README.md

---
pretty_name: Reasoning-Structured Videos Evaluation Artifacts
tags:
  - world-model
  - video-generation
  - benchmark
  - compositional-consistency
  - reproducibility
---

# Reasoning-Structured Videos: Evaluation Artifacts

This page hosts evaluation artifacts for **Reasoning-Structured Videos: A Stratified Diagnostic Suite for Compositional Consistency in World Models**.

The benchmark tests whether action-conditioned video world models respect three trajectory relations:

- **Inverse:** a path followed by its inverse should return to the initial state.
- **Loop:** a closed path should return to the initial state.
- **Equivalence:** two different paths reaching the same state should produce matching endpoints.

We report **self-consistency (SC)** as the primary cross-model diagnostic and use GT-anchor and distributional metrics as complementary evidence.

## Files

| File | Description |
| --- | --- |
| `matrix_game.zip` | 1,371 released Matrix-Game 2.0 SC rollout videos |
| `evaluate_matrix_game_sc.py` | Standalone Matrix-Game SC reproduction script |
| `Reasoning-Structured-Videos-Rebuttal-main.zip` | Frozen R20/R50 manifests, minWM/HY-WorldPlay camera adapters, strict-endpoint and terminal-window evaluators, tests, and result summaries |
| `r50/` | Frozen minWM and HY-WorldPlay R50 SC/GT-anchor rollout videos, metadata, reference images, and manifest |

Reference videos and trajectory metadata are hosted separately in [VideoWorldmodel/ReasoningStructureTestset](https://huggingface.co/datasets/VideoWorldmodel/ReasoningStructureTestset).

## Released R50 rollouts

The `r50/` directory contains the generated rollouts used for the frozen R50 evaluation of two camera-trajectory-conditioned methods:

| Method | Self-consistency | GT-anchor | Total |
| --- | ---: | ---: | ---: |
| [minWM](https://github.com/shengshu-ai/minWM) | 200 | 200 | 400 |
| [HY-WorldPlay 1.5 AR Distill 480P I2V](https://github.com/Tencent-Hunyuan/HY-WorldPlay) | 200 | 200 | 400 |

R50 has 50 graphs for each of Inverse, Loop, and Equivalence. Each tier contains 200 rollouts because every Equivalence graph has paired A/B branches. Self-consistency rollouts start from the model's conditioning frame; GT-anchor rollouts condition on the first 180 GT frames and predict through logical `raw359`.

```text
r50/
  manifests/subset_manifest_R20_R50_raw360_v1.jsonl
  minwm/{self_consistency,gt_anchor}/predictions/<relation>/<record_id>/
  hy_worldplay/{self_consistency,gt_anchor}/predictions/<relation>/<record_id>/
```

Each record includes `rollout.mp4` and `metadata.json`; `reference.png` is included where produced by the inference adapter. Use the logical-to-physical frame mapping in `metadata.json` when selecting frames: saved video spans differ between SC and GT-anchor outputs, so physical frame indices must not be guessed.

Download only this release with:

```bash
hf download VideoWorldmodel/Evaluation \
  --repo-type dataset \
  --include "r50/**" \
  --local-dir .
```

## Main results

### Common camera-trajectory SC (frozen R50)

minWM and HY-WorldPlay receive the same frozen graph IDs and camera trajectories through their official pose-control pathways. Each model completed 200/200 rollouts with zero evaluation failures, using the same 512x288 evaluation preprocessing.

| Model | Inverse LPIPS / PSNR | Loop LPIPS / PSNR | Equivalence LPIPS / PSNR |
| --- | ---: | ---: | ---: |
| HY-WorldPlay 1.5 AR Distill | **0.4597 / 15.07** | **0.4941 / 15.50** | **0.3723 / 16.94** |
| minWM | 0.7118 / 10.46 | 0.7442 / 10.85 | 0.4437 / 14.05 |

R50 contains 50 graphs per relation: 150 graph units and 200 videos because every Equivalence graph has A/B branches. The code archive includes graph-bootstrap intervals, the corresponding GT-anchor summaries, and frozen R50 Endpoint FID/KID reports. Endpoint KID uses an unbiased finite-sample estimator, so valid negative estimates are retained in the detailed artifact rather than interpreted as distances below zero.

### External-model Inverse SC versus revisit horizon

On the same frozen R20 Inverse graphs, pose-certified matched-state revisits show increasing inconsistency from 10 to 40 action steps. minWM changes by +0.2697 LPIPS [0.2196, 0.3256] and -3.65 dB PSNR [-4.69, -2.80]; HY-WorldPlay changes by +0.1039 [0.0379, 0.1754] and -1.94 dB [-3.37, -0.83]. The paired GT same-pose floor shows no detectable 10-to-40 degradation. The archive contains the evaluator, tests, per-graph pose audit, strict fixed-pair sensitivity analysis, and frozen JSON/Markdown results.

### Matrix-Game Inverse SC versus revisit horizon

All 448 Inverse graphs are evaluated at matched-state revisits with increasing action separation. “Physical frame” denotes the zero-indexed position in the saved Matrix MP4. Matrix exports 357 frames for the complete 40-action schedule, so action boundary `k` is mapped to physical frame `round(356k/40)`, anchoring both endpoints and preserving outward/return symmetry.

| Revisit horizon | LPIPS (95% CI) | PSNR dB (95% CI) |
| ---: | ---: | ---: |
| 10 actions | 0.4851 [0.4652, 0.5053] | 14.03 [13.53, 14.53] |
| 20 actions | 0.6106 [0.5976, 0.6234] | 11.46 [11.14, 11.77] |
| 30 actions | 0.6685 [0.6584, 0.6784] | 10.71 [10.45, 10.96] |
| Full rollout (40 actions) | 0.7062 [0.6973, 0.7151] | 10.45 [10.21, 10.69] |

The paired full-minus-10 change is +0.2211 LPIPS [0.1988, 0.2434] and -3.58 dB PSNR [-4.02, -3.15]. Adjacent boundary-rounding schemes preserve the monotonic trend and change intermediate means by at most 0.005 LPIPS / 0.10 dB.

### Endpoint distribution fidelity

Endpoint FID/KID compare generated and matched GT logical `raw359` endpoint sets using clean-fid Inception-v3 pool3 features.

Matrix-Game, complete available output set:

| Relation | Graphs / images | Endpoint FID ↓ | KID ×1000 ↓ |
| --- | ---: | ---: | ---: |
| Inverse | 448 / 448 | 134.94 | 23.018 |
| Loop | 445 / 445 | 141.33 | 24.362 |
| Equivalence | 239 / 478 | 145.55 | 22.943 |

minWM, frozen R50 SC outputs:

| Relation | Graphs / images | Endpoint FID ↓ | KID ×1000 ↓ |
| --- | ---: | ---: | ---: |
| Inverse | 50 / 50 | 242.46 | 47.860 |
| Loop | 50 / 50 | 249.40 | 54.173 |
| Equivalence | 50 / 100 | 240.23 | 50.359 |

Endpoint FID is an image-set metric and is not numerically comparable to the clip-level FVD reported elsewhere. The Matrix analysis also includes 20/50/100/200/full graph sensitivity and a GT-vs-GT finite-sample floor. These endpoint metrics complement, rather than replace, paired SC LPIPS/PSNR.

### Terminal-window distribution robustness

Because an external-model R50 relation contains only 50 strict endpoint images, we additionally pool the final matched logical frames from the common SC rollout track. `K=9` covers the final 0.56 seconds and `K=18` the final 1.12 seconds of each 22.5-second rollout. Each entry is FID / KID ×1000.

| Window | HY-WorldPlay: Inverse / Loop / Equivalence | minWM: Inverse / Loop / Equivalence |
| --- | ---: | ---: |
| K=9 | **103.94 / 6.553 · 132.62 / 8.388 · 128.98 / 8.825** | 223.16 / 62.504 · 242.04 / 69.070 · 217.60 / 56.783 |
| K=18 | **95.61 / 6.763 · 129.45 / 9.053 · 117.96 / 8.224** | 214.68 / 62.997 · 235.68 / 67.737 · 208.07 / 56.998 |

These are point estimates over 50 graph clusters per relation. Consecutive frames are correlated, so the graph remains the sampling unit. This is a late-horizon marginal appearance-distribution check, not an exact-state closure or temporal-order metric. The code archive contains the evaluator, unit test, frozen JSON/Markdown results, and a generic reproduction command.

## Quick reproduction: Matrix-Game SC

This path requires only the files on the current page; no GT dataset is needed.

```bash
python -m pip install -U huggingface_hub

hf download VideoWorldmodel/Evaluation \
  matrix_game.zip evaluate_matrix_game_sc.py \
  --repo-type dataset \
  --local-dir .

unzip matrix_game.zip -d data/MatrixGame2_SC_videos

python -m pip install \
  "numpy>=1.26,<3" \
  "opencv-python-headless>=4.8,<5" \
  "torch>=2.2,<3" \
  "torchvision>=0.17,<1" \
  "lpips==0.1.4"

python evaluate_matrix_game_sc.py \
  --data data/MatrixGame2_SC_videos \
  --output results/matrix_game_sc \
  --lpips \
  --device auto \
  --check-paper
```

If the archive creates one additional top-level directory, point `--data` to the directory that directly contains the five relation folders.

Expected values:

| Relation | Graph N | Recomputed LPIPS / PSNR | Paper LPIPS / PSNR |
| --- | ---: | ---: | ---: |
| Inverse-SC | 448 | 0.7061 / 10.4476 | 0.71 / 10.45 |
| Loop-SC | 445 | 0.7173 / 10.6227 | 0.72 / 10.62 |
| Equivalence-SC | 239 | 0.5918 / 12.5732 | 0.59 / 12.57 |

The evaluator verifies file counts and Equivalence pair integrity, and writes per-graph scores, graph-bootstrap confidence intervals, an audit, and a paper-value check.

## Reproduce the additional analyses

Download and unpack the code artifact:

```bash
hf download VideoWorldmodel/Evaluation \
  Reasoning-Structured-Videos-Rebuttal-main.zip \
  --repo-type dataset \
  --local-dir .

unzip Reasoning-Structured-Videos-Rebuttal-main.zip
cd Reasoning-Structured-Videos-Rebuttal-main

python -m pip install -r requirements-eval.txt
python -m unittest discover -s tests -v
```

The repository README documents six reproducibility paths:

1. recompute SC/GT LPIPS and PSNR from minWM or HY-WorldPlay rollout directories;
2. recompute pose-certified Inverse SC versus horizon for minWM and HY-WorldPlay from saved rollouts;
3. recompute Matrix-Game Inverse SC versus revisit horizon directly from `matrix_game.zip`;
4. recompute relation-wise endpoint FID/KID;
5. recompute R50 terminal-window FID/KID from saved external-model rollouts;
6. run the full Matrix endpoint audit using `matrix_game.zip` and the GT dataset.

The generated minWM/HY-WorldPlay R50 rollouts are released under `r50/`; model checkpoints are not included. Regenerating the videos requires the official [minWM](https://github.com/shengshu-ai/minWM) or [HY-WorldPlay](https://github.com/Tencent-Hunyuan/HY-WorldPlay) repository, its checkpoint, its official environment, and suitable GPUs.

## Frozen identifiers

- Public subset seed: `2357`
- R20 manifest SHA-256: `f8307b78ffb4633b1d6ca6340498a9db615dca4cc45a045d16139abf4375abdf`
- Nested R20/R50 manifest SHA-256: `c1b3e051ec861f6babd00f67cf7c31d0ceba590d93a6fac1ac6a768b40448db4`
- `matrix_game.zip` SHA-256: `caec3d8deb20cffbc645f0aeeaa2af425536715eef935b17347cdfab728a88d4`
- `Reasoning-Structured-Videos-Rebuttal-main.zip` SHA-256: `9ee07bfff222800b2eddf6d3e4a44dd2e93a250ea8e7945dbbdf1a7af8b80ca0`

## Scope

The released experiments evaluate deterministic camera trajectories in static scenes. They support relation-specific diagnostic conclusions under the stated protocol; they are not intended as a universal ranking of world-model architectures.