mlsanityData to 7 Oct 2026

Edu-Values: Towards Evaluating the Chinese Education Values of Large Language Models

arXiv 2409.12739 ↗First posted 19 Sep 2024cs.CLcited by 5

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Abstract (arXiv)

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.

Key facts. Cited by 5 papers in the map (data through 7 Oct 2026). Builds on 31 of its 45 references that are in the map. First posted on arXiv 19 Sep 2024.

Builds on

31 of 45 references.

References · 31

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19 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2025: 4; 2026: 1.

5 papers.

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  1. 2024E-EVAL: A Comprehensive Chinese K-12 Education Evaluation Benchmark for Large Language Models
  2. 2025OmniEduBench: A Comprehensive Chinese Benchmark for Evaluating Large Language Models in Education
  3. 2023C-Eval: A Multi-Level Multi-Discipline Chinese Evaluation Suite for Foundation Models
  4. 2025Benchmarking Multi-National Value Alignment for Large Language Models
  5. 2025Analysis of instruction-based LLMs' capabilities to score and judge text-input problems in an academic setting
  6. 2024CMMU: A Benchmark for Chinese Multi-modal Multi-type Question Understanding and Reasoning
  7. 2025Cultural Value Alignment in Large Language Models: A Prompt-based Analysis of Schwartz Values in Gemini, ChatGPT, and DeepSeek
  8. 2026On the Credibility of Evaluating LLMs using Survey Questions