356 citations · 660 across the 9 of their papers we have counts for
9 papers
RoVi-Aug: Robot and Viewpoint Augmentation for Cross-Embodiment Robot Learning
Lawrence Yunliang Chen, Chenfeng Xu, Karthik Dharmarajan +6
Scaling up robot learning requires large and diverse datasets, and how to efficiently reuse collected data and transfer policies to new embodiments remains an open question. Emergi…
Stop Regressing: Training Value Functions via Classification for Scalable Deep RL
Jesse Farebrother, Jordi Orbay, Quan Vuong +9
Value functions are a central component of deep reinforcement learning (RL). These functions, parameterized by neural networks, are trained using a mean squared error regression ob…
RT-Sketch: Goal-Conditioned Imitation Learning from Hand-Drawn Sketches
Priya Sundaresan, Quan Vuong, Jiayuan Gu +10
Natural language and images are commonly used as goal representations in goal-conditioned imitation learning (IL). However, natural language can be ambiguous and images can be over…
PIVOT: Iterative Visual Prompting Elicits Actionable Knowledge for VLMs
Soroush Nasiriany, Fei Xia, Wenhao Yu +20
Vision language models (VLMs) have shown impressive capabilities across a variety of tasks, from logical reasoning to visual understanding. This opens the door to richer interactio…
RT-Trajectory: Robotic Task Generalization via Hindsight Trajectory Sketches
Jiayuan Gu, Sean Kirmani, Paul Wohlhart +14
Generalization remains one of the most important desiderata for robust robot learning systems. While recently proposed approaches show promise in generalization to novel objects, s…
Q-Transformer: Scalable Offline Reinforcement Learning via Autoregressive Q-Functions
Yevgen Chebotar, Quan Vuong, Alex Irpan +22
In this work, we present a scalable reinforcement learning method for training multi-task policies from large offline datasets that can leverage both human demonstrations and auton…