41 citations · 55 across the 14 of their papers we have counts for
4 papers · 1 filter
Measuring Empowerment from Offline Data for Intrinsically Motivated Exploration
Ishir Garg, Vivek Myers, Qiyang Li +3
Large, unlabeled datasets of prior experience have become increasingly available for agentic tasks in domains such as robotics and coding. A common recipe for these tasks is to tra…
Learning to Act While Waiting: RL Finetuning of Generalist Robot Policies Under Inference Latency
Brian Zhu, Momen Khalil, E Harrison +17
While reinforcement learning (RL) allows generalist robot policies to continually improve during deployment, the large model size of modern generalist policies, such as VLAs, poses…
Test-Time Gradient Guidance of Flow Policies in Reinforcement Learning
Zhiyuan Zhou, Andy Peng, Charles Xu +4
Expressive continuous control policies, such as diffusion and flow models, form the backbone of recent advances in scaling imitation learning for simulated and real robot control.…
Q-learning with Adjoint Matching
Qiyang Li, Sergey Levine
We propose Q-learning with Adjoint Matching (QAM), a novel TD-based reinforcement learning (RL) algorithm that tackles a long-standing challenge in continuous-action RL: efficient…