2 papers
cs.RO2026
EgoPush: Learning End-to-End Egocentric Multi-Object Rearrangement for Mobile Robots
Boyuan An, Zhexiong Wang, Yipeng Wang +4
Humans can rearrange objects in cluttered environments using egocentric perception, navigating occlusions without global coordinates. Inspired by this capability, we study long-hor…
cs.AI2024
Reinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs
Ruoxi Cheng, Haoxuan Ma, Shuirong Cao +6
Bias in LLMs can harm user experience and societal outcomes. However, current bias mitigation methods often require intensive human feedback, lack transferability to other topics o…