most citedReinforcement Learning from Multi-role Debates as Feedback for Bias Mitigation in LLMs

1 citations · 1 across the 2 of their papers we have counts for

collaborators

2 papers

cs.RO2026

EgoPush: Egocentric Multi-Object Rearrangement for Mobile Robots via Constrained Teacher Observability

Boyuan An, Zhexiong Wang, Yipeng Wang +4

Humans rearrange objects in cluttered environments using egocentric perception, actively moving to keep task-relevant spatial cues in view. Mobile robots have not matched this: rea…

cs.AI2024★ 1 cited

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…