Chandra Kuchi

most citedOpen-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

1 citations · 1 across the 1 of their papers we have counts for

collaborators

3 papers

cs.RO2026★ 1 cited

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

Open-H-Embodiment Consortium, :, Nigel Nelson +213

Autonomous medical robots hold promise to improve patient outcomes, reduce provider workload, democratize access to care, and enable superhuman precision. However, autonomous medic…

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.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…

Open-H-Embodiment: A Large-Scale Dataset for Enabling Foundation Models in Medical Robotics

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

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

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

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