4 citations · 8 across the 7 of their papers we have counts for
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cs.CL2023★ 1 cited
The Trickle-down Impact of Reward (In-)consistency on RLHF
Lingfeng Shen, Sihao Chen, Linfeng Song +5
Standard practice within Reinforcement Learning from Human Feedback (RLHF) involves optimizing against a Reward Model (RM), which itself is trained to reflect human preferences for…
cs.CL2023★ 2 cited
Stabilizing RLHF through Advantage Model and Selective Rehearsal
Baolin Peng, Linfeng Song, Ye Tian +3
Large Language Models (LLMs) have revolutionized natural language processing, yet aligning these models with human values and preferences using RLHF remains a significant challenge…