=5.6s, and again in the later rear-view frames such as frame_t=8.3s and frame_t=9.4s. There is no meaningful change in sky color or clarity.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.3s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt asks for dark roadside barriers, green grass, and long rows of tall trees on both sides. In the opening and closing rear-oriented frames, both sides of the highway clearly contain all three elements: dark barriers, narrow green grass strips, and dense tall trees extending into the distance, as shown in frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s. However, when the camera moves near the starting edge of the road, both sides are not consistently visible and the left side especially drops out into open sky in several frames such as frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, and frame_t=5.6s. Because the rubric asks for consistency across all sampled frames and both sides are not maintained visually in a non-trivial portion, this is only a partial match.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=2.8s\",\"frame_t=3.9s\",\"frame_t=5.6s\",\"frame_t=8.9s\"],\"judged_score\":1},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt specifies that the road begins abruptly with no ground behind it, only open sky, giving a suspended-in-space effect. This feature is absent in the opening frames, where the highway appears to continue normally behind the camera viewpoint rather than showing an obvious starting edge, as in frame_t=0.0s, frame_t=0.6s, and frame_t=1.1s. The abrupt road start with open sky behind becomes clearly visible only in the middle portion of the clip, especially frame_t=2.8s through frame_t=6.1s, where the road edge ends against open sky. Since this defining environmental attribute is visible only in some frames and not across all sampled frames, consistency is weak.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.1s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=6.1s\"],\"judged_score\":1},{\"rubric_id\":\"env_05\",\"reasoning\":\"The prompt asks for bright daytime lighting and a clean, minimal environment. Throughout the clip, illumination is bright and even, with no nighttime, dusk, or harsh weather changes. The road, barriers, grass, and trees are rendered simply with little clutter, visible in frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, and frame_t=8.9s. The environment remains sparse and uncluttered with no extra structures or distracting background elements. Despite some geometric oddity near the road start, the overall lighting and minimal style remain consistent.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=4.4s\",\"frame_t=8.9s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt well on the wide straight highway, clear blue sky, and bright minimal daytime look. The main weaknesses are inconsistent visibility of the full two-sided roadside tree/grass/barrier setup and the abrupt suspended road start, which appears clearly only in part of the clip.\",\"issues\":[\"Both sides of the highway do not consistently show barriers, grass, and tree rows in all frames, especially near the road start views.\",\"The abrupt starting edge of the road with open sky behind is only clearly visible in the middle portion of the clip, not throughout all sampled frames.\"]}}", + "provider": "openai", + "response_id": "resp_048ae55bfc5c2537006acf2b50573887d0a5ac6c8685acde0b", + "usage": { + "input_tokens": 22551, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 1209, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23760 + } + } + }, + { + "agent": "object", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Object Rubric Items\n\n### obj_01\nRubric: When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?\n\n### obj_02\nRubric: When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?\n\n### obj_03\nRubric: When the car is visible and judgeable, are there exactly two black racing stripes on it?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961935, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"obj_01\",\"reasoning\":\"The targeted entity is the main vehicle. In all sampled frames where the vehicle is visible, it has a low-slung coupe profile, two-door sports-car proportions, a short cabin, pronounced hood and trunk, and sporty front/rear fascia. This is visible from the rear at frame_t=0.0s and frame_t=8.9s, from side/rear angles at frame_t=1.1s, frame_t=7.8s, and frame_t=9.4s, and from front/side angles at frame_t=3.9s and frame_t=5.6s. There is no frame where it resembles an SUV, truck, sedan, or other non-sports-car vehicle type. Therefore the vehicle is clearly a sports car throughout visible frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=3.9s\",\"frame_t=5.6s\",\"frame_t=7.8s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"obj_02\",\"reasoning\":\"The rubric asks whether the car body is predominantly yellow. Across all visible frames, the vehicle body panels are consistently yellow, including rear views at frame_t=0.0s and frame_t=8.9s, side views at frame_t=2.2s and frame_t=6.7s, and front/three-quarter views at frame_t=4.4s and frame_t=5.0s. Black accents are limited to the racing stripes, windows, and some trim, but the main body color remains clearly yellow in every judgeable frame. No meaningful color shift or alternate body color appears.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=6.7s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"obj_03\",\"reasoning\":\"The rubric asks for exactly two black racing stripes on the car. In multiple clear views, two parallel black stripes are visible running along the top surfaces of the car, including the roof/hood/trunk regions. This is clearly seen from behind at frame_t=0.0s and frame_t=8.9s, from side/top angles at frame_t=1.7s, frame_t=2.8s, and frame_t=7.2s, and from front views at frame_t=4.4s and frame_t=5.0s. Although perspective changes make portions of the stripes more or less visible at times, the visible evidence consistently supports exactly two stripes rather than one or more than two.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=7.2s\",\"frame_t=8.9s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The main object is highly consistent with the prompt: the video shows a yellow sports car with two black racing stripes throughout the sampled frames.\",\"issues\":[]}}", + "provider": "openai", + "response_id": "resp_0cff1281a9c1fce2006acf2b4fca2887d0a80bdec3cb43d317", + "usage": { + "input_tokens": 22571, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 21504 + }, + "output_tokens": 710, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23281 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [], + "summary": "The main object is highly consistent with the prompt: the video shows a yellow sports car with two black racing stripes throughout the sampled frames." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=3.9s", + "frame_t=5.6s", + "frame_t=7.8s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The targeted entity is the main vehicle. In all sampled frames where the vehicle is visible, it has a low-slung coupe profile, two-door sports-car proportions, a short cabin, pronounced hood and trunk, and sporty front/rear fascia. This is visible from the rear at frame_t=0.0s and frame_t=8.9s, from side/rear angles at frame_t=1.1s, frame_t=7.8s, and frame_t=9.4s, and from front/side angles at frame_t=3.9s and frame_t=5.6s. There is no frame where it resembles an SUV, truck, sedan, or other non-sports-car vehicle type. Therefore the vehicle is clearly a sports car throughout visible frames.", + "rubric_id": "obj_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=6.7s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The rubric asks whether the car body is predominantly yellow. Across all visible frames, the vehicle body panels are consistently yellow, including rear views at frame_t=0.0s and frame_t=8.9s, side views at frame_t=2.2s and frame_t=6.7s, and front/three-quarter views at frame_t=4.4s and frame_t=5.0s. Black accents are limited to the racing stripes, windows, and some trim, but the main body color remains clearly yellow in every judgeable frame. No meaningful color shift or alternate body color appears.", + "rubric_id": "obj_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=7.2s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The rubric asks for exactly two black racing stripes on the car. In multiple clear views, two parallel black stripes are visible running along the top surfaces of the car, including the roof/hood/trunk regions. This is clearly seen from behind at frame_t=0.0s and frame_t=8.9s, from side/top angles at frame_t=1.7s, frame_t=2.8s, and frame_t=7.2s, and from front views at frame_t=4.4s and frame_t=5.0s. Although perspective changes make portions of the stripes more or less visible at times, the visible evidence consistently supports exactly two stripes rather than one or more than two.", + "rubric_id": "obj_03" + } + ], + "score": 1.0 + }, + "overall_score": 0.84, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 8 + }, + "scene_name": "RacingCar" + }, + "obj_score": 1.0, + "overall_score": 0.84, + "pass": 4 + }, + { + "env_score": 0.8, + "judge_result": { + "alpha": 0.6, + "environment_result": { + "agent": "environment", + "explanations": { + "issues": [ + "The abrupt suspended start of the road is only directly verifiable in the middle portion of the video, not across all frames.", + "Both roadside barriers/grass/tree rows are not equally visible in some side-angle and road-start views.", + "Some frames near the road start emphasize open sky and edge geometry, reducing visibility of the full two-sided environment." + ], + "summary": "The video matches the prompt’s environment well overall: it shows a very wide straight highway, clear blue sky, bright daytime lighting, and the expected minimal roadside scenery. The main weakness is that the suspended-road starting edge is only directly visible in part of the sequence, and both-side roadside details are less consistently shown in some camera angles." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.6s", + "frame_t=8.3s", + "frame_t=8.9s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The prompt asks for a very wide, straight highway extending forward. In the early and late frames, this is clearly visible: frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s all show a broad multi-lane road with straight lane markings and a long vanishing point ahead. Mid-sequence side views such as frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s still show the highway lanes running straight and parallel, supporting consistency. However, when the camera reaches the road start area in frame_t=3.9s through frame_t=5.6s, the visible forward extension is reduced because the road appears to terminate abruptly at the edge; while this is compatible with the prompt's suspended-road concept, it makes the long forward extension less consistently visible in those frames. Overall the highway remains very wide and straight in the vast majority of frames.", + "rubric_id": "env_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=6.1s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The prompt specifies a clear blue sky. Across all sampled frames, the sky appears uniformly blue without clouds or weather effects. This is evident in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=6.1s, and frame_t=9.4s. Even when the camera rotates around the car, the sky remains clear and stable with no visible atmospheric changes. There are no contradictory frames.", + "rubric_id": "env_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=0.6s", + "frame_t=1.7s", + "frame_t=2.2s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=8.3s", + "frame_t=8.9s" + ], + "judged_score": 2, + "reasoning": "The prompt requires both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. In balanced rear and rear-quarter views such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s, both sides clearly contain the dark barriers, green strips, and tall dense tree rows. In side-oriented frames like frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s, only one side is prominently visible due to camera angle, but the visible side still matches the prompt well. A minor issue appears around the road-start views, especially frame_t=3.9s to frame_t=5.6s, where the composition shows gaps/open sky beyond the road edge and only partial side scenery, making both sides less consistently represented in those moments. Still, the side environment is correct in most frames.", + "rubric_id": "env_03" + }, + { + "frame_evidence": [ + "frame_t=3.3s", + "frame_t=3.9s", + "frame_t=4.4s", + "frame_t=5.0s", + "frame_t=5.6s", + "frame_t=6.1s", + "frame_t=0.0s", + "frame_t=8.3s" + ], + "judged_score": 1, + "reasoning": "The prompt specifies that the road begins abruptly with no ground behind it, only open sky, as if suspended in space. This feature is clearly visible in the frames where the camera looks toward the start of the road: frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, and frame_t=6.1s all show the roadway ending sharply with open sky beyond and no supporting ground behind it. In earlier and later frames such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=9.4s, that start edge is not visible because the camera is oriented down the highway, so the attribute is not directly verifiable there. Since the prompt asks for this condition across all sampled frames and it is only visible/confirmable in a portion of them, the match is partial rather than fully consistent.", + "rubric_id": "env_04" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=4.4s", + "frame_t=7.8s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The environment is supposed to have bright daytime lighting and a clean, minimal look. Throughout the sequence, lighting is consistently bright with clear visibility and crisp shadows, as seen in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. The scene remains visually simple: wide road, barriers, grass, trees, and sky, without clutter or extraneous background elements. The only mild limitation is that the suspended-road edge introduces a somewhat artificial look in mid-frames, but it still aligns with the prompt’s minimal environment rather than contradicting it. Overall this criterion is satisfied consistently.", + "rubric_id": "env_05" + } + ], + "score": 0.8 + }, + "judge_calls": [ + { + "agent": "environment", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "6eabac3b5374e26860c38ef3eb04aae2733a35f5b6ef2495b19f16355f03b7cf", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Environment Rubric Items\n\n### env_01\nRubric: Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?\n\n### env_02\nRubric: Does the sky stay clear blue across all sampled frames?\n\n### env_03\nRubric: Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?\n\n### env_04\nRubric: Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?\n\n### env_05\nRubric: Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961934, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"env_01\",\"reasoning\":\"The prompt asks for a very wide, straight highway extending forward. In the early and late frames, this is clearly visible: frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, frame_t=8.9s, and frame_t=9.4s all show a broad multi-lane road with straight lane markings and a long vanishing point ahead. Mid-sequence side views such as frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s still show the highway lanes running straight and parallel, supporting consistency. However, when the camera reaches the road start area in frame_t=3.9s through frame_t=5.6s, the visible forward extension is reduced because the road appears to terminate abruptly at the edge; while this is compatible with the prompt's suspended-road concept, it makes the long forward extension less consistently visible in those frames. Overall the highway remains very wide and straight in the vast majority of frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.6s\",\"frame_t=8.3s\",\"frame_t=8.9s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_02\",\"reasoning\":\"The prompt specifies a clear blue sky. Across all sampled frames, the sky appears uniformly blue without clouds or weather effects. This is evident in frame_t=0.0s, frame_t=2.8s, frame_t=4.4s, frame_t=6.1s, and frame_t=9.4s. Even when the camera rotates around the car, the sky remains clear and stable with no visible atmospheric changes. There are no contradictory frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=6.1s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"env_03\",\"reasoning\":\"The prompt requires both sides of the highway to show dark roadside barriers, green grass, and long rows of tall trees. In balanced rear and rear-quarter views such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=8.9s, both sides clearly contain the dark barriers, green strips, and tall dense tree rows. In side-oriented frames like frame_t=1.7s, frame_t=2.2s, frame_t=6.7s, and frame_t=7.2s, only one side is prominently visible due to camera angle, but the visible side still matches the prompt well. A minor issue appears around the road-start views, especially frame_t=3.9s to frame_t=5.6s, where the composition shows gaps/open sky beyond the road edge and only partial side scenery, making both sides less consistently represented in those moments. Still, the side environment is correct in most frames.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=0.6s\",\"frame_t=1.7s\",\"frame_t=2.2s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=8.3s\",\"frame_t=8.9s\"],\"judged_score\":2},{\"rubric_id\":\"env_04\",\"reasoning\":\"The prompt specifies that the road begins abruptly with no ground behind it, only open sky, as if suspended in space. This feature is clearly visible in the frames where the camera looks toward the start of the road: frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, and frame_t=6.1s all show the roadway ending sharply with open sky beyond and no supporting ground behind it. In earlier and later frames such as frame_t=0.0s, frame_t=0.6s, frame_t=8.3s, and frame_t=9.4s, that start edge is not visible because the camera is oriented down the highway, so the attribute is not directly verifiable there. Since the prompt asks for this condition across all sampled frames and it is only visible/confirmable in a portion of them, the match is partial rather than fully consistent.\",\"frame_evidence\":[\"frame_t=3.3s\",\"frame_t=3.9s\",\"frame_t=4.4s\",\"frame_t=5.0s\",\"frame_t=5.6s\",\"frame_t=6.1s\",\"frame_t=0.0s\",\"frame_t=8.3s\"],\"judged_score\":1},{\"rubric_id\":\"env_05\",\"reasoning\":\"The environment is supposed to have bright daytime lighting and a clean, minimal look. Throughout the sequence, lighting is consistently bright with clear visibility and crisp shadows, as seen in frame_t=0.0s, frame_t=1.1s, frame_t=4.4s, frame_t=7.8s, and frame_t=9.4s. The scene remains visually simple: wide road, barriers, grass, trees, and sky, without clutter or extraneous background elements. The only mild limitation is that the suspended-road edge introduces a somewhat artificial look in mid-frames, but it still aligns with the prompt’s minimal environment rather than contradicting it. Overall this criterion is satisfied consistently.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=4.4s\",\"frame_t=7.8s\",\"frame_t=9.4s\"],\"judged_score\":3}],\"explanations\":{\"summary\":\"The video matches the prompt’s environment well overall: it shows a very wide straight highway, clear blue sky, bright daytime lighting, and the expected minimal roadside scenery. The main weakness is that the suspended-road starting edge is only directly visible in part of the sequence, and both-side roadside details are less consistently shown in some camera angles.\",\"issues\":[\"The abrupt suspended start of the road is only directly verifiable in the middle portion of the video, not across all frames.\",\"Both roadside barriers/grass/tree rows are not equally visible in some side-angle and road-start views.\",\"Some frames near the road start emphasize open sky and edge geometry, reducing visibility of the full two-sided environment.\"]}}", + "provider": "openai", + "response_id": "resp_018831187318dc5b006acf2b4df34087d0ad9edadaae26989c", + "usage": { + "input_tokens": 22551, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 0 + }, + "output_tokens": 1440, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23991 + } + } + }, + { + "agent": "object", + "request": { + "images": [ + { + "label": "ref_frame", + "sha256": "3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea" + }, + { + "label": "frame_t=0.0s", + "sha256": "03c62786995697c289316b0a52cedb0ff50b356846a2d90b219ff9c36a145023" + }, + { + "label": "frame_t=0.6s", + "sha256": "b83cd26a64ef2b240cb2468d79a0a56c0ef929b31be42e242b07842818981ef6" + }, + { + "label": "frame_t=1.1s", + "sha256": "adbd6a0c807f9e0f8e443d73804f03c5262f6a6a589a5ecec13dcb1fda6b27ab" + }, + { + "label": "frame_t=1.7s", + "sha256": "df6c58d2f2e0c072331d9934defdf47b353bd582db44d2a0b793d818fd27f05c" + }, + { + "label": "frame_t=2.2s", + "sha256": "82731dbf4e8e3c841e1da4702fb89540b4209abbbeb6a8d8474f11ca6a720c71" + }, + { + "label": "frame_t=2.8s", + "sha256": "37b54c4fdb5ec594b8e985f02fd50b89024fdebad004be53f11b211c7c03acc6" + }, + { + "label": "frame_t=3.3s", + "sha256": "91cd0eddb3fffb4b6367c7fbbdefd9948bc552a83155013918f94d72f17e991d" + }, + { + "label": "frame_t=3.9s", + "sha256": "46066acae189495244b137b4855717f90f27c04ebdfa5931b0a5d0d3e738e7c3" + }, + { + "label": "frame_t=4.4s", + "sha256": "ac6be00d80f008ae25580933d0b603f5ba6d4a962ca3613226cdb0f93faeadaa" + }, + { + "label": "frame_t=5.0s", + "sha256": "0822b41bdc44de1e28f75ac3d6268e9daf1c3e086456cb7139b0cbc4fad3f6d5" + }, + { + "label": "frame_t=5.6s", + "sha256": "b16637cdfb2dd26a891eed1f4b00b5ca7f269179702cb16fa0f3685ef3191ffc" + }, + { + "label": "frame_t=6.1s", + "sha256": "cc0d3604c814e4968ccbb56eccf8478f6ac030ec7773576d17c55144a66bfe80" + }, + { + "label": "frame_t=6.7s", + "sha256": "824a166f8c8a20cbb057433e130d6817b14b74ebb1e0f1c62371cd511d93176b" + }, + { + "label": "frame_t=7.2s", + "sha256": "dadd51867f800c36851088ac7bd74605b905a38f653e0cb87c35e8f435d1a4d7" + }, + { + "label": "frame_t=7.8s", + "sha256": "4dde24523044686fc294b3a51058bb749d0d4af78e618ad62239f55f8ecf303f" + }, + { + "label": "frame_t=8.3s", + "sha256": "5344a5b4278f4330197e0cfc5cf0181e94e0f88fba52e1893d4c8800745c21ca" + }, + { + "label": "frame_t=8.9s", + "sha256": "c234b6b0fdbefb07f61d6725a56d2e02da04258c5cdbd40fdd88367985c1e97e" + }, + { + "label": "frame_t=9.4s", + "sha256": "bbf66a7d5caaac28bc30ae9168e2e6e994730518ac7285771f52ffb8c6d60167" + } + ], + "model": "gpt-5.4", + "schema_sha256": "f5dcf678e0fd5ac5e2293ac0eb379e41d67bb3b1a43b3eec5b1af8a6be21664c", + "system_prompt_sha256": "674a919215f02571563c873dec603d13b63a4c32276f59b37d5d7620213fadd2", + "user_text": "## Evaluation Task\nEvaluate the candidate video frames against each rubric item below.\n\nReference image: ref_frame\nCandidate frames: frame_t=0.0s, frame_t=0.6s, frame_t=1.1s, frame_t=1.7s, frame_t=2.2s, frame_t=2.8s, frame_t=3.3s, frame_t=3.9s, frame_t=4.4s, frame_t=5.0s, frame_t=5.6s, frame_t=6.1s, frame_t=6.7s, frame_t=7.2s, frame_t=7.8s, frame_t=8.3s, frame_t=8.9s, frame_t=9.4s\n\nPrompt:\nA very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car\n\n## Object Rubric Items\n\n### obj_01\nRubric: When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?\n\n### obj_02\nRubric: When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?\n\n### obj_03\nRubric: When the car is visible and judgeable, are there exactly two black racing stripes on it?\n\nEvaluate each rubric item and return structured JSON." + }, + "response": { + "attempts": 1, + "created_at": 1791961932, + "model_requested": "gpt-5.4", + "model_resolved": "gpt-5.4-2026-03-05", + "output_text": "{\"item_scores\":[{\"rubric_id\":\"obj_01\",\"reasoning\":\"The main vehicle is visible in all sampled frames. In rear, side, and front-quarter views, it has a low-slung two-door coupe profile, compact body, sporty proportions, and styling associated with a sports car rather than an SUV, sedan, truck, or van. This is clear in the rear view at frame_t=0.0s and frame_t=8.9s, the side views at frame_t=2.2s and frame_t=6.7s, and the front views at frame_t=4.4s and frame_t=5.0s. No frame suggests a different vehicle type.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=2.2s\",\"frame_t=4.4s\",\"frame_t=6.7s\",\"frame_t=8.9s\"],\"judged_score\":3},{\"rubric_id\":\"obj_02\",\"reasoning\":\"The car body appears predominantly yellow throughout the clip. Across rear, side, and front angles, the body panels are consistently yellow, while windows and stripes are black and wheels are gray/white. This is evident at frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, frame_t=7.2s, and frame_t=9.4s. There is no meaningful color shift away from yellow in any judgeable frame.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.7s\",\"frame_t=4.4s\",\"frame_t=7.2s\",\"frame_t=9.4s\"],\"judged_score\":3},{\"rubric_id\":\"obj_03\",\"reasoning\":\"The prompt calls for exactly two black racing stripes. In most visible frames, the car clearly shows two black longitudinal stripes on the hood/roof/rear deck area. This is visible from behind at frame_t=0.0s, from side/rear angles at frame_t=0.6s and frame_t=7.8s, and from front angles at frame_t=4.4s and frame_t=5.6s. However, there is a brief inconsistency/ambiguity in some side views where the roof region appears to suggest an extra narrow dark band or broken stripe segment, especially around frame_t=1.1s to frame_t=2.8s, making the exact count slightly less clean than perfect. The dominant presentation is still two black stripes.\",\"frame_evidence\":[\"frame_t=0.0s\",\"frame_t=1.1s\",\"frame_t=2.8s\",\"frame_t=4.4s\",\"frame_t=7.8s\"],\"judged_score\":2}],\"explanations\":{\"summary\":\"The main object is consistently a yellow sports car and mostly matches the prompt well. The only notable object-level issue is minor ambiguity in the exact stripe count in some angles.\",\"issues\":[\"Minor ambiguity/inconsistency in the appearance of the two black racing stripes in a few side-view frames.\"]}}", + "provider": "openai", + "response_id": "resp_06ba306740b44139006acf2b4c201087d0ac37f75dfcce4d1b", + "usage": { + "input_tokens": 22571, + "input_tokens_details": { + "cache_write_tokens": 0, + "cached_tokens": 0 + }, + "output_tokens": 653, + "output_tokens_details": { + "reasoning_tokens": 0 + }, + "total_tokens": 23224 + } + } + } + ], + "model": "gpt-5.4", + "num_frames": 18, + "object_result": { + "agent": "object", + "explanations": { + "issues": [ + "Minor ambiguity/inconsistency in the appearance of the two black racing stripes in a few side-view frames." + ], + "summary": "The main object is consistently a yellow sports car and mostly matches the prompt well. The only notable object-level issue is minor ambiguity in the exact stripe count in some angles." + }, + "item_scores": [ + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=2.2s", + "frame_t=4.4s", + "frame_t=6.7s", + "frame_t=8.9s" + ], + "judged_score": 3, + "reasoning": "The main vehicle is visible in all sampled frames. In rear, side, and front-quarter views, it has a low-slung two-door coupe profile, compact body, sporty proportions, and styling associated with a sports car rather than an SUV, sedan, truck, or van. This is clear in the rear view at frame_t=0.0s and frame_t=8.9s, the side views at frame_t=2.2s and frame_t=6.7s, and the front views at frame_t=4.4s and frame_t=5.0s. No frame suggests a different vehicle type.", + "rubric_id": "obj_01" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.7s", + "frame_t=4.4s", + "frame_t=7.2s", + "frame_t=9.4s" + ], + "judged_score": 3, + "reasoning": "The car body appears predominantly yellow throughout the clip. Across rear, side, and front angles, the body panels are consistently yellow, while windows and stripes are black and wheels are gray/white. This is evident at frame_t=0.0s, frame_t=1.7s, frame_t=4.4s, frame_t=7.2s, and frame_t=9.4s. There is no meaningful color shift away from yellow in any judgeable frame.", + "rubric_id": "obj_02" + }, + { + "frame_evidence": [ + "frame_t=0.0s", + "frame_t=1.1s", + "frame_t=2.8s", + "frame_t=4.4s", + "frame_t=7.8s" + ], + "judged_score": 2, + "reasoning": "The prompt calls for exactly two black racing stripes. In most visible frames, the car clearly shows two black longitudinal stripes on the hood/roof/rear deck area. This is visible from behind at frame_t=0.0s, from side/rear angles at frame_t=0.6s and frame_t=7.8s, and from front angles at frame_t=4.4s and frame_t=5.6s. However, there is a brief inconsistency/ambiguity in some side views where the roof region appears to suggest an extra narrow dark band or broken stripe segment, especially around frame_t=1.1s to frame_t=2.8s, making the exact count slightly less clean than perfect. The dominant presentation is still two black stripes.", + "rubric_id": "obj_03" + } + ], + "score": 0.8889 + }, + "overall_score": 0.8356, + "provider": "openai", + "rubric_metadata": { + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "generator_model": "gpt-5.4", + "generator_provider": "openai", + "num_candidates_generated": 8 + }, + "scene_name": "RacingCar" + }, + "obj_score": 0.8889, + "overall_score": 0.8356, + "pass": 5 + } + ], + "reference_video": "reference/unity_groundtruth.mp4", + "reference_video_sha256": "e372aca1ed36cc093cd3cf8f164d4da581d0aa5762d6ea4e58778815e89aa067", + "schema_version": 1, + "summary": { + "env_score": { + "max": 0.8, + "mean": 0.7733, + "min": 0.7333, + "n": 5, + "std": 0.0365 + }, + "obj_score": { + "max": 1.0, + "mean": 0.9333, + "min": 0.7778, + "n": 5, + "std": 0.0994 + }, + "overall_score": { + "max": 0.88, + "mean": 0.8373, + "min": 0.7511, + "n": 5, + "std": 0.0526 + } + } +} diff --git a/cases/RacingCar/prompt_third/reference/artifacts/rubrics/RacingCar/openai_gpt-5-4_v0.json b/cases/RacingCar/prompt_third/reference/artifacts/rubrics/RacingCar/openai_gpt-5-4_v0.json new file mode 100644 index 0000000000000000000000000000000000000000..9ba8a7c3d4b151e4aa57a42d530e520f98c9d793 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/rubrics/RacingCar/openai_gpt-5-4_v0.json @@ -0,0 +1,60 @@ +{ + "scene_name": "RacingCar", + "prompt_text": "A very wide, straight highway under a clear blue sky, with dark roadside barriers, green grass, and long rows of tall trees on both sides. The road begins abruptly at a starting point, with no ground behind it—only open sky, as if the road is suspended in space. A yellow sports car with two black racing stripes is parking exactly at the start of the road, centered in the frame, viewed from behind. The car faces forward into the long empty highway. Bright daytime lighting, clean and minimal environment. The character is the yellow sports car", + "rubric_items": [ + { + "rubric_id": "env_01", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the environment consistently show a very wide, straight highway extending forward across all sampled frames?" + }, + { + "rubric_id": "env_02", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the sky stay clear blue across all sampled frames?" + }, + { + "rubric_id": "env_03", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Do both sides of the highway consistently show dark roadside barriers, green grass, and long rows of tall trees across all sampled frames?" + }, + { + "rubric_id": "env_04", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Across all sampled frames, does the road begin abruptly with no ground behind it, showing only open sky as if suspended in space?" + }, + { + "rubric_id": "env_05", + "agent": "environment", + "weight": 1.0, + "rubric_text": "Does the environment consistently maintain bright daytime lighting and a clean, minimal look across all sampled frames?" + }, + { + "rubric_id": "obj_01", + "agent": "object", + "weight": 1.0, + "rubric_text": "When the main vehicle is visible and judgeable, is it clearly a sports car rather than another type of vehicle?" + }, + { + "rubric_id": "obj_02", + "agent": "object", + "weight": 1.0, + "rubric_text": "When the car is visible and judgeable, is its body predominantly yellow as specified in the prompt?" + }, + { + "rubric_id": "obj_03", + "agent": "object", + "weight": 1.0, + "rubric_text": "When the car is visible and judgeable, are there exactly two black racing stripes on it?" + } + ], + "metadata": { + "generator_provider": "openai", + "generator_model": "gpt-5.4", + "generated_at": "2026-05-06T10:42:49.157215+00:00", + "num_candidates_generated": 8 + } +} \ No newline at end of file diff --git a/cases/RacingCar/prompt_third/reference/artifacts/trajectory.yaml b/cases/RacingCar/prompt_third/reference/artifacts/trajectory.yaml new file mode 100644 index 0000000000000000000000000000000000000000..3c9c9f5c33ee71578ff0395782d976d495481804 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/artifacts/trajectory.yaml @@ -0,0 +1,20 @@ +schema_version: 1 +trajectory_id: prompt.camera.left_turn_v1 +description: Continuous left (counter-clockwise) camera turn of the prompt-scene consistency cases (hold ArrowLeft for 10 s); in place in first person, around the character in third person. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 10.0, values: {yaw_rate_deg_s: -40.0}} +paper_alignment: + status: reconstructed + matched: [ten_second_left_camera_turn, unity_reference_turn_rate] + missing: The paper specifies a 10 s camera turn but no rate; 40 deg/s is the turn measured in every case's Unity reference poses. + source: ../../../eval_sets/wmeval_lite_v1/cases/ChessBoard/prompt_first/reference/artifacts/poses.npy +adapters: + unity: {status: reference, channel: yaw_rate_deg_s} + project_genie: + status: nominal + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/RacingCar/prompt_third/reference/checksums.sha256 b/cases/RacingCar/prompt_third/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..e12a24594e73d562f189446de38ffe74220f1f16 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/checksums.sha256 @@ -0,0 +1,14 @@ +402da2a8afaa4fbbe3bea7a22c3b7ab1bbe7a933d2682be371aef670b90ed7a7 reference/artifacts/action.npy +35a052e6999a15f1138f0baf229eda4561574e0076b2349b3d01d653b417492e reference/artifacts/action.npz +862f3c8fa9543110b9cca3df5923165db879352cf7a124bd46df6ad8fa1b9547 reference/artifacts/actions.jsonl +6c1b16087a172c31b7477f34056143101b780c7dff749cb04047854ec3e82738 reference/artifacts/actions.txt +a6c8f44991fde99816940c50810bc9e858cfd8bb587a3d5d042c5f3e0f1038a5 reference/artifacts/intrinsics.npy +01aa43256385d65e3e8de91f84f36c67806d6eb9bf29e475a590dc124fd1a0de reference/artifacts/intrinsics_t4.npy +329fa628fa914cedd695ebf4be8c4c59348db551810f03a2872a5934d4ac58fe reference/artifacts/object_masses.json +3994ff7fd8942040dac2a6fdc968526c452d06e8af174db8f2223708f21f755f reference/artifacts/object_transforms.json +8066c4184ce87c224868f823f028c10485f5953ada1b6ffbc48892e0fccff529 reference/artifacts/poses.npy +bb680f089c3ebc55438d199800709739b46839d8e7199bb3961f3a3a221082c8 reference/artifacts/reference_scores.json +24406bb6a7fc85d9b6390009c6e445b8cc07f2d661381873983817bf271d305c reference/artifacts/rubrics/RacingCar/openai_gpt-5-4_v0.json +2344c6a9fc2c0f2469c83cb3013c89c3f4d8307d9767431c5718a63a1eff32bd reference/artifacts/trajectory.yaml +3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea reference/ref.png +e372aca1ed36cc093cd3cf8f164d4da581d0aa5762d6ea4e58778815e89aa067 reference/unity_groundtruth.mp4 diff --git a/cases/RacingCar/prompt_third/reference/ref.png b/cases/RacingCar/prompt_third/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..0abb8416488e6715d85b0b578b53f983e99085d8 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3f2b8ae1927f72d4ec07bdecbcb5685f9efe0170e7d95b1bd764ae297549c0ea +size 921081 diff --git a/cases/RacingCar/prompt_third/reference/unity_groundtruth.mp4 b/cases/RacingCar/prompt_third/reference/unity_groundtruth.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..b9831e9428c28c70739e39ebfea9d210d2e8bda1 --- /dev/null +++ b/cases/RacingCar/prompt_third/reference/unity_groundtruth.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e372aca1ed36cc093cd3cf8f164d4da581d0aa5762d6ea4e58778815e89aa067 +size 4904681 diff --git a/cases/SunRisesAndSets/lighting/reference/artifacts/actions.txt b/cases/SunRisesAndSets/lighting/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..8008442f33051c4dcb1665625316ed54934a34cf --- /dev/null +++ b/cases/SunRisesAndSets/lighting/reference/artifacts/actions.txt @@ -0,0 +1,4 @@ +[ + {"op": "setview", "key": "first", "note": "first-person at standing eye height (~1.6 m); no body, hands or held items in frame"}, + {"op": "hold", "key": "ArrowLeft", "ms": 10000, "note": "walk counter-clockwise around the round dining table at a constant ~2 m radius, one full loop over the clip, table kept centred in view; the sun stays fixed (fixed-sun, walking-orbit regime)"} +] diff --git a/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json b/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json new file mode 100644 index 0000000000000000000000000000000000000000..b545ada081ee41e56922f181477a0d8a16851ea7 --- /dev/null +++ b/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json @@ -0,0 +1,168 @@ +{ + "case_id": "SunRisesAndSets/lighting", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "note": "How each evaluated world model realised the canonical action script (reference/artifacts/actions.txt) and the case prompt. seed_image is the bundled reference/ref.png; text_prompt is case.yaml `prompt`. Recorded from the paper's generation runs (Modal volume WMEval-lighting-repro, inputs/actions/).", + "models": { + "project_genie": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Google Project Genie (hosted)", + "entry": "manual web session", + "action_channel": "text + interactive action", + "orbit_action": "manual left orbit following the prompt", + "orbit_action_meaning": "operator-driven; clips post-trimmed to the first 40 s", + "cli": {}, + "uses_text_prompt": true, + "output": "video.mp4", + "note": "Not scriptable: generated manually and downloaded, then clipped to 40 s." + }, + "lingbot_world": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "robbyant/lingbot-world-base-cam", + "entry": "generate.py (torchrun, 8xH100)", + "action_channel": "action_string DSL + camera pose", + "orbit_action": "l-160", + "orbit_action_meaning": "turn left for 160 frames (one left sweep)", + "cli": { + "--task": "i2v-A14B", + "--size": "480*832", + "--frame_num": "161", + "--action_string": "l-160", + "--action_path": "examples/00", + "--allow_act2cam": "(flag)", + "--sample_steps": "20", + "--base_seed": "" + }, + "uses_text_prompt": true, + "output": "video.mp4" + }, + "matrix_game_2": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Skywork/Matrix-Game-2.0 (base_distilled_model)", + "entry": "inference.py (1xH100)", + "action_channel": "keyboard/camera action tokens", + "orbit_action": "mode=universal default camera schedule", + "orbit_action_meaning": "universal-scene action schedule; no explicit turn string exposed", + "cli": { + "--config_path": "configs/inference_yaml/inference_universal.yaml", + "--num_output_frames": "150", + "--seed": "" + }, + "uses_text_prompt": false, + "output": "demo.mp4" + }, + "matrix_game_3": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Skywork/Matrix-Game-3.0", + "entry": "generate.py (torchrun, 8xH100)", + "action_channel": "action tokens + text", + "orbit_action": "num_iterations=12 rollout", + "orbit_action_meaning": "12 autoregressive chunks at 704x1280", + "cli": { + "--size": "704*1280", + "--num_iterations": "12", + "--num_inference_steps": "3", + "--vae_type": "mg_lightvae", + "--seed": "" + }, + "uses_text_prompt": true, + "output": ".mp4" + }, + "hy_worldplay": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "tencent/HY-WorldPlay (ar_distilled_action_model) + HunyuanVideo-1.5", + "entry": "hyvideo/generate.py (torchrun, 8xH100)", + "action_channel": "camera pose DSL", + "orbit_action": "left-31", + "orbit_action_meaning": "yaw left across 31 latents; video_length=125=31*4+1 -> one left sweep", + "cli": { + "--resolution": "480p", + "--aspect_ratio": "16:9", + "--video_length": "125", + "--pose": "left-31", + "--few_step": "true", + "--num_inference_steps": "4", + "--model_type": "ar", + "--sr": "false", + "--seed": "" + }, + "uses_text_prompt": true, + "output": "gen.mp4" + }, + "waypoint15": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Overworld/Waypoint-1.5-1B (+ Overworld-Models/taehv1_5)", + "entry": "world_engine WorldEngine python API (1xH100)", + "action_channel": "per-frame keyboard/mouse CtrlInput", + "orbit_action": "CtrlInput(mouse=[-0.15, 0.0]) x 90 steps", + "orbit_action_meaning": "continuous first-person left yaw; 4 frames emitted per step -> 360 frames + 1 seed frame = 364 @ 60fps", + "cli": { + "quant": "None (bf16)", + "n_steps": "90", + "seed_frame": "1280x720 RGB, stacked x4" + }, + "uses_text_prompt": false, + "note": "Waypoint-1.5 has NO text-prompt channel (prompt_conditioning: null); the scene is set purely by the seed image.", + "output": "video.mp4" + } + } +} diff --git a/cases/SunRisesAndSets/lighting/reference/checksums.sha256 b/cases/SunRisesAndSets/lighting/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..a99493f184793fbe558ea8f7df5d38a3838b1163 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0000000000000000000000000000000000000000..15f2953fdf7007076c9b85e9f28a9ac8009c0209 --- /dev/null +++ b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/actions.txt @@ -0,0 +1,7 @@ +# lighting.camera.look_at_orbit_v2 -- generated action trajectory. +# Provenance: trajectory.yaml (semantic SHA-256: 6649252e0317aaf1b696eee475748781f28714a59432a2fb0778272bcf2dc8e5) +# Alignment: reconstructed; 600 steps; channels: orbit_phase_rate_deg_s +# start_s end_s orbit_phase_rate_deg_s +0.0 10.0 36.0 + +# Project Genie browser adapter: not compiled; camera pose records are not browser actions. diff --git a/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/calibration.json b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/calibration.json new file mode 100644 index 0000000000000000000000000000000000000000..3f7a6082850ac04e00db57052e2030b2a554cc6e --- /dev/null +++ b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/calibration.json @@ -0,0 +1,75 @@ +{ + "scene": "Assets/Scenes/SampleScene.unity", + "unityVersion": "6000.3.8f1", + "tableSelection": "GameObject exact name Table23; aggregate Renderer.bounds", + "targetSelection": "table mesh bounds centre x/z and max.y", + "floorSelection": "GameObject Plane transform.position.y", + "tableBoundsCenter": { + "x": 0.0, + "y": 0.6367848515510559, + "z": -8.940696716308594e-7 + }, + "tableBoundsSize": { + "x": 1.760000467300415, + "y": 1.273569941520691, + "z": 1.7600003480911255 + }, + "originUnity": { + "x": 0.0, + "y": 0.0, + "z": -8.940696716308594e-7 + }, + "targetUnity": { + "x": 0.0, + "y": 1.2735698223114014, + "z": -8.940696716308594e-7 + }, + "radiusM": 2.0, + "eyeHeightM": 1.600000023841858, + "durationSec": 10.0, + "verticalFovDeg": 60.0, + "width": 1024, + "height": 1024, + "fps": 12, + "localToUnity": "diag(1,1,-1) plus originUnity; local RH +Y up; initial local +Z", + "lights": [ + { + "name": "Directional Light", + "type": "Directional", + "position": { + "x": 0.0, + "y": 3.0, + "z": 0.0 + }, + "euler": { + "x": 63.399993896484378, + "y": 330.0, + "z": 0.0000019067700804953348 + }, + "forward": { + "x": -0.22387953102588654, + "y": -0.8941541910171509, + "z": 0.38777080178260805 + }, + "color": { + "r": 1.0, + "g": 1.0, + "b": 1.0, + "a": 1.0 + }, + "intensity": 2.0, + "colorTemperature": 5000.0, + "enabled": true, + "useColorTemperature": true + } + ], + "disabledBehaviours": [ + "CameraOrbitAgent", + "DayAndNight", + "KeyboardCameraController", + "Unity.MLAgents.DecisionRequester", + "Unity.MLAgents.Policies.BehaviorParameters", + "Unity.MLAgents.Sensors.CameraSensorComponent", + "UnityEngine.Rendering.Volume" + ] +} \ No newline at end of file diff --git a/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/compile_manifest.json b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/compile_manifest.json new file mode 100644 index 0000000000000000000000000000000000000000..ca5c0f7b01f490815e339198d1b5af5e973ab0b2 --- /dev/null +++ b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/compile_manifest.json @@ -0,0 +1,28 @@ +{ + "action_npy": "action.npy", + "action_npy_sha256": "58449a0ac721a3dbb1489921c31709ddf04e3fe6010196ba1aa83c9cd96baf80", + "action_npz": "action.npz", + "action_npz_sha256": "7888d0752e0d2c7f11352189a52bd305178a08f27291cdf62eddcd89470904f2", + "actions_txt": "actions.txt", + "actions_txt_sha256": "76bbdbd2d96ea7ba8e32ada4c63da678b4d8d1ef0e21eed740eb0ae35897c25f", + "alignment_status": "reconstructed", + "camera_pose_samples": "actions.jsonl", + "camera_pose_samples_sha256": "363cdb74bd333b673e7836877f4966f56ffa37a50a1c30c7760110c972512149", + "channel_names": [ + "orbit_phase_rate_deg_s" + ], + "control_interval_convention": "half_open", + "coordinates": "right_handed_y_up_opencv_c2w", + "kind": "camera_look_at_orbit", + "pose_count": 601, + "pose_endpoint_included": true, + "poses": "poses.npy", + "poses_sha256": "b7ca2b4c561cae5617a6b3ce91ebf645a3eaacf831122b3a4f7502b43cf3d33d", + "project_genie_status": "not_compiled", + "schema_version": 1, + "semantic_sha256": "6649252e0317aaf1b696eee475748781f28714a59432a2fb0778272bcf2dc8e5", + "source": "../../../../../../tmp/wmeval-lighting-orbit/eval_sets/wmeval_lite_v1/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/trajectory.yaml", + "step_count": 600, + "target": "camera", + "trajectory_id": "lighting.camera.look_at_orbit_v2" +} diff --git a/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/evaluator_assets.lock.json b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/evaluator_assets.lock.json new file mode 100644 index 0000000000000000000000000000000000000000..aafe8360b8f28822c3958f425ca522d3b6471b58 --- /dev/null +++ b/cases/SunRisesAndSets/lighting_orbit_v2/reference/artifacts/evaluator_assets.lock.json @@ -0,0 +1,22 @@ +{ + "schema_version": 1, + "assets": { + "grounding_dino": { + "model_id": "IDEA-Research/grounding-dino-tiny", + "revision": 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reference/artifacts/actions.jsonl +76bbdbd2d96ea7ba8e32ada4c63da678b4d8d1ef0e21eed740eb0ae35897c25f reference/artifacts/actions.txt +a6b1c115db28eb560a4a97912989b32b55cb0e27dede2265f6b75fce944907d0 reference/artifacts/calibration.json +05000d7341528bd0ed81a50c4cc492f811056d9f8b6d506266fb77001571d40a reference/artifacts/compile_manifest.json +20b833c7c0b000f2c97a0270d810e27eb38ba5c8cdc3b1be828e89ae7790170f reference/artifacts/evaluator_assets.lock.json +9863596b07da04d6ae28ad29424684aa31a12cf20a2a8c7429b5e5e32bd2d704 reference/artifacts/frames.jsonl +d7e1e879f11b985669c75f2667ee0bbfcd91a3cb845a75074aa013933c567ad9 reference/artifacts/intrinsics.npy +b7ca2b4c561cae5617a6b3ce91ebf645a3eaacf831122b3a4f7502b43cf3d33d reference/artifacts/poses.npy +fb56899f069b842af553094450f59bb593fadaf7aa0ac5980d4191508413c60a reference/artifacts/scene_dependencies.json +6ba3519cb8bb9534998dbe94f01c42a6624399005391780db9dd0e80e98303e2 reference/artifacts/table_cell.json 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file mode 100644 index 0000000000000000000000000000000000000000..852c8ce19592ac4204a13fc4e3c3b0b50518174d --- /dev/null +++ b/cases/SunRisesAndSets/lighting_orbit_v2/reference/unity_orbit.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:a8766eb32e271df40be6d6ddab9103304f54c71e9464b27abee3891c33370015 +size 4925826 diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npy b/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..c0f12fd2ca3e3c0bc2579ec71400014303d2badc --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:98a9c58f1d9d6b92c42641d7e6b875244f5461f298f67cdde4caa738721a424e +size 928 diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npz b/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..8f1eaaed53c292eac940e3fe91093ef371c2e7b0 --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:fc89715ec9b6cb4eec65ccd52831d625a90b5bd64a4f66859cfeb5cd8085cc4c +size 1553 diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.jsonl b/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..6f1065e33508f3c121f49a4fb16b4dc3a9c649e0 --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.jsonl @@ -0,0 +1 @@ +{"keys": ["ArrowLeft"], "ms": 10000, "op": "hold", "target_yaw_deg": -360.0} diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.txt b/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..e6e58b678c5972ebced481841e85b903ccdd54e0 --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/actions.txt @@ -0,0 +1,8 @@ +# table7.camera.360_in_v1 -- generated action trajectory. +# Provenance: camera_360_in.yaml (semantic SHA-256: 16008bd3e1bd2b5497b424eab147eda7a7858572ce3d1afb5ccb62d509e9d6c4) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 10.0 -36.0 + +# Project Genie browser actions: +{"keys": ["ArrowLeft"], "ms": 10000, "op": "hold", "target_yaw_deg": -360.0} diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/intrinsics.npy b/cases/WanderingGarden/scene_360_in/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..bbcf4e0b4ed93705aee5bb0ae311331adbe864ad --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version 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"trajectory.yaml": "16008bd3e1bd2b5497b424eab147eda7a7858572ce3d1afb5ccb62d509e9d6c4" + }, + "table_cell": "table7/WanderingGarden/360_in", + "trajectory_id": "table7.camera.360_in_v1" +} diff --git a/cases/WanderingGarden/scene_360_in/reference/artifacts/trajectory.yaml b/cases/WanderingGarden/scene_360_in/reference/artifacts/trajectory.yaml new file mode 100644 index 0000000000000000000000000000000000000000..9b7744d9ecaf4f796b234c66b53495758c59618b --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/artifacts/trajectory.yaml @@ -0,0 +1,21 @@ +schema_version: 1 +trajectory_id: table7.camera.360_in_v1 +description: Nominal counter-clockwise full-yaw proxy for the paper's inward-facing condition. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 10.0, values: {yaw_rate_deg_s: -36.0}} +paper_alignment: + status: reconstructed + matched: [full_360_degree_camera_rotation, inward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes inward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/WanderingGarden/scene_360_in/reference/checksums.sha256 b/cases/WanderingGarden/scene_360_in/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..bc3da5b8da6da1b6ab3f3c04232f72b7297ec3cc --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/checksums.sha256 @@ -0,0 +1,11 @@ +98a9c58f1d9d6b92c42641d7e6b875244f5461f298f67cdde4caa738721a424e reference/artifacts/action.npy +fc89715ec9b6cb4eec65ccd52831d625a90b5bd64a4f66859cfeb5cd8085cc4c reference/artifacts/action.npz +475464fc6c6588c87a99495e3ddd9c49846b6d07b471871f796f794e3f6546e5 reference/artifacts/actions.jsonl +cd7ae0afab76799bff60f9015bfb07d5d90077fa4daefb9a46c4b82a1d630ce9 reference/artifacts/actions.txt +b30a63f7ee1c97adcc919c4be5eac8df36ac40f7640410413b1da3c1330282fa reference/artifacts/intrinsics.npy +dd677ad7fb29fe4724ed6ad04c16f94a4c14e3322da3c919852c779d0dfd9b77 reference/artifacts/object_transforms.json +ebdee088a7f899502be470ca48fb475e5a401a38cfcd61ceb41d3c5bbd905fb6 reference/artifacts/poses.npy +08ae36e1b7c2418b8b414a7eb62853eb34dbc24d49eceda767b09f5d29528bab reference/artifacts/table_cell.json +16008bd3e1bd2b5497b424eab147eda7a7858572ce3d1afb5ccb62d509e9d6c4 reference/artifacts/trajectory.yaml +195a2384dac3aad0aea93b508d381b8162b37b3e7a60b8e68a047698593ae742 reference/ref.png +5cd55d75ade860b207244aca2ec739bd00875ba9f4207b2e3d25d9e7f492cacf reference/reference.mp4 diff --git a/cases/WanderingGarden/scene_360_in/reference/ref.png b/cases/WanderingGarden/scene_360_in/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..90a2b96affed5485363248265ae432f9c4aa5005 --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:195a2384dac3aad0aea93b508d381b8162b37b3e7a60b8e68a047698593ae742 +size 1582085 diff --git a/cases/WanderingGarden/scene_360_in/reference/reference.mp4 b/cases/WanderingGarden/scene_360_in/reference/reference.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..f19afd1e5c909222757bf30ce26f7c42012e808c --- /dev/null +++ b/cases/WanderingGarden/scene_360_in/reference/reference.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:5cd55d75ade860b207244aca2ec739bd00875ba9f4207b2e3d25d9e7f492cacf +size 8759714 diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npy b/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..8798a3b24eb9f78f5158c973b343fad5ca80f8cb --- /dev/null +++ b/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:242e5eac182551cc84ce4deb884905055a82aa62054c4b8523444fd1d35a4822 +size 928 diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npz b/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..bb4103314405fbedc2323fce157a2fd60bf472b0 --- /dev/null +++ b/cases/WanderingGarden/scene_360_out/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:3ddcda933deb456dbdc4ba913a4482a380b6af669534a1267d3be449489d534d +size 1558 diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.jsonl b/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..44d5b4904887601489fb1f5d5782249ac30bdcd3 --- /dev/null +++ b/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.jsonl @@ -0,0 +1 @@ +{"keys": ["ArrowRight"], "ms": 10000, "op": "hold", "target_yaw_deg": 360.0} diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.txt b/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..ff19e91ba197f0397bb83d57a23339060e7e9fe6 --- /dev/null +++ b/cases/WanderingGarden/scene_360_out/reference/artifacts/actions.txt @@ -0,0 +1,8 @@ +# table7.camera.360_out_v1 -- generated action trajectory. +# Provenance: camera_360_out.yaml (semantic SHA-256: de3cce86bcf6f0ce53780a43057eaddae92d32fcc8df443a00de5ec28eb07d97) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 10.0 36.0 + +# Project Genie browser actions: +{"keys": ["ArrowRight"], "ms": 10000, "op": "hold", "target_yaw_deg": 360.0} diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/intrinsics.npy b/cases/WanderingGarden/scene_360_out/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..bbcf4e0b4ed93705aee5bb0ae311331adbe864ad --- /dev/null +++ b/cases/WanderingGarden/scene_360_out/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b30a63f7ee1c97adcc919c4be5eac8df36ac40f7640410413b1da3c1330282fa +size 4928 diff --git a/cases/WanderingGarden/scene_360_out/reference/artifacts/object_transforms.json b/cases/WanderingGarden/scene_360_out/reference/artifacts/object_transforms.json new file mode 100644 index 0000000000000000000000000000000000000000..37f84363229f17aadb8dc8612981c29f73bff35d 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translation. 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+size 6453623 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npy b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..2211e9b91c679a2e844b7b1e79010a0118a626e5 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:55171151a4042416c87105acbfe5f1017aa9e5340a6f73320bad60f84b1da6dc +size 928 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npz b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..1145453953fcc8e4c6fbb355d6842bdd5ce43d3f --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:dbcc9bbb0473106a99b4c3907860d25cf7b5ca75d48d027053672649dff6eb4b +size 1557 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.jsonl b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..de550e084831ef9b829588ed14d50c801d032fab --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.jsonl @@ -0,0 +1,2 @@ +{"keys": ["ArrowLeft"], "ms": 1250, "op": "hold", "target_yaw_deg": -45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.txt b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..054bde7c9929a52fa4bbd69c01510e5e43ebcaec --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/actions.txt @@ -0,0 +1,10 @@ +# table7.camera.perturb_in_v1 -- generated action trajectory. +# Provenance: camera_perturb_in.yaml (semantic SHA-256: ae53bd32c4359f1a1471b5dfa584ad4c27d41171eba55541e2b52e5e3993a1cf) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 1.25 -36.0 +1.25 10.0 0.0 + +# Project Genie browser actions: +{"keys": ["ArrowLeft"], "ms": 1250, "op": "hold", "target_yaw_deg": -45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/intrinsics.npy b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..bbcf4e0b4ed93705aee5bb0ae311331adbe864ad --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b30a63f7ee1c97adcc919c4be5eac8df36ac40f7640410413b1da3c1330282fa +size 4928 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/object_transforms.json b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/object_transforms.json new file mode 100644 index 0000000000000000000000000000000000000000..ea2e074f7e79f150b79974f4103652fa2481988b --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/object_transforms.json @@ -0,0 +1,4545 @@ +{ + "objects": { + "Main tree": { + "frames": [ + 0, + 1, + 2, + 3, + 4, + 5, + 6, + 7, + 8, + 9, + 10, + 11, + 12, + 13, + 14, + 15, + 16, + 17, + 18, + 19, + 20, + 21, + 22, + 23, + 24, + 25, + 26, + 27, + 28, + 29, + 30, + 31, + 32, + 33, + 34, + 35, + 36, + 37, + 38, + 39, + 40, + 41, + 42, + 43, + 44, + 45, + 46, + 47, + 48, + 49, + 50, + 51, + 52, + 53, + 54, + 55, + 56, + 57, + 58, + 59, + 60, + 61, + 62, + 63, + 64, + 65, + 66, + 67, + 68, + 69, + 70, + 71, + 72, + 73, + 74, + 75, + 76, + 77, + 78, + 79, + 80, + 81, + 82, + 83, + 84, + 85, + 86, + 87, + 88, + 89, + 90, + 91, + 92, + 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"ae53bd32c4359f1a1471b5dfa584ad4c27d41171eba55541e2b52e5e3993a1cf" + }, + "table_cell": "table7/WanderingGarden/perturb_in", + "trajectory_id": "table7.camera.perturb_in_v1" +} diff --git a/cases/WanderingGarden/scene_perturb_in/reference/artifacts/trajectory.yaml b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/trajectory.yaml new file mode 100644 index 0000000000000000000000000000000000000000..a9c2be88686e0f934a133ccb033f0d66d364fab8 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/artifacts/trajectory.yaml @@ -0,0 +1,22 @@ +schema_version: 1 +trajectory_id: table7.camera.perturb_in_v1 +description: Nominal counter-clockwise 45-degree yaw proxy for the paper's inward-facing condition, then hold. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 1.25, values: {yaw_rate_deg_s: -36.0}} + - {start_sec: 1.25, end_sec: 10.0, values: {yaw_rate_deg_s: 0.0}} +paper_alignment: + status: reconstructed + matched: [camera_perturbation, nominal_45_degrees, inward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes inward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/WanderingGarden/scene_perturb_in/reference/checksums.sha256 b/cases/WanderingGarden/scene_perturb_in/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..6c536aab8111ec1493d41e6ee1bbb90e24634b15 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/checksums.sha256 @@ -0,0 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+cf80b7109ccae26d76f06f856741f8f5cebcb1cf90be7225625ec57bec7ded72 reference/reference.mp4 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/ref.png b/cases/WanderingGarden/scene_perturb_in/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..90a2b96affed5485363248265ae432f9c4aa5005 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:195a2384dac3aad0aea93b508d381b8162b37b3e7a60b8e68a047698593ae742 +size 1582085 diff --git a/cases/WanderingGarden/scene_perturb_in/reference/reference.mp4 b/cases/WanderingGarden/scene_perturb_in/reference/reference.mp4 new file mode 100644 index 0000000000000000000000000000000000000000..193aa3c2ef381cda7d71815fff67c7c52090ed25 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_in/reference/reference.mp4 @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:cf80b7109ccae26d76f06f856741f8f5cebcb1cf90be7225625ec57bec7ded72 +size 2379112 diff --git a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npy b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npy new file mode 100644 index 0000000000000000000000000000000000000000..64bfd555a0cbf5760755b54f5c6c65dae964c0d2 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:609b00050865df5ff6f5f4c5eb4d67f497e8a3c47673ff30b4b9a053ade8ae5a +size 928 diff --git a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npz b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npz new file mode 100644 index 0000000000000000000000000000000000000000..03989693a9e39d3678bd9c2f42dd10f9debe9a0b --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/action.npz @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:f9d8d2db204f8f50ab391b3aa4d1acdd8f43676e159780866073a98f952a9012 +size 1558 diff --git a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.jsonl b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.jsonl new file mode 100644 index 0000000000000000000000000000000000000000..cb966160697781be73ea32d5a50eb82f0ae8971b --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.jsonl @@ -0,0 +1,2 @@ +{"keys": ["ArrowRight"], "ms": 1250, "op": "hold", "target_yaw_deg": 45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.txt b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..ec26e338d528541e98d3fe3a460f5ea066e41738 --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/actions.txt @@ -0,0 +1,10 @@ +# table7.camera.perturb_out_v1 -- generated action trajectory. +# Provenance: camera_perturb_out.yaml (semantic SHA-256: 8f6169a0bd84b9f2ebadb8877086a985d8f6aa5affd0747dd974a96707ccee2f) +# Alignment: reconstructed; 200 steps; channels: yaw_rate_deg_s +# start_s end_s yaw_rate_deg_s +0.0 1.25 36.0 +1.25 10.0 0.0 + +# Project Genie browser actions: +{"keys": ["ArrowRight"], "ms": 1250, "op": "hold", "target_yaw_deg": 45.0} +{"ms": 8750, "op": "wait"} diff --git a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/intrinsics.npy b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/intrinsics.npy new file mode 100644 index 0000000000000000000000000000000000000000..bbcf4e0b4ed93705aee5bb0ae311331adbe864ad --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/intrinsics.npy @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:b30a63f7ee1c97adcc919c4be5eac8df36ac40f7640410413b1da3c1330282fa +size 4928 diff --git 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a/cases/WanderingGarden/scene_perturb_out/reference/artifacts/trajectory.yaml b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/trajectory.yaml new file mode 100644 index 0000000000000000000000000000000000000000..1855c90ed05da6db7093442d63b386550f8fc1cc --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/artifacts/trajectory.yaml @@ -0,0 +1,22 @@ +schema_version: 1 +trajectory_id: table7.camera.perturb_out_v1 +description: Nominal clockwise 45-degree yaw proxy for the paper's outward-facing condition, then hold. +duration_sec: 10.0 +control_hz: 20 +channels: + yaw_rate_deg_s: {kind: continuous, min: -360.0, max: 360.0, unit: deg_per_sec} +segments: + - {start_sec: 0.0, end_sec: 1.25, values: {yaw_rate_deg_s: 36.0}} + - {start_sec: 1.25, end_sec: 10.0, values: {yaw_rate_deg_s: 0.0}} +paper_alignment: + status: reconstructed + matched: [camera_perturbation, nominal_45_degrees, outward_label, five_generations] + missing: The paper does not publish rate/duration or establish that yaw sign encodes outward orientation; an orientation-specific first frame is a separate case requirement. + source: ../../../../_arxiv__WorldModel_Eval/text/3_benchmark_v1.tex +adapters: + unity: {status: needs_scene_calibration, channel: yaw_rate_deg_s} + project_genie: + status: nominal + nominal_yaw_rate_deg_s: 36.0 + key_rules: + - {channel: yaw_rate_deg_s, threshold: 1.0, positive_key: ArrowRight, negative_key: ArrowLeft} diff --git a/cases/WanderingGarden/scene_perturb_out/reference/checksums.sha256 b/cases/WanderingGarden/scene_perturb_out/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..8243f630b31b28eb88fcf62029edb754b6edae0c --- /dev/null +++ b/cases/WanderingGarden/scene_perturb_out/reference/checksums.sha256 @@ -0,0 +1,11 @@ +609b00050865df5ff6f5f4c5eb4d67f497e8a3c47673ff30b4b9a053ade8ae5a reference/artifacts/action.npy +f9d8d2db204f8f50ab391b3aa4d1acdd8f43676e159780866073a98f952a9012 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b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/artifacts/actions.txt new file mode 100644 index 0000000000000000000000000000000000000000..8008442f33051c4dcb1665625316ed54934a34cf --- /dev/null +++ b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/artifacts/actions.txt @@ -0,0 +1,4 @@ +[ + {"op": "setview", "key": "first", "note": "first-person at standing eye height (~1.6 m); no body, hands or held items in frame"}, + {"op": "hold", "key": "ArrowLeft", "ms": 10000, "note": "walk counter-clockwise around the round dining table at a constant ~2 m radius, one full loop over the clip, table kept centred in view; the sun stays fixed (fixed-sun, walking-orbit regime)"} +] diff --git a/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json new file mode 100644 index 0000000000000000000000000000000000000000..b545ada081ee41e56922f181477a0d8a16851ea7 --- /dev/null +++ b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/artifacts/actions_per_model.json @@ -0,0 +1,168 @@ +{ + "case_id": "SunRisesAndSets/lighting", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "note": "How each evaluated world model realised the canonical action script (reference/artifacts/actions.txt) and the case prompt. seed_image is the bundled reference/ref.png; text_prompt is case.yaml `prompt`. Recorded from the paper's generation runs (Modal volume WMEval-lighting-repro, inputs/actions/).", + "models": { + "project_genie": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Google Project Genie (hosted)", + "entry": "manual web session", + "action_channel": "text + interactive action", + "orbit_action": "manual left orbit following the prompt", + "orbit_action_meaning": "operator-driven; clips post-trimmed to the first 40 s", + "cli": {}, + "uses_text_prompt": true, + "output": "video.mp4", + "note": "Not scriptable: generated manually and downloaded, then clipped to 40 s." + }, + "lingbot_world": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "robbyant/lingbot-world-base-cam", + "entry": "generate.py (torchrun, 8xH100)", + "action_channel": "action_string DSL + camera pose", + "orbit_action": "l-160", + "orbit_action_meaning": "turn left for 160 frames (one left sweep)", + "cli": { + "--task": "i2v-A14B", + "--size": "480*832", + "--frame_num": "161", + "--action_string": "l-160", + "--action_path": "examples/00", + "--allow_act2cam": "(flag)", + "--sample_steps": "20", + "--base_seed": "" + }, + "uses_text_prompt": true, + "output": "video.mp4" + }, + "matrix_game_2": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Skywork/Matrix-Game-2.0 (base_distilled_model)", + "entry": "inference.py (1xH100)", + "action_channel": "keyboard/camera action tokens", + "orbit_action": "mode=universal default camera schedule", + "orbit_action_meaning": "universal-scene action schedule; no explicit turn string exposed", + "cli": { + "--config_path": "configs/inference_yaml/inference_universal.yaml", + "--num_output_frames": "150", + "--seed": "" + }, + "uses_text_prompt": false, + "output": "demo.mp4" + }, + "matrix_game_3": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Skywork/Matrix-Game-3.0", + "entry": "generate.py (torchrun, 8xH100)", + "action_channel": "action tokens + text", + "orbit_action": "num_iterations=12 rollout", + "orbit_action_meaning": "12 autoregressive chunks at 704x1280", + "cli": { + "--size": "704*1280", + "--num_iterations": "12", + "--num_inference_steps": "3", + "--vae_type": "mg_lightvae", + "--seed": "" + }, + "uses_text_prompt": true, + "output": ".mp4" + }, + "hy_worldplay": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "tencent/HY-WorldPlay (ar_distilled_action_model) + HunyuanVideo-1.5", + "entry": "hyvideo/generate.py (torchrun, 8xH100)", + "action_channel": "camera pose DSL", + "orbit_action": "left-31", + "orbit_action_meaning": "yaw left across 31 latents; video_length=125=31*4+1 -> one left sweep", + "cli": { + "--resolution": "480p", + "--aspect_ratio": "16:9", + "--video_length": "125", + "--pose": "left-31", + "--few_step": "true", + "--num_inference_steps": "4", + "--model_type": "ar", + "--sr": "false", + "--seed": "" + }, + "uses_text_prompt": true, + "output": "gen.mp4" + }, + "waypoint15": { + "scene": "SunRisesAndSets", + "regime": "first-person, fixed sun, walking orbit (single left turn)", + "seed_image": "reference/ref.png", + "text_prompt_file": "case.yaml:prompt", + "seeds": [ + 42, + 1, + 2, + 3, + 4 + ], + "model": "Overworld/Waypoint-1.5-1B (+ Overworld-Models/taehv1_5)", + "entry": "world_engine WorldEngine python API (1xH100)", + "action_channel": "per-frame keyboard/mouse CtrlInput", + "orbit_action": "CtrlInput(mouse=[-0.15, 0.0]) x 90 steps", + "orbit_action_meaning": "continuous first-person left yaw; 4 frames emitted per step -> 360 frames + 1 seed frame = 364 @ 60fps", + "cli": { + "quant": "None (bf16)", + "n_steps": "90", + "seed_frame": "1280x720 RGB, stacked x4" + }, + "uses_text_prompt": false, + "note": "Waypoint-1.5 has NO text-prompt channel (prompt_conditioning: null); the scene is set purely by the seed image.", + "output": "video.mp4" + } + } +} diff --git a/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/checksums.sha256 b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/checksums.sha256 new file mode 100644 index 0000000000000000000000000000000000000000..a99493f184793fbe558ea8f7df5d38a3838b1163 --- /dev/null +++ b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/checksums.sha256 @@ -0,0 +1,3 @@ +be72b78fc20b5438111c955e001ede344cedc958c6ad30f498c29ac4da96baa5 reference/artifacts/actions.txt +d961cd5a53cbf4701ea2620a9f532b856a907d94f55cc5dab2cb2e3b8c4f064f reference/artifacts/actions_per_model.json +e02cdc2898a64f2e6e02182224f9487a9fb70cae56ed12103842bdea595e7d1d reference/ref.png diff --git a/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/ref.png b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/ref.png new file mode 100644 index 0000000000000000000000000000000000000000..31cad6fd78d7421a59dd1c63c82e18144a8faa9d --- /dev/null +++ b/lighting_paper_native/cases/SunRisesAndSets/lighting/reference/ref.png @@ -0,0 +1,3 @@ +version https://git-lfs.github.com/spec/v1 +oid sha256:e02cdc2898a64f2e6e02182224f9487a9fb70cae56ed12103842bdea595e7d1d +size 711676