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HaWMPO: Hallucination-Aware World Model-based Policy Optimization for Generalist Robot Policy

arXiv · AI, language, vision and robotics · article · Sep 9, 2026 · UTC

Generalist robot policies have demonstrated strong generalization across robotic manipulation tasks, yet their success rates remain limited in com- plex long-horizon scenarios. Recent methods improve Visual-Language-Action (VLA) policies through online reinforcement learning on real robots, but such training relies on costly physical interactions, suffers from low sample efficiency, and may introduce hardware and safety risks. World models offer a promising alternative by enabling policy optimization with imagined rollouts. However, long-horizon rollouts generated by world models often suffer

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