Stanford and UT Austin Researchers Propose Contrastive Preference Learning (CPL): A Simple Reinforcement Learning RL-Free Method for RLHF that Works with Arbitrary MDPs and off-Policy Data
The problem of matching human preferences to large pretrained fashions has gained prominence within the examine ...
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