WoVR+: World Model as Reliable Simulator for Versatile VLA Policy Optimization with RL

Action-conditioned world models can reduce costly real-robot interaction in reinforcement learning for Vision-Language-Action models (VLA-RL), but hallucinations can mislead policy optimization. Extending them to richer VLA interfaces and long-horizon tasks raises challenges in spatiotemporal and cross-modal consistency, exploration-reliability balance in RL, and compounding rollout errors.

초록에서 가져왔습니다. 요약을 준비 중입니다.