24 citations · 46 across the 11 of their papers we have counts for
4 papers · 1 filter
DrEureka: Language Model Guided Sim-To-Real Transfer
Yecheng Jason Ma, William Liang, Hung-Ju Wang +5
Transferring policies learned in simulation to the real world is a promising strategy for acquiring robot skills at scale. However, sim-to-real approaches typically rely on manual…
Composing Pre-Trained Object-Centric Representations for Robotics From "What" and "Where" Foundation Models
Junyao Shi, Jianing Qian, Yecheng Jason Ma +1
There have recently been large advances both in pre-training visual representations for robotic control and segmenting unknown category objects in general images. To leverage these…
Universal Visual Decomposer: Long-Horizon Manipulation Made Easy
Zichen Zhang, Yunshuang Li, Osbert Bastani +4
Real-world robotic tasks stretch over extended horizons and encompass multiple stages. Learning long-horizon manipulation tasks, however, is a long-standing challenge, and demands…
LIV: Language-Image Representations and Rewards for Robotic Control
Yecheng Jason Ma, William Liang, Vaidehi Som +4
We present Language-Image Value learning (LIV), a unified objective for vision-language representation and reward learning from action-free videos with text annotations. Exploiting…