b:botstest.Submit a resource ↗

Models / Research

UniVLA

Robot policy research using latent action representations.

VLARobot learning
Publisher repository ↗
UniVLA resource page screenshot
Resource screenshot · captured 2026-10-08 · visually reviewed

Overview

Robot policy research using latent action representations.

Compare observation inputs, action representations, adaptation data and inference requirements. Code licensing and model-weight licensing may differ; review both before deployment. A source repository may have an open code license while its checkpoints have separate terms.

Project information

Maintainer
OpenDriveLab
Primary language
Python
Repository code license
Apache-2.0
Model-weight license
Not recorded
Dataset license
Not recorded
Hardware design license
Not recorded
Maintenance
Not archived in the last recorded metadata
Last observed repository push
2025-11-19

Code licenses do not automatically cover model weights, datasets or hardware designs. Unrecorded license details require confirmation with the publisher.

Documentation sections

  • :earthasia: UniVLA
  • :fire: Highlights
  • Table of Contents
  • :moviecamera: Demo
  • :loudspeaker: News
  • 🤗 Model Zoo <a name="ckpts"></a>

Browse this resource’s categories

Application areas

Education & research ↗

Explore related collections

Vision-language-action models ↗