SeekingDream/Static-to-Dynamic-LLMEval

• highreadme#1

  Clarify repo's purpose as a survey paper in README's opening

  原因：

  当前

  # Recent Advances in Large Language Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation

  复制粘贴的修复

  复制

  # Recent Advances in Large Language Model Benchmarks against Data Contamination: From Static to Dynamic Evaluation
  
  This repository serves as the official, actively maintained companion for our survey paper, providing a comprehensive review and ongoing updates on the latest research in dynamic evaluation for large language models.

  待办完成忽略
• highlicense#2

  Add a LICENSE file to the repository

  原因：

  复制粘贴的修复

  复制

  Create a LICENSE file (e.g., MIT, Apache-2.0) in the root of the repository to clearly state the terms of use for the code and content.

  待办完成忽略
• mediumtopics#3

  Add 'survey' and 'literature-review' topics

  原因：

  当前

  benchmark, dynamic-evaluation, evaluation, large-language-model, llm, llms, testing

  复制粘贴的修复

  复制

  benchmark, dynamic-evaluation, evaluation, large-language-model, llm, llms, testing, survey, literature-review, research-paper

  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 to evaluate large language models effectively, avoiding data contamination issues?

  你：未被推荐
  AI 推荐顺序：

  1. EleutherAI's LM Evaluation Harness (lm-eval) (EleutherAI/lm-evaluation-harness)

  AI 推荐了 1 个替代方案，却始终没点名 SeekingDream/Static-to-Dynamic-LLMEval。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  Tools for dynamic evaluation of large language models to improve benchmark robustness?

  你：未被推荐
  AI 推荐顺序：

  1. Adversarial GLUE (AdvGLUE)
  2. CheckList
  3. Dynabench
  4. Gauntlet
  5. Robustness Gym
  6. Hugging Face Evaluate library
  7. DeepMind's "Measuring and Improving Robustness in NLP" toolkit

  AI 推荐了 7 个替代方案，却始终没点名 SeekingDream/Static-to-Dynamic-LLMEval。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 SeekingDream/Static-to-Dynamic-LLMEval?

  pass
  ✓AI 明确点名了 SeekingDream/Static-to-Dynamic-LLMEval

  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 SeekingDream/Static-to-Dynamic-LLMEval in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 SeekingDream/Static-to-Dynamic-LLMEval

  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 SeekingDream/Static-to-Dynamic-LLMEval solve, and who is the primary audience?

  pass
  ⚠AI 未点名 SeekingDream/Static-to-Dynamic-LLMEval —— 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？