With the rapid evolution of large language models (LLMs), there is a growing concern that they may pose risks or have negative social impacts. Therefore, evaluation of human values alignment is becoming increasingly important. Previous work mainly focuses on assessing the performance of LLMs on certain knowledge and reasoning abilities, while neglecting the alignment to human values, especially in a Chinese context. In this paper, we present CValues, the first Chinese human values evaluation benchmark to measure the alignment ability of LLMs in terms of both safety and responsibility criteria. As a result, we have manually collected adversarial safety prompts across 10 scenarios and induced responsibility prompts from 8 domains by professional experts. To provide a comprehensive values evaluation of Chinese LLMs, we not only conduct human evaluation for reliable comparison, but also construct multi-choice prompts for automatic evaluation. Our findings suggest that while most Chinese LLMs perform well in terms of safety, there is considerable room for improvement in terms of responsibility. Moreover, both the automatic and human evaluation are important for assessing the human values alignment in different aspects. The benchmark and code is available on ModelScope and Github.

本文提出了CValues，首个用于评估大型语言模型（LLMs）人类价值观一致性的中文评估基准，该基准通过在十个场景中手动收集对抗性安全提示和由专业专家引导的八个领域的责任提示来衡量LLMs的一致性能力。研究发现，虽然大部分中文LLMs在安全方面表现良好，但在责任方面还有相当大的改进空间。自动评估和人工评估在评估不同方面的人类价值观一致性方面都是重要的。

CValues: 从安全到责任，衡量中国大型语言模型的价值