Update minor-revision RGB results and 1107 experiment figures
Browse filesPublish the validated 50-case native RGB baseline comparison, current candidate losses and aggregates, updated example figure, and 1107 experiment figures/tables. Preserve plan annotations and 12 agent-ablation videos.
- MINOR_REVISION.md +25 -7
- README.md +1 -1
- agenthoi_minor_revision.zip +2 -2
MINOR_REVISION.md
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@@ -12,9 +12,9 @@ Implicit Representation Alignment**.
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| Directory | Contents | Paper reference |
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| `plan_evaluation/` | Plans under single-agent, w/o clipping refiner and full settings; blinded Qwen3-VL annotations; metric outputs and judge scripts | Table 3; supplementary D |
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| `agent_ablation/` | Keyboard, cream tube, razor and mask inputs, stage outputs and generated videos for full, w/o Perception and w/o Interaction | Fig.
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| `motion_text_matching/` | Candidate descriptions, per-case matching results, aggregate results and example RGB/motion frames | Table 4; supplementary Fig. 4 |
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| `paper_figures/`, `paper_tables/` |
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The fifth and sixth ablation examples from the initial experiment export are
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excluded. Figures use the final captions and layouts, including the cream-tube
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full-control, no-perception and no-interaction generations.
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The keyboard and mask cases illustrate incorrect object categories or
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unrequested wearing after removing an agent. Fig.
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the refiner inserts alignment with the receiving hand before transfer.
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The cream-tube video variants show smaller differences than the failure cases.
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All four candidates receive the same Gaussian noise at noise level 0.5
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(timestep 500); the candidate with the lowest flow-matching loss is selected.
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`M_motion` has 84% top-1 accuracy
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inference.
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`results/all_cases_comparison.csv` stores
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hashes. Fields such as `input` and `source_video` preserve the original
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experiment's provenance and are not portable file locations.
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Example RGB and motion frames are bundled. Full encoded motion latents,
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`SHA256SUMS` records every released file except itself. `PROVENANCE.json`
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records the source-archive hashes and packaging transformations.
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The existing dataset's benchmark images and GT videos remain the source inputs.
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| Directory | Contents | Paper reference |
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| `plan_evaluation/` | Plans under single-agent, w/o clipping refiner and full settings; blinded Qwen3-VL annotations; metric outputs and judge scripts | Table 3; supplementary D |
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| `agent_ablation/` | Keyboard, cream tube, razor and mask inputs, stage outputs and generated videos for full, w/o Perception and w/o Interaction | Fig. 8–9; supplementary Fig. 2–3 |
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| `motion_text_matching/` | Candidate descriptions, per-case matching results, aggregate results and example RGB/motion frames | Table 4; supplementary Fig. 4 |
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| `paper_figures/`, `paper_tables/` | 1107 experiment figures, captions and table sources | Same numbering as the revised paper |
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The fifth and sixth ablation examples from the initial experiment export are
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excluded. Figures use the final captions and layouts, including the cream-tube
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full-control, no-perception and no-interaction generations.
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The keyboard and mask cases illustrate incorrect object categories or
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unrequested wearing after removing an agent. Fig. 9 uses the cream tube:
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the refiner inserts alignment with the receiving hand before transfer.
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The cream-tube video variants show smaller differences than the failure cases.
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All four candidates receive the same Gaussian noise at noise level 0.5
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(timestep 500); the candidate with the lowest flow-matching loss is selected.
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`M_motion` on skeleton-and-mask inputs has 84% top-1 accuracy and mean loss gap
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+5.493168222407501e-4. The base Wan2.1-T2V-1.3B on RGB inputs has 14% accuracy
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and mean loss gap -6.11583391825328e-6; chance is 25%. The model is used for feature alignment during training and removed at
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inference.
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`results/all_cases_comparison.csv` stores the current RGB-baseline comparison;
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`results/candidate_losses.json` contains all four measured candidate losses;
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`results/summary.json` stores the recomputed aggregates; `data/candidates.json` retains descriptions and encoded-input
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hashes. Fields such as `input` and `source_video` preserve the original
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experiment's provenance and are not portable file locations.
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Example RGB and motion frames are bundled. Full encoded motion latents,
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`SHA256SUMS` records every released file except itself. `PROVENANCE.json`
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records the source-archive hashes and packaging transformations.
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The existing dataset's benchmark images and GT videos remain the source inputs.
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## 2026-11-07 update
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The release now uses the measured native RGB baseline run for Table 4.
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The earlier baseline on skeleton-and-mask inputs is retained only as
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`legacy_base_motion_comparison.csv` and `legacy_base_motion_aggregate.csv`.
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Current results and the example figure use the RGB run. Source protocol records
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are retained under `motion_text_matching/source_protocols/`.
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Figures and tables are synchronized with `TOG2026_hzy_AgentHOI_1107`.
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The package additionally includes the real-input comparison (Fig. 4), agent
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ablation, implicit-alignment, data, VLM and agent-transfer experiment figures.
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For these existing paper experiments, supplied figures and tables are included;
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no additional per-video metric outputs or inference reruns are claimed.
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The original plan judgments, stage traces and 12 agent-ablation videos are unchanged.
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README.md
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- Generated plans and blinded Qwen3-VL annotations for single-agent, w/o clipping
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refiner and full settings (Table 3).
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- Reference images, stage outputs and videos for the four agent-ablation cases;
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final Fig.
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- Motion–text matching candidate descriptions, per-case results and example
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frames (Table 4 and supplementary Fig. 4).
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- Final figure PDFs, table sources, metric aggregation scripts and checksums.
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- Generated plans and blinded Qwen3-VL annotations for single-agent, w/o clipping
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refiner and full settings (Table 3).
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- Reference images, stage outputs and videos for the four agent-ablation cases;
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final Fig. 8–9 and supplementary Fig. 2–3.
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- Motion–text matching candidate descriptions, per-case results and example
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frames (Table 4 and supplementary Fig. 4).
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- Final figure PDFs, table sources, metric aggregation scripts and checksums.
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agenthoi_minor_revision.zip
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size
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size 69194567
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