most citedOvercoming Reward Overoptimization via Adversarial Policy Optimization with Lightweight Uncertainty Estimation

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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…