hkust-nlp/ceval

• mediumreadme#1

  Strengthen README's opening to assert official status and unique value

  原因：

  当前

  C-Eval is a comprehensive Chinese evaluation suite for foundation models. It consists of 13948 multi-choice questions spanning 52 diverse disciplines and four difficulty levels, as shown below. Please visit our website or check our paper for more details.

  复制粘贴的修复

  复制

  C-Eval is the **official and most comprehensive Chinese evaluation suite** for foundation models. As presented at NeurIPS 2023, it features 13948 multi-choice questions across 52 diverse disciplines and four difficulty levels, serving as the primary benchmark for Chinese LLMs. Visit our website or check our paper for more details.

  待办完成忽略
• lowreadme#2

  Expand "Why C-Eval?" section to explicitly state differentiators

  原因：

  当前

  📝 Why C-Eval? How did we build it? (in Chinese)

  复制粘贴的修复

  复制

  ## Why C-Eval? (Core Differentiators)
  
  C-Eval stands out as the leading benchmark for Chinese LLMs due to its:
  - **Comprehensiveness:** 13948 questions across 52 disciplines.
  - **Multi-level Difficulty:** Four distinct difficulty levels for nuanced evaluation.
  - **Official Status:** The primary reference for Chinese foundation model evaluation, accepted at NeurIPS 2023.
  - **Community Integration:** Widely adopted and integrated into evaluation harnesses like lm-evaluation-harness.

  待办完成忽略

本次扫描解析到的品类 GEO 通道：google/gemini-2.5-flash, deepseek/deepseek-v4-flash

• 品类问题

  How can I benchmark large language models specifically for Chinese language understanding?

  你：未被推荐
  AI 推荐顺序：

  1. C-Eval
  2. CMMLU (Chinese Massive Multitask Language Understanding)
  3. GAOKAO-Bench
  4. CLUE (Chinese Language Understanding Evaluation) Benchmark
  5. LongBench
  6. Xiezhi (獇貈)

  AI 推荐了 6 个替代方案，却始终没点名 hkust-nlp/ceval。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Need a comprehensive, multi-disciplinary benchmark for evaluating Chinese large language models.

  你：未被推荐
  AI 推荐顺序：

  1. C-Eval
  2. CMMLU
  3. GAOKAO-Bench
  4. AGIEval
  5. CLUE
  6. Xiezhi

  AI 推荐了 6 个替代方案，却始终没点名 hkust-nlp/ceval。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  warn

  建议：

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of hkust-nlp/ceval?

  pass
  ⚠AI 未点名 hkust-nlp/ceval —— 很可能在说另一个项目

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• If a team adopts hkust-nlp/ceval in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 hkust-nlp/ceval

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？

• In one sentence, what problem does the repo hkust-nlp/ceval solve, and who is the primary audience?

  pass
  ✓AI 明确点名了 hkust-nlp/ceval

  AI 的回答可能信誓旦旦却是错的。请按事实核对：技术栈、目标人群、差异化点是不是和你实际的对得上？