2 papers
cs.LG2026
Learning Process Rewards via Success Visitation Matching for Efficient RL
Raymond Tsao, Andrew Wagenmaker, Sergey Levine
In many modern applications of reinforcement learning (RL), the natural reward for a task of interest is inherently sparse: a reward of 0 is given everywhere except when the task i…
cs.LG2025
Posterior Behavioral Cloning: Pretraining BC Policies for Efficient RL Finetuning
Andrew Wagenmaker, Perry Dong, Raymond Tsao +2
Standard practice across domains from robotics to language is to first pretrain a policy on a large-scale demonstration dataset, and then finetune this policy, typically with reinf…