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| Main Authors: | , , , , , , , , , , , , , , , , , , , , |
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| Format: | Preprint |
| Published: |
2025
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| Subjects: | |
| Online Access: | https://arxiv.org/abs/2511.02366 |
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| _version_ | 1866914211622289408 |
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| author | Li, Yudong Yang, Peiru Huang, Feng Yang, Zhongliang Wang, Kecheng Li, Haitian Chen, Baocheng An, Xingyu Liu, Ziyu Yang, Youdan Chen, Kejiang Wan, Sifang Wang, Xu Sun, Yufei Wu, Liyan Zhou, Ruiqi Wen, Wenya Gu, Xingchi Zhang, Tianxin Gao, Yue Huang, Yongfeng |
| author_facet | Li, Yudong Yang, Peiru Huang, Feng Yang, Zhongliang Wang, Kecheng Li, Haitian Chen, Baocheng An, Xingyu Liu, Ziyu Yang, Youdan Chen, Kejiang Wan, Sifang Wang, Xu Sun, Yufei Wu, Liyan Zhou, Ruiqi Wen, Wenya Gu, Xingchi Zhang, Tianxin Gao, Yue Huang, Yongfeng |
| contents | We introduce LiveSecBench, a continuously updated safety benchmark specifically for Chinese-language LLM application scenarios. LiveSecBench constructs a high-quality and unique dataset through a pipeline that combines automated generation with human verification. By periodically releasing new versions to expand the dataset and update evaluation metrics, LiveSecBench provides a robust and up-to-date standard for AI safety. In this report, we introduce our second release v251215, which evaluates across five dimensions (Public Safety, Fairness & Bias, Privacy, Truthfulness, and Mental Health Safety.) We evaluate 57 representative LLMs using an ELO rating system, offering a leaderboard of the current state of Chinese LLM safety. The result is available at https://livesecbench.intokentech.cn/. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2511_02366 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | LiveSecBench: A Dynamic and Event-Driven Safety Benchmark for Chinese Language Model Applications Li, Yudong Yang, Peiru Huang, Feng Yang, Zhongliang Wang, Kecheng Li, Haitian Chen, Baocheng An, Xingyu Liu, Ziyu Yang, Youdan Chen, Kejiang Wan, Sifang Wang, Xu Sun, Yufei Wu, Liyan Zhou, Ruiqi Wen, Wenya Gu, Xingchi Zhang, Tianxin Gao, Yue Huang, Yongfeng Computation and Language We introduce LiveSecBench, a continuously updated safety benchmark specifically for Chinese-language LLM application scenarios. LiveSecBench constructs a high-quality and unique dataset through a pipeline that combines automated generation with human verification. By periodically releasing new versions to expand the dataset and update evaluation metrics, LiveSecBench provides a robust and up-to-date standard for AI safety. In this report, we introduce our second release v251215, which evaluates across five dimensions (Public Safety, Fairness & Bias, Privacy, Truthfulness, and Mental Health Safety.) We evaluate 57 representative LLMs using an ELO rating system, offering a leaderboard of the current state of Chinese LLM safety. The result is available at https://livesecbench.intokentech.cn/. |
| title | LiveSecBench: A Dynamic and Event-Driven Safety Benchmark for Chinese Language Model Applications |
| topic | Computation and Language |
| url | https://arxiv.org/abs/2511.02366 |