103 citations · 147 across the 18 of their papers we have counts for
4 papers · 1 filter
In-Context Imitation Learning via Next-Token Prediction
Letian Fu, Huang Huang, Gaurav Datta +5
We explore how to enhance next-token prediction models to perform in-context imitation learning on a real robot, where the robot executes new tasks by interpreting contextual infor…
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…
DROID: A Large-Scale In-The-Wild Robot Manipulation Dataset
Alexander Khazatsky, Karl Pertsch, Suraj Nair +98
The creation of large, diverse, high-quality robot manipulation datasets is an important stepping stone on the path toward more capable and robust robotic manipulation policies. Ho…
Mirage: Cross-Embodiment Zero-Shot Policy Transfer with Cross-Painting
Lawrence Yunliang Chen, Kush Hari, Karthik Dharmarajan +3
The ability to reuse collected data and transfer trained policies between robots could alleviate the burden of additional data collection and training. While existing approaches su…