Tim Jones

collaborators

4 papers

cs.LG2026

$I ¨ _{0.7}$ : a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

Physical Intelligence, Bo Ai, Ali Amin +85

We present a new robotic foundation model, called $I ¨ _{0.7}$ , that can enable strong out-of-the-box performance in a wide range of scenarios. $I ¨ _{0.7}$ can follow diverse language…

cs.LG2026

$I ¨ _{0}$ : A Vision-Language-Action Flow Model for General Robot Control

Kevin Black, Noah Brown, Danny Driess +21

Robot learning holds tremendous promise to unlock the full potential of flexible, general, and dexterous robot systems, as well as to address some of the deepest questions in artif…

cs.LG2025

$I ¨ _{0.6}^{*}$ : 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…

cs.LG2025

$I ¨ _{0.5}$ : 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…

I¨0.7​: a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

I¨0​: A Vision-Language-Action Flow Model for General Robot Control

I¨0.6∗​: a VLA That Learns From Experience

I¨0.5​: a Vision-Language-Action Model with Open-World Generalization

$I ¨ _{0.7}$ : a Steerable Generalist Robotic Foundation Model with Emergent Capabilities

$I ¨ _{0}$ : A Vision-Language-Action Flow Model for General Robot Control

$I ¨ _{0.6}^{*}$ : a VLA That Learns From Experience

$I ¨ _{0.5}$ : a Vision-Language-Action Model with Open-World Generalization