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cs.CL2024
Toward Optimal LLM Alignments Using Two-Player Games
Rui Zheng, Hongyi Guo, Zhihan Liu +10
The standard Reinforcement Learning from Human Feedback (RLHF) framework primarily focuses on optimizing the performance of large language models using pre-collected prompts. Howev…
cs.CL2024
Improving Reinforcement Learning from Human Feedback Using Contrastive Rewards
Wei Shen, Xiaoying Zhang, Yuanshun Yao +3
Reinforcement learning from human feedback (RLHF) is the mainstream paradigm used to align large language models (LLMs) with human preferences. Yet existing RLHF heavily relies on…