arXiv — cs.AI preprintsInternational9 October 2026
ACID: Action Consistency via Inverse Dynamics for Planning with World Models
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arXiv:2607.02403v2 Announce Type: replace-cross Abstract: Decision-time planning with action-conditioned world models has become a popular paradigm for embodied control. However, the standard planning cost judges a candidate solely by how close its predicted terminal state lies to the goal, leaving the realizability of the intermediate transitions unchecked--a predicted trajectory can look convincing while the environment rollout drifts away from it. In this paper, we propose ACID, a decision-time planning framework that introduces cycle action consistency: the action inferred backward from a
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