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cs.LG2025
PersRM-R1: Enhance Personalized Reward Modeling with Reinforcement Learning
Mengdi Li, Guanqiao Chen, Xufeng Zhao +3
Reward models (RMs), which are central to existing post-training methods, aim to align LLM outputs with human values by providing feedback signals during fine-tuning. However, exis…
cs.AI2025
Curriculum-RLAIF: Curriculum Alignment with Reinforcement Learning from AI Feedback
Jiaye Lin, Mengdi Li, Xufeng Zhao +4
Reward models trained through Reinforcement Learning from AI Feedback (RLAIF) methods frequently suffer from limited generalizability, which hinders the alignment performance of po…
cs.RO2025
LLM+MAP: Bimanual Robot Task Planning using Large Language Models and Planning Domain Definition Language
Kun Chu, Xufeng Zhao, Cornelius Weber +1
Bimanual robotic manipulation provides significant versatility, but also presents an inherent challenge due to the complexity involved in the spatial and temporal coordination betw…