BEE: Intervention-Adaptive Real-World Reinforcement Learning with Vision-Language-Action Models
Vision-language-action (VLA) models handle long-horizon manipulation, yet success hinges on a few precision-critical phases where millimeter-scale errors undo all prior progress. Online reinforcement learning (RL) can optimize exactly these actions, but free exploration is far too costly on real robots, which makes hum...
Wei-Hui Zhao, Xiao Yan, Zu-Nian Wan et al.
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