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cs.LG2024
Cost-Effective Proxy Reward Model Construction with On-Policy and Active Learning
Yifang Chen, Shuohang Wang, Ziyi Yang +6
Reinforcement learning with human feedback (RLHF), as a widely adopted approach in current large language model pipelines, is \textit{bottlenecked by the size of human preference d…
cs.LG2024
Self-Exploring Language Models: Active Preference Elicitation for Online Alignment
Shenao Zhang, Donghan Yu, Hiteshi Sharma +6
Preference optimization, particularly through Reinforcement Learning from Human Feedback (RLHF), has achieved significant success in aligning Large Language Models (LLMs) to adhere…