21 citations · 22 across the 5 of their papers we have counts for
5 papers
Prompt-Driven Exploration: Language as an Exploration Space for VLA Reinforcement Learning
Sunshine Jiang, John Marangola, David Zhang +6
Exploration is essential to RL since a policy cannot improve by repeatedly sampling the behaviors it already prefers. Standard methods inject stochasticity in the action space, but…
Learning from Hindsight for VLA Reinforcement Learning
Iris Xu, Sunshine Jiang, John Marangola +8
Reinforcement learning is increasingly used to fine-tune vision-language-action (VLA) models, but robot interaction is expensive and learning becomes highly sample inefficient when…
What Matters When Cotraining Robot Manipulation Policies on Everyday Human Videos?
Richard Li, Aditya Prakash, Andrew Wen +3
Human video datasets used for cotraining robot manipulation policies largely consist of curated demonstrations where motions are orchestrated to resemble robot behavior and 3D hand…
Stable Object Reorientation using Contact Plane Registration
Richard Li, Carlos Esteves, Ameesh Makadia +1
We present a system for accurately predicting stable orientations for diverse rigid objects. We propose to overcome the critical issue of modelling multimodality in the space of ro…
Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning
Richard Li, Allan Jabri, Trevor Darrell +1
Learning robotic manipulation tasks using reinforcement learning with sparse rewards is currently impractical due to the outrageous data requirements. Many practical tasks require…