70 citations · 73 across the 3 of their papers we have counts for
4 papers
You Only Live Once: Single-Life Reinforcement Learning
Annie S. Chen, Archit Sharma, Sergey Levine +1
Reinforcement learning algorithms are typically designed to learn a performant policy that can repeatedly and autonomously complete a task, usually starting from scratch. However,…
Just Train Twice: Improving Group Robustness without Training Group Information
Evan Zheran Liu, Behzad Haghgoo, Annie S. Chen +5
Standard training via empirical risk minimization (ERM) can produce models that achieve high accuracy on average but low accuracy on certain groups, especially in the presence of s…
Learning Generalizable Robotic Reward Functions from "In-The-Wild" Human Videos
Annie S. Chen, Suraj Nair, Chelsea Finn
We are motivated by the goal of generalist robots that can complete a wide range of tasks across many environments. Critical to this is the robot's ability to acquire some metric o…
Batch Exploration with Examples for Scalable Robotic Reinforcement Learning
Annie S. Chen, HyunJi Nam, Suraj Nair +1
Learning from diverse offline datasets is a promising path towards learning general purpose robotic agents. However, a core challenge in this paradigm lies in collecting large amou…