Zijun Wang

PAVXploreRL: Physical-Action-Visual World Model Reinforcement Learning with Action Exploration

Han Wang, Zijun Wang, Shuoshuo Xue, Rui Cao, Fengjiao Cheng, Xiaodan Liang, et al.

Action-conditioned world models are a key component of embodied AI, serving as scalable policy evaluators that reduce reliance on expensive real-world rollouts. To accurately capture diverse action-induced dynamics, such models should satisfy three key objectives-Physical Plausib…Read more