README.md

---
language:
- zh
license: cc-by-nc-4.0
size_categories:
- 10K<n<100K
task_categories:
- text-classification
---

<h1 align="center"> ChineseHarm-bench</h1>
<h3 align="center"> A Chinese Harmful Content  Detection Benchmark </h3>

> ⚠️ **WARNING**: This project and associated data contain content that may be toxic, offensive, or disturbing. Use responsibly and with discretion.

<p align="center">
  <a href="https://github.com/zjunlp/ChineseHarm-bench">Project</a> •
  <a href="https://arxiv.org/abs/2506.10960">Paper</a> •
  <a href="https://huggingface.co/collections/zjunlp/chineseharm-bench-683b452c5dcd1d6831c3316c">Hugging Face</a> 
</p>

<div>
</div>
<div align="center">
<p align="center">
  <img src="chineseharm_case.png" width="80%"/></p>
</div>

## 🌟Benchmark

This folder contains the ChineseHarm-Bench.

* `bench.json` is the full benchmark combining all categories.
* The other files (e.g., `低俗色情.json`, `欺诈.json`) are category-specific subsets.

Each file is a list of examples with:

* `"文本"`: the input Chinese text
* `"标签"`: the ground-truth label

## 🚩 Ethics Statement

We obtain all data with proper authorization from the respective data-owning organizations and signed the necessary agreements.

**The benchmark is released under the CC BY-NC 4.0 license.
All datasets have been anonymized and reviewed by the Institutional Review Board (IRB) of the data provider to ensure privacy protection.**

Moreover, we categorically denounce any malicious misuse of this benchmark and are committed to ensuring that its development and use consistently align with human ethical principles.

## Acknowledgement

We gratefully acknowledge Tencent for providing the dataset and LLaMA-Factory for the training codebase.

## 🚩Citation

Please cite our repository if you use ChineseHarm-bench in your work. Thanks!

```bibtex
@misc{liu2025chineseharmbenchchineseharmfulcontent,
      title={ChineseHarm-Bench: A Chinese Harmful Content Detection Benchmark}, 
      author={Kangwei Liu and Siyuan Cheng and Bozhong Tian and Xiaozhuan Liang and Yuyang Yin and Meng Han and Ningyu Zhang and Bryan Hooi and Xi Chen and Shumin Deng},
      year={2025},
      eprint={2506.10960},
      archivePrefix={arXiv},
      primaryClass={cs.CL},
      url={https://arxiv.org/abs/2506.10960}, 
}
```