Using Context Is Not Enough: Test-Time Training for Personalized Reward Modeling
Reinforcement learning from human feedback (RLHF) aligns large language models (LLMs) with human preferences, yet most pipelines learn a single reward model that overlooks individual differences in preferences. Personalized reward models (PRMs) address this by conditioning rewards on user-specific feedback, most common...
Bo-Hao Wang, Xiao-Yan Zhao, Yang Zhang et al.
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