README.md

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<img src='https://cdn-uploads.huggingface.co/production/uploads/647773a1168cb428e00e9a8f/N8lP93rB6lL3iqzML4SKZ.png'  width=100px>

<h1 align="center"><b>On Path to Multimodal Generalist: Levels and Benchmarks</b></h1>
<p align="center">
<a href="https://generalist.top/">[📖 Project]</a>
<a href="https://level.generalist.top">[🏆 Leaderboard]</a>
<a href="https://xxxxx">[📄 Paper]</a>
<a href="https://huggingface.co/General-Level">[🤗 Dataset-HF]</a>
<a href="https://github.com/path2generalist/GeneralBench">[📝 Dataset-Github]</a>
</p>


</div>


---
We divide our benchmark into two settings: **`open`** and **`closed`**.

<!-- This is the **`open benchmark`** of Generalist-Bench, where we release the full ground-truth annotations for all datasets.
It allows researchers to train and evaluate their models with access to the answers.

If you wish to thoroughly evaluate your model's performance, please use the
[👉 closed benchmark](https://huggingface.co/datasets/General-Level/General-Bench-Closeset), which comes with detailed usage instructions.

Final results will be updated on the [🏆 Leaderboard](https://level.generalist.top). -->


This is the **`Closed benchmark`** of Generalist-Bench, where we release only the question annotations—**without ground-truth answers**—for all datasets.

You can follow the detailed [usage](#-usage) instructions to submit the resuls generate by your own model.

Final results will be updated on the [🏆 Leaderboard](https://level.generalist.top).


If you’d like to train or evaluate your model with access to the full answers, please check out the [👉 open benchmark](https://huggingface.co/datasets/General-Level/General-Bench-Openset), where all ground-truth annotations are provided.









---

##  📕 Table of Contents

- [✨ File Origanization Structure](#filestructure)
- [🍟 Usage](#usage)
- [🌐 General-Bench](#bench)
  - [🍕 Capabilities and Domians Distribution](#distribution)
- [🖼️ Image Task Taxonomy](#imagetaxonomy)
- [📽️ Video Task Taxonomy](#videotaxonomy)
- [📞 Audio Task Taxonomy](#audiotaxonomy)
- [💎 3D Task Taxonomy](#3dtaxonomy)
- [📚 Language Task Taxonomy](#languagetaxonomy)





---
 
<span id='filestructure'/>

# ✨✨✨ **File Origanization Structure**

Here is the organization structure of the file system:

```

General-Bench

├── Image

│   ├── comprehension

│   │   ├── Bird-Detection

│   │   │   ├── annotation.json

│   │   │   └── images

│   │   │       └── Acadian_Flycatcher_0070_29150.jpg

│   │   ├── Bottle-Anomaly-Detection

│   │   │   ├── annotation.json

│   │   │   └── images

│   │   └── ...

│   └── generation

│       └── Layout-to-Face-Image-Generation

│           ├── annotation.json

│           └── images

│           └── ...

├── Video

│   ├── comprehension

│   │   └── Human-Object-Interaction-Video-Captioning

│   │       ├── annotation.json

│   │       └── videos

│   │       └── ...

│   └── generation

│       └── Scene-Image-to-Video-Generation

│           ├── annotation.json

│           └── videos

│           └── ...

├── 3d

│   ├── comprehension

│   │   └── 3D-Furniture-Classification

│   │       ├── annotation.json

│   │       └── pointclouds

│   │       └── ...

│   └── generation

│       └── Text-to-3D-Living-and-Arts-Point-Cloud-Generation

│           ├── annotation.json

│           └── pointclouds

│           └── ...

├── Audio

│   ├── comprehension

│   │   └── Accent-Classification

│   │       ├── annotation.json

│   │       └── audios

│   │       └── ...

│   └── generation

│       └── Video-To-Audio

│           ├── annotation.json

│           └── audios

│           └── ...

├── NLP

│   ├── History-Question-Answering

│   │   └── annotation.json

│   ├── Abstractive-Summarization

│   │   └── annotation.json

│   └── ...



```


An illustrative example of file formats:


![image/png](https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/RD3b7Jwu0dftVq-4KbpFr.png)


<span id='usage'/>

## 🍟🍟🍟 Usage 

Please download all the files in this repository. We also provide overview.json, which is an example of the format of our dataset.

xxxx


---





<span id='bench'/>



# 🌐🌐🌐 **General-Bench** 




A companion  massive multimodal benchmark dataset, encompasses a broader spectrum of skills, modalities, formats, and capabilities, including over **`700`** tasks and **`325K`** instances. 

<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/647773a1168cb428e00e9a8f/d4TIWw3rlWuxpBCEpHYJB.jpeg'>
<p> Overview of General-Bench, which covers 145 skills for more than 700 tasks with over 325,800 samples under
comprehension and generation categories in various modalities</p>
</div>


<span id='distribution'/>

## 🍕🍕🍕 Capabilities and Domians Distribution

<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/fF3iH95B3QEBvJYwqzZVG.png'>
<p> Distribution of various capabilities evaluated in General-Bench.</p>
</div>


<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/wQvllVeK-KC3Edp8Zjh-V.png'>
<p>Distribution of various domains and disciplines covered by General-Bench.</p>
</div>





<span id='imagetaxonomy'/>

# 🖼️ Image Task Taxonomy
<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/2QYihQRhZ5C9K5IbukY7R.png'>
<p>Taxonomy and hierarchy of data in terms of Image modality.</p>
</div>




<span id='videotaxonomy'/>

# 📽️ Video Task Taxonomy

<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/A7PwfW5gXzstkDH49yIG5.png'>
<p>Taxonomy and hierarchy of data in terms of Video modality.</p>
</div>









<span id='audiotaxonomy'/>

# 📞 Audio Task Taxonomy



<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/e-QBvBjeZy8vmcBjAB0PE.png'>
<p>Taxonomy and hierarchy of data in terms of Audio modality.</p>
</div>



<span id='3dtaxonomy'/>

# 💎 3D Task Taxonomy


<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/EBXb-wyve14ExoLCgrpDK.png'>
<p>Taxonomy and hierarchy of data in terms of 3D modality.</p>
</div>




<span id='languagetaxonomy'/>

# 📚 Language Task Taxonomy

<div align="center">
<img src='https://cdn-uploads.huggingface.co/production/uploads/64c139d867eff857ea51caa8/FLfk3QGdYb2sgorKTj_LT.png'>
<p>Taxonomy and hierarchy of data in terms of Language modality.</p>
</div>




---




# 🚩 **Citation**

If you find our benchmark useful in your research, please kindly consider citing us:

```

@article{generalist2025,

  title={On Path to Multimodal Generalist: Levels and Benchmarks},

  author={Hao Fei, Yuan Zhou, Juncheng Li, Xiangtai Li, Qingshan Xu, Bobo Li, Shengqiong Wu, Yaoting Wang, Junbao Zhou, Jiahao Meng, Qingyu Shi, Zhiyuan Zhou, Liangtao Shi, Minghe Gao, Daoan Zhang, Zhiqi Ge, Siliang Tang, Kaihang Pan, Yaobo Ye, Haobo Yuan, Tao Zhang, Weiming Wu, Tianjie Ju, Zixiang Meng, Shilin Xu, Liyu Jia, Wentao Hu, Meng Luo, Jiebo Luo, Tat-Seng Chua, Hanwang Zhang, Shuicheng YAN},

  journal={arXiv},

  year={2025}

}

```