SafetyBench：评估大语言模型的安全性
SafetyBench: Evaluating the Safety of Large Language Models
AI总结：
针对大语言模型安全评估缺乏综合基准的问题，提出包含11435道中英文多类别安全选择题的SafetyBench基准，测试25款主流LLMs发现GPT-4安全性表现最优且现有模型仍有较大提升空间。
摘要：
随着大语言模型（Large Language Models, LLMs）的快速发展，其安全性问题受到越来越多的关注。因此，评估LLMs的安全性已成为推动LLMs广泛应用的一项关键任务。然而，缺乏全面的安全性评估基准严重阻碍了对LLMs安全性的有效评估与提升。在本研究中，我们提出SafetyBench——一个用于评估LLMs安全性的综合基准，它包含11435道多样化的选择题，涵盖7个不同类别的安全问题。值得注意的是，SafetyBench同时包含中英文数据，可支持两种语言的评估。我们在零样本和少样本设置下对25个主流中英文LLMs开展了大量测试，结果显示GPT-4的性能显著优于同类模型，且当前LLMs的安全性仍有很大提升空间。我们还证明，在SafetyBench中测得的安全理解能力与安全生成能力具有相关性。数据与评估指南可在https://github.com/thu-coai/SafetyBench获取，提交入口与排行榜可在https://llmbench.ai/safety查看。
英文摘要：
With the rapid development of Large Language Models (LLMs), increasing attention has been paid to their safety concerns. Consequently, evaluating the safety of LLMs has become an essential task for facilitating the broad applications of LLMs. Nevertheless, the absence of comprehensive safety evaluation benchmarks poses a significant impediment to effectively assess and enhance the safety of LLMs. In this work, we present SafetyBench, a comprehensive benchmark for evaluating the safety of LLMs, which comprises 11,435 diverse multiple choice questions spanning across 7 distinct categories of safety concerns. Notably, SafetyBench also incorporates both Chinese and English data, facilitating the evaluation in both languages. Our extensive tests over 25 popular Chinese and English LLMs in both zero-shot and few-shot settings reveal a substantial performance advantage for GPT-4 over its counterparts, and there is still significant room for improving the safety of current LLMs. We also demonstrate that the measured safety understanding abilities in SafetyBench are correlated with safety generation abilities. Data and evaluation guidelines are available at \url{https://github.com/thu-coai/SafetyBench}{https://github.com/thu-coai/SafetyBench}. Submission entrance and leaderboard are available at \url{https://llmbench.ai/safety}{https://llmbench.ai/safety}.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
