| --- |
| language: |
| - zh |
| pretty_name: OpenGuardrailsMixZh_97k |
| --- |
| |
| # OpenGuardrailsMixZh 97k |
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| - **Repository:** [openguardrails/OpenGuardrailsMixZh_97k](https://huggingface.co/openguardrails/OpenGuardrailsMixZh_97k) |
| - **License:** Apache 2.0 |
| - **Paper:** [OpenGuardrails: An Open-Source Context-Aware AI Guardrails Platform](https://arxiv.org/abs/2510.19169) |
| - **Code:** [openguardrails/openguardrails](https://github.com/openguardrails/openguardrails) |
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| ## 📘 Dataset Summary |
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| **OpenGuardrailsMixZh 97k** is a large-scale **Chinese safety dataset collection** introduced in the [OpenGuardrails](https://arxiv.org/abs/2510.19169) paper. |
| It consists of **97,000 Chinese samples** curated, translated, and aligned from several well-known English safety datasets, designed for **multilingual safety evaluation** and **guardrail model training**. |
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| This dataset provides a diverse coverage of safety-related scenarios such as: |
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| * Toxic and unsafe language |
| * Jailbreak and prompt-injection attempts |
| * Ethical and legal compliance |
| * Sensitive topics and harmful instructions |
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| ## 📚 Source Composition |
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| OpenGuardrailsMixZh combines translated and aligned subsets from the following datasets: |
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| | Source Dataset | Description | License | |
| | -------------- | ------------------------------------------------------------------------- | ---------- | |
| | ToxicChat | Multi-turn dialogues containing toxicity and moderation-relevant language | CC BY 4.0 | |
| | WildGuardMix | Diverse unsafe prompts for red-teaming and alignment | Apache 2.0 | |
| | PolyGuard | Multi-lingual safety dataset for LLM guardrails | Apache 2.0 | |
| | XSTest | Cross-lingual safety test dataset | Apache 2.0 | |
| | BeaverTails | Large-scale red teaming dataset for safety and refusal behavior | Apache 2.0 | |
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| All datasets were **machine-translated** to ensure high-quality Chinese representations. |
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| ## 📊 Dataset Statistics |
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| | Attribute | Value | |
| | ---------------------- | ------------------------------------------------------------- | |
| | Total Samples | 97,000 | |
| | Languages | Chinese (Simplified) | |
| | Tasks | Safety classification, refusal prediction, toxicity detection | |
| | Avg. Tokens per sample | ~180 | |
| | Data Type | Instruction–Response pairs with safety annotations | |
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| ## 🧠 Intended Uses |
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| * Fine-tuning and evaluating **Chinese guardrail models** |
| * Benchmarking multilingual **LLM safety performance** |
| * Research on **cross-lingual safety transfer** and **alignment robustness** |
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| ## Limitations |
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| * Some translations may lose subtle cultural or contextual nuances. |
| * Safety labels were aligned from English datasets and may not fully capture **Chinese socio-cultural sensitivities**. |
| * The dataset is intended **for research purposes only**, not for deployment in production without additional validation. |
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| ## Citation |
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| If you use this dataset, please cite the following paper: |
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| ```bibtex |
| @misc{openguardrails, |
| title={OpenGuardrails: An Open-Source Context-Aware AI Guardrails Platform}, |
| author={Thomas Wang and Haowen Li}, |
| year={2025}, |
| url={https://arxiv.org/abs/2510.19169}, |
| } |
| ``` |
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| ## License |
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| This dataset is released under the **Apache 2.0 License**. |
| Please refer to the original source datasets for their respective licenses when using subsets. |
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| ## Acknowledgements |
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| We thank the creators of **ToxicChat**, **WildGuardMix**, **PolyGuard**, **XSTest**, and **BeaverTails** for making their datasets publicly available, enabling cross-lingual safety research. |
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