---
pretty_name: AVM-Eval
size_categories:
  - 10K<n<100K
tags:
  - robotics
  - world-models
  - evaluation
  - arxiv:2610.32222
---

# AVM-Eval

**AVM-Eval (Action and Video Mismatch Benchmark)** evaluates how reliably inverse dynamics models and reward models assess **action-following fidelity** on real and generated robot videos. It is introduced in [ACWM-RM: A Reference-Free Reward Model from Complementary Mismatch Preferences](https://arxiv.org/abs/2610.32222).

## Dataset Overview

AVM-Eval contains approximately **67.2k evaluation pairs**:

| Pair type | Size | Description |
| --- | --- | --- |
| Action mismatch | 53.9k | The same recorded video paired with original and perturbed action sequences, covering numerical and semantic perturbations. |
| Video mismatch | 13.3k | Two generated videos conditioned on the same initial frame and action sequence, covering intra-model and cross-model comparisons. Preferences are determined using nDTW-based action-following scores. |

Source data comes from **AgiBotWorld, RoboTwin, RoboDojo, and Genie-Sim**. Generated videos are produced by **DreamDojo-2B, DreamDojo-14B, GE-Sim-2B, and OSCAR-2B**. The benchmark uses pairwise accuracy to evaluate action-following assessment, including generalization to unseen tasks, embodiments, and scenes.

## Files

```text
action_mismatch/   # Action-mismatch evaluation pairs in Parquet format
video_mismatch/    # Video-mismatch evaluation pairs in Parquet format
media.tar          # Media archive
```

See the paper for construction details and the evaluation protocol.

## Citation

If you use AVM-Eval in your research, please cite:

```bibtex
@misc{hong2026acwmrm,
  title         = {{ACWM-RM}: A Reference-Free Reward Model from Complementary Mismatch Preferences},
  author        = {Shibo Hong and Siyu Ren and FengJiao Chen and Zhongyuan Peng and Wei Shi and Yixin Cao},
  year          = {2026},
  eprint        = {2610.32222},
  archivePrefix = {arXiv},
  primaryClass  = {cs.CV},
  url           = {https://arxiv.org/abs/2610.32222}
}
```