---
library_name: pytorch
tags:
  - robotics
  - vision-language-action
  - visual-prompting
---

# VP-VLA-OXE

This repository contains the VP-VLA policy checkpoint trained for OXE / SimplerEnv-style tabletop manipulation.

VP-VLA uses visual prompts as an interface for vision-language-action models: a high-level planner converts language instructions into visual prompts, and the policy follows those prompts to produce robot actions.

## Usage

Use this checkpoint with the released VP-VLA codebase:

- Code: https://github.com/JIA-Lab-research/VP-VLA
- Paper: https://huggingface.co/papers/2603.22003

Please follow the installation and evaluation instructions in the VP-VLA repository, then pass this checkpoint path to the SimplerEnv evaluation script.

## Citation

If you use this model, please cite the VP-VLA paper:

https://huggingface.co/papers/2603.22003