Event-Aligned Visual Action Reasoning for World Action Models
World-Action Models (WAMs) utilize future visual prediction as an intermediate reasoning process to guide action generation. However, existing WAMs typically structure visual imagination according to predefined temporal intervals, without explicitly accounting for the different roles of task-critical interactions and connecting transitions. We argue that effective visual foresight should align directly with task-relevant interactions and their corresponding reasoning demands. To this end, we introduce an event-aligned visual action reasoning framework that organizes visual-action prediction around interaction events. Through event-aligned visual-action supervision, WAM learns to generate ...
| Authors | Xiaomeng Yang, Yushu Wu, Yi Gao et al. |
|---|---|
| Primary category | cs.CV |
| Published | 7 October 2026 |
| Last updated at source | 7 October 2026 |
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