---
base_model:
- InternRobotics/InternVLA-A1-3B
pipeline_tag: robotics
license: mit
---

This repository contains the weights for the model evaluated in the paper [EBench: Elemental Diagnosis of Generalist Mobile Manipulation Policies](https://huggingface.co/papers/2606.18239).

- **Project Page:** [EBench Home](https://internrobotics.github.io/EBench-home/)
- **Repository:** [EBench GitHub](https://github.com/InternRobotics/EBench)
- **Paper:** [EBench: Elemental Diagnosis of Generalist Mobile Manipulation Policies](https://huggingface.co/papers/2606.18239)

## Introduction

EBench is an indoor VLA (Vision-Language-Action) manipulation benchmark built on NVIDIA Isaac Sim. Instead of compressing a model's behavior into a single overall success rate, it produces a **multi-axis capability profile** that exposes what a model is good at — and where it overfits.

This model is the InternVLA-A1-3B base model evaluated as a baseline on the EBench dataset.

## Citation

If you find EBench useful, please consider citing:

```bibtex
@misc{ebench2026,
  title  = {EBench: Elemental Mobile Manipulation Benchmark},
  author = {Shanghai AI Laboratory},
  year   = {2026},
  note   = {Preprint coming soon},
  url    = {https://internrobotics.github.io/EBench-doc/}
}
```