Edu-Values：面向评估大型语言模型的中国教育价值观
Edu-Values: Towards Evaluating the Chinese Education Values of Large Language Models
AI总结：
本文提出Edu-Values基准，评估大型语言模型的中国教育价值观，包含七个核心价值，通过1418道题测试，发现中文LLM在教育文化差异下表现更优，且利用Edu-Values构建外部知识库可提升对齐效果。
摘要：
本文提出了Edu-Values，首个包含七个核心价值（专业哲学、教师职业伦理、教育法律法规、文化素养、教育知识与技能、基本素养和学科知识）的中国教育价值观评估基准。我们精心设计了1,418道题目，涵盖单选、多模态问答、主观分析、对抗性提示和中国传统文化（简答题）。我们对21种最先进的LLM进行了基于人工反馈的自动评估，发现三个主要结论：（1）由于教育文化差异，中文LLM在中文LLM中表现更优，Qwen 2以81.37的分数排名第一；（2）LLM在教师职业伦理和专业哲学方面经常遇到困难；（3）利用Edu-Values构建外部知识库以增强RAG显著提高了LLM的对齐效果。这证明了所提出基准的有效性。
英文摘要：
In this paper, we present Edu-Values, the first Chinese education values evaluation benchmark that includes seven core values: professional philosophy, teachers' professional ethics, education laws and regulations, cultural literacy, educational knowledge and skills, basic competencies and subject knowledge. We meticulously design 1,418 questions, covering multiple-choice, multi-modal question answering, subjective analysis, adversarial prompts, and Chinese traditional culture (short answer) questions. We conduct human feedback based automatic evaluation over 21 state-of-the-art (SoTA) LLMs, and highlight three main findings: (1) due to differences in educational culture, Chinese LLMs outperform English LLMs, with Qwen 2 ranking the first with a score of 81.37; (2) LLMs often struggle with teachers' professional ethics and professional philosophy; (3) leveraging Edu-Values to build an external knowledge repository for RAG significantly improves LLMs' alignment. This demonstrates the effectiveness of the proposed benchmark.
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。
