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cs.CL2026
Fast-Slow Thinking RM: Efficient Integration of Scalar and Generative Reward Models
Jiayun Wu, Peixu Hou, Shan Qu +3
Reward models (RMs) are critical for aligning Large Language Models via Reinforcement Learning from Human Feedback (RLHF). While Generative Reward Models (GRMs) achieve superior ac…
cs.CL2024
Inductive-Deductive Strategy Reuse for Multi-Turn Instructional Dialogues
Jiao Ou, Jiayu Wu, Che Liu +3
Aligning large language models (LLMs) with human expectations requires high-quality instructional dialogues, which usually require instructions that are diverse and in-depth. Exist…