13 citations · 18 across the 4 of their papers we have counts for
4 papers · 1 filter
ELASTIC: Efficiently Learning to Adaptively Scale Test-Time Compute for Generative Control Policies
Andrew Zou Li, Gokul Swamy, Yonatan Bisk +1
Generative control policies (GCPs), such as diffusion policies and flow-based vision-language-action models, enable test-time scaling in robot control. Test-time compute can be all…
STAMP: Differentiable Task and Motion Planning via Stein Variational Gradient Descent
Yewon Lee, Andrew Z. Li, Philip Huang +7
Planning for sequential robotics tasks often requires integrated symbolic and geometric reasoning. TAMP algorithms typically solve these problems by performing a tree search over h…
Chemistry Lab Automation via Constrained Task and Motion Planning
Naruki Yoshikawa, Andrew Zou Li, Kourosh Darvish +6
Chemists need to perform many laborious and time-consuming experiments in the lab to discover and understand the properties of new materials. To support and accelerate this process…
Boreas: A Multi-Season Autonomous Driving Dataset
Keenan Burnett, David J. Yoon, Yuchen Wu +9
The Boreas dataset was collected by driving a repeated route over the course of one year, resulting in stark seasonal variations and adverse weather conditions such as rain and fal…