2 citations · 2 across the 2 of their papers we have counts for
5 papers
: a VLA That Learns From Experience
Physical Intelligence, Ali Amin, Raichelle Aniceto +53
We study how vision-language-action (VLA) models can improve through real-world deployments via reinforcement learning (RL). We present a general-purpose method, RL with Experience…
Knowledge Insulating Vision-Language-Action Models: Train Fast, Run Fast, Generalize Better
Danny Driess, Jost Tobias Springenberg, Brian Ichter +8
Vision-language-action (VLA) models provide a powerful approach to training control policies for physical systems, such as robots, by combining end-to-end learning with transfer of…
SRT-H: A Hierarchical Framework for Autonomous Surgery via Language Conditioned Imitation Learning
Ji Woong Kim, Juo-Tung Chen, Pascal Hansen +11
Research on autonomous surgery has largely focused on simple task automation in controlled environments. However, real-world surgical applications demand dexterous manipulation ove…
: a Vision-Language-Action Model with Open-World Generalization
Physical Intelligence, Kevin Black, Noah Brown +33
In order for robots to be useful, they must perform practically relevant tasks in the real world, outside of the lab. While vision-language-action (VLA) models have demonstrated im…
Hi Robot: Open-Ended Instruction Following with Hierarchical Vision-Language-Action Models
Lucy Xiaoyang Shi, Brian Ichter, Michael Equi +12
Generalist robots that can perform a range of different tasks in open-world settings must be able to not only reason about the steps needed to accomplish their goals, but also proc…