EV-WM: Event-Verified World Models for Long-Horizon Robotic Manipulation
Pretrained-feature world models provide a useful substrate for robot imagination, but visual or latent prediction alone does not determine whether an imagined future satisfies task-relevant predicates. Long-horizon manipulation requires progress signals that are relational, predicate-level, and physically grounded: whether an object has moved, whether a drawer or contact state has changed, whether a placement predicate is satisfied, and whether a candidate future is reliable enough for execution. We introduce \textbf{EV-WM}, a predicate-grounded verification framework for world-model planning. EV-WM rolls out candidate futures in pretrained visual-feature space, decodes them into structur...
| Authors | Kailin Wang, Haoxiang Jie, Yaoyuan Yan et al. |
|---|---|
| Primary category | cs.RO |
| Published | 11 June 2026 |
| Last updated at source | 15 June 2026 |
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