James Darpinian

most cited

π_{0.5}

: a Vision-Language-Action Model with Open-World Generalization

2 citations · 2 across the 2 of their papers we have counts for

collaborators

3 papers

cs.RO2025

Emergence of Human to Robot Transfer in Vision-Language-Action Models

Simar Kareer, Karl Pertsch, James Darpinian +5

Vision-language-action (VLA) models can enable broad open world generalization, but require large and diverse datasets. It is appealing to consider whether some of this data can co…

cs.LG2025

$π_{0.6}^{*}$ : 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★ 2 cited

$π_{0.5}$ : 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…

Emergence of Human to Robot Transfer in Vision-Language-Action Models

π0.6∗​: a VLA That Learns From Experience

π0.5​: a Vision-Language-Action Model with Open-World Generalization

$π_{0.6}^{*}$ : a VLA That Learns From Experience

$π_{0.5}$ : a Vision-Language-Action Model with Open-World Generalization