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README.md
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# ProtectionBench
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**Paper:** [arXiv:2610.19948](https://arxiv.org/abs/2610.19948) · [PDF](https://arxiv.org/pdf/2610.19948)
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This work was completed at Xiaohongshu.
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The evaluation dataset for **When Protection Overrides Consequences: Understanding Protection Mode in Large Language Model Decision-Making**. Main compares a low-immediate-risk person/animal with an object facing larger time-sensitive physical damage. Reference labels describe the larger stated physical consequence, not universal moral correctness.
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## Third-party models and services
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Unless explicitly stated otherwise, this repository does not include or distribute any third-party model weights. Users who independently download or enable third-party models or services must also comply with the applicable upstream project, model-weight, and data license terms. Use of third-party API services is subject to the applicable service providers' terms and conditions.
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# ProtectionBench
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This work was completed at Xiaohongshu.
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The evaluation dataset for **[When Protection Overrides Consequences: Understanding Protection Mode in Large Language Model Decision-Making](https://arxiv.org/abs/2610.19948)**. Main compares a low-immediate-risk person/animal with an object facing larger time-sensitive physical damage. Reference labels describe the larger stated physical consequence, not universal moral correctness.
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## Third-party models and services
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Unless explicitly stated otherwise, this repository does not include or distribute any third-party model weights. Users who independently download or enable third-party models or services must also comply with the applicable upstream project, model-weight, and data license terms. Use of third-party API services is subject to the applicable service providers' terms and conditions.
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## Citation
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If you use ProtectionBench, please cite:
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```bibtex
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@misc{li2026protectionoverridesconsequencesunderstanding,
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title={When Protection Overrides Consequences: Understanding Protection Mode in Large Language Model Decision-Making},
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author={Yuanfan Li and Junyi Chen and Qi Zhou and Rui Yang and ZhangLiujie and Weihang Chen},
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year={2026},
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eprint={2610.19948},
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archivePrefix={arXiv},
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primaryClass={cs.AI},
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url={https://arxiv.org/abs/2610.19948},
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}
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```
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