UT Austin

Items

1. Apr 15

   Value Gradient Flow recasts behavior-regularized RL

   UC Berkeley and UT Austin treat the optimization behind RLHF and offline RL as optimal transport solved by discrete gradient flow from the reference distribution, dropping explicit policy parameterization and beating PPO and DPO variants on D4RL, OGBench, and LLM RL tasks.