356 citations · 843 across the 31 of their papers we have counts for
5 papers · 2 filters
Vision Language Models are In-Context Value Learners
Yecheng Jason Ma, Joey Hejna, Ayzaan Wahid +15
Predicting temporal progress from visual trajectories is important for intelligent robots that can learn, adapt, and improve. However, learning such progress estimator, or temporal…
ALOHA Unleashed: A Simple Recipe for Robot Dexterity
Tony Z. Zhao, Jonathan Tompson, Danny Driess +4
Recent work has shown promising results for learning end-to-end robot policies using imitation learning. In this work we address the question of how far can we push imitation learn…
ALOHA 2: An Enhanced Low-Cost Hardware for Bimanual Teleoperation
ALOHA 2 Team, Jorge Aldaco, Travis Armstrong +23
Diverse demonstration datasets have powered significant advances in robot learning, but the dexterity and scale of such data can be limited by the hardware cost, the hardware robus…
RT-H: Action Hierarchies Using Language
Suneel Belkhale, Tianli Ding, Ted Xiao +6
Language provides a way to break down complex concepts into digestible pieces. Recent works in robot imitation learning use language-conditioned policies that predict actions given…
Learning to Learn Faster from Human Feedback with Language Model Predictive Control
Jacky Liang, Fei Xia, Wenhao Yu +47
Large language models (LLMs) have been shown to exhibit a wide range of capabilities, such as writing robot code from language commands -- enabling non-experts to direct robot beha…