ImageWAM: Do World Action Models Really Need Video Generation, or Just Image Editing?
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...
| Authors | Yuyang Zhang, Wenyao Zhang, Zekun Qi et al. |
|---|---|
| Primary category | cs.CV |
| Published | 17 June 2026 |
| Last updated at source | 17 June 2026 |
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