README.md

---
license: mit
task_categories:
- robotics
tags:
- lerobot
- mobile-manipulation
- vla
---

# EBench: Elemental Mobile Manipulation Benchmark Dataset

[Project Page](https://internrobotics.github.io/EBench-home/) | [Paper](https://huggingface.co/papers/2606.18239) | [GitHub](https://github.com/InternRobotics/EBench) | [Documentation](https://internrobotics.github.io/EBench-doc/)

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 repository contains the training trajectories (stored in the [LeRobot](https://github.com/huggingface/lerobot) format) used in the EBench evaluation suite.

## Key Features
- **Three manipulation regimes in one benchmark** — covers *long-horizon*, *dexterous & precise*, and *mobile* manipulation.
- **5-axis atomic diagnostic** — every task is labelled by *Scene · Atomic Skill · Horizon · Precision · Mobility*.
- **4-axis generalization tests** — controlled perturbations along *Object · Background · Instruction · Mixed*.
- **Strict train / test isolation** — validation and unseen splits are open for tuning, while a held-out test split drives the leaderboard.

## Citation

```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/}
}
```