221 citations · 468 across the 22 of their papers we have counts for
26 papers
Fine-Tuning VLAs with Self-Demonstrated Generative Control for Multi-Task Manipulation
Prachi Garg, Steve Xing, Prahit Yaugand +2
State-of-the-art vision-language-action (VLA) models such as exhibit strong semantic understanding, instruction following and task behavior. However, when deployed on new…
Push Past Green: Learning to Look Behind Plant Foliage by Moving It
Xiaoyu Zhang, Saurabh Gupta
Autonomous agriculture applications (e.g., inspection, phenotyping, plucking fruits) require manipulating the plant foliage to look behind the leaves and the branches. Partial visi…
Predicting Motion Plans for Articulating Everyday Objects
Arjun Gupta, Max E. Shepherd, Saurabh Gupta
Mobile manipulation tasks such as opening a door, pulling open a drawer, or lifting a toilet lid require constrained motion of the end-effector under environmental and task constra…
One-shot Visual Imitation via Attributed Waypoints and Demonstration Augmentation
Matthew Chang, Saurabh Gupta
In this paper, we analyze the behavior of existing techniques and design new solutions for the problem of one-shot visual imitation. In this setting, an agent must solve a novel in…
On-Device CPU Scheduling for Sense-React Systems
Aditi Partap, Samuel Grayson, Muhammad Huzaifa +5
Sense-react systems (e.g. robotics and AR/VR) have to take highly responsive real-time actions, driven by complex decisions involving a pipeline of sensing, perception, planning, a…
Learning Value Functions from Undirected State-only Experience
Matthew Chang, Arjun Gupta, Saurabh Gupta
This paper tackles the problem of learning value functions from undirected state-only experience (state transitions without action labels i.e. (s,s',r) tuples). We first theoretica…