18 citations · 34 across the 10 of their papers we have counts for
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cs.LG2023★ 1 cited
Learning Optimal Advantage from Preferences and Mistaking it for Reward
W. Bradley Knox, Stephane Hatgis-Kessell, Sigurdur Orn Adalgeirsson +4
We consider algorithms for learning reward functions from human preferences over pairs of trajectory segments, as used in reinforcement learning from human feedback (RLHF). Most re…
cs.LG2023★ 2 cited
Contrastive Preference Learning: Learning from Human Feedback without RL
Joey Hejna, Rafael Rafailov, Harshit Sikchi +4
Reinforcement Learning from Human Feedback (RLHF) has emerged as a popular paradigm for aligning models with human intent. Typically RLHF algorithms operate in two phases: first, u…