metadata
license: mit
task_categories:
- robotics
MetaFine Dataset
This dataset is a companion release for the paper Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation.
- Project Page: https://metafine.github.io/
- GitHub Repository: https://github.com/Hiangx-robotics/MetaFine
MetaFine is a diagnostic meta-evaluation framework for fine-grained robotic manipulation. Instead of a single binary success rate, it disentangles manipulation competency along three fundamental axes: understanding, perception, and behavior.
Dataset Structure
The repository contains two main parts:
- Fine-grained annotated simulation assets: 40+ URDF-based simulation objects (including a PartNet-Mobility subset and custom URDFs) with fine-grained part annotations and related interaction metadata (
capabilities.json). - Fine-grained task data: Task specifications (YAML) used for training and testing fine-grained manipulation policies across various environments.
Usage
You can download the assets and configurations using the Hugging Face CLI:
huggingface-cli download hiangx/MetaFine --repo-type dataset
Place the unpacked assets/ and configs/ directories next to your local MetaFine repository root to use them with the platform.
Citation
@article{xu2026metafine,
title = {Beyond Binary Success: A Diagnostic Meta-Evaluation Framework for Fine-Grained Manipulation},
author = {Xu, He-Yang and Zhang, Pengyuan and Ge, Zongyuan and Hao, Xiaoshuai and Belongie, Serge and Geng, Xin and Peng, Yuxin and Wei, Xiu-Shen},
journal = {arXiv preprint arXiv:2605.19986},
year = {2026}
}