7 citations · 8 across the 4 of their papers we have counts for
3 papers · 1 filter
Tether: Autonomous Functional Play with Correspondence-Driven Trajectory Warping
William Liang, Sam Wang, Hung-Ju Wang +3
The ability to conduct and learn from interaction and experience is a central challenge in robotics, offering a scalable alternative to labor-intensive human demonstrations. Howeve…
Eurekaverse: Environment Curriculum Generation via Large Language Models
William Liang, Sam Wang, Hung-Ju Wang +3
Recent work has demonstrated that a promising strategy for teaching robots a wide range of complex skills is by training them on a curriculum of progressively more challenging envi…
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…