动态更新的中文大模型安全测评基准，覆盖五大风险维度。
LiveSecBench: A Dynamic and Event-Driven Safety Benchmark for Chinese Language Model Applications
- 结合自动生成与人工审核构建高质量数据集。
- 评估57个主流中文大模型，按五大维度给出ELO排名。
- 持续迭代版本，适合研究者与开发者追踪安全进展。
我们提出LiveSecBench，一个针对中文语言模型应用的持续更新安全评测基准。通过自动化生成与人工验证相结合的流水线，构建高质量且独特的数据集。定期发布新版本以扩展数据并更新评估指标，为AI安全提供稳健、实时的标准。本报告介绍第二版v251215，涵盖公共安全、公平性与偏见、隐私、真实性及心理健康安全五个维度。使用ELO评分系统评估57个代表性中文大模型，提供当前中文大模型安全水平的排行榜。结果可访问 https://livesecbench.intokentech.cn/ 查阅。
原文摘要 · Abstract (English)
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/.
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