| title | ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing? |
|---|---|
| authors | Yuyang Zhang, Wenyao Zhang, Zekun Qi, He Zhang, Haitao Lin, Jingbo Zhang, Yao Mu, Xiaokang Yang, Wenjun Zeng, Xin Jin |
| date | 2026-06-17 |
| venue | arXiv (preprint, not peer reviewed) |
| id | arXiv:2606.19531 |
| affiliation | Shanghai Jiao Tong University |
| upvotes | 25 (Hugging Face Daily Papers, 2026-11-01) |
| links | abs pdf hf code |
| abstract | World Action Models (WAMs) commonly rely on video generation to bridge visual world modeling and robot control. However, video-based WAMs face three coupled limitations: dense multi-frame future tokens make inference costly, full video prediction spends capacity on action-irrelevant temporal and appearance details, and long-horizon future imagination may introduce errors that mislead action prediction. These issues raise a simple question: Does world action model really need video generation? We propose ImageWAM, a simple WAM framework that repurposes pretrained image editing models for robot action prediction. In contrast to video generation, image editing provides a better-matched prior: it only needs to model a target-frame transformation, focuses on action-relevant current-to-target visual differences, and grounds task instructions to localized visual changes through edit pretraining. In practice, ImageWAM does not decode the target frame at inference time; instead, it conditions a flow-matching action expert on the KV caches produced by image-editing denoising, using them as a compact world-action context. ImageWAM outperforms standard VLA baselines and matching competitive WAMs without additional policy pretraining across different simulator and real-world experiments. It also reduces FLOPs to 1/6 and latency to 1/4 of video-based WAMs. Attention analysis further shows that editing caches focus on task-relevant change regions, supporting image editing as an effective alternative to video-based world-action modeling. |
cite
@misc{zhang2026imagewam,
title={ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing?},
author={Yuyang Zhang and Wenyao Zhang and Zekun Qi and He Zhang and Haitao Lin and Jingbo Zhang and Yao Mu and Xiaokang Yang and Wenjun Zeng and Xin Jin},
year={2026},
eprint={2606.19531},
archivePrefix={arXiv},
url={https://arxiv.org/abs/2606.19531}
}