A General Theoretical Paradigm to Understand Learning from Human Preferences

Mohammad Gheshlaghi Azar, Mark Rowland, Bilal Piot +4

The prevalent deployment of learning from human preferences through reinforcement learning (RLHF) relies on two important approximations: the first assumes that pairwise preference…