Making Foresight Actionable: Repurposing Representation Alignment in World Action Models
World Action Models (WAMs) offer a promising route for robot manipulation by using video generation models to model future scene evolution before producing control actions. However, our empirical observations reveal a phenomenon: generating plausible visual futures does not always guarantee the extraction of accurate actions. To diagnose this failure, we conduct action-head attention analysis and causal interventions. We find that the action decoder fails to focus on task-relevant interaction regions and remains sensitive to perturbations in task-irrelevant areas. This reveals a representation mismatch: hidden states optimized for visual reconstruction are not inherently organized in a fo...
| Authors | Lu Qiu, Yizhuo Li, Yi Chen et al. |
|---|---|
| Primary category | cs.CV |
| Published | 10 June 2026 |
| Last updated at source | 10 June 2026 |
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