DEEP-PolyU/Awesome-LLM-based-Text2SQL

• highreadme#1

  Reposition the README's opening paragraph to explicitly state its nature as an 'Awesome List' and 'Survey'

  原因：

  当前

  This repository provides a comprehensive collection of research papers, benchmarks, and open-source projects on **large language model-based text-to-SQL (LLM-based Text-to-SQL)**. It includes all the contents from our survey paper 📖<em>"**Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL**"</em> and will be continuously updated to incorporate the up-to-date advances and notable contributions from the text-to-SQL community. Stay tuned!!

  复制粘贴的修复

  复制

  This **Awesome List** is a comprehensive, continuously updated collection of research papers, benchmarks, and open-source projects on **large language model-based text-to-SQL (LLM-based Text-to-SQL)**. It serves as the official companion to our survey paper 📖<em>"**Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL**"</em>, curating the latest advances and notable contributions from the text-to-SQL community.

  待办完成忽略
• mediumtopics#2

  Add specific 'awesome-list' and 'survey-paper' topics

  原因：

  当前

  awesome, awesome-text-to-sql, awesome-text2sql, database, large-language-models, llms, natual-language-processing, natural-language-understanding, nl2sql, survey, text-to-sql, text2sql

  复制粘贴的修复

  复制

  awesome, awesome-list, awesome-text-to-sql, awesome-text2sql, database, large-language-models, llms, natual-language-processing, natural-language-understanding, nl2sql, survey, survey-paper, text-to-sql, text2sql

  待办完成忽略
• lowtopics#3

  Correct typo in 'natural-language-processing' topic

  原因：

  当前

  natual-language-processing

  复制粘贴的修复

  复制

  natural-language-processing

  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

  Where can I find a comprehensive survey of large language model text-to-SQL solutions?

  你：未被推荐
  AI 推荐顺序：

  1. Papers With Code
  2. arXiv
  3. Google Scholar
  4. Hugging Face
  5. Towards Data Science
  6. Kaggle

  AI 推荐了 6 个替代方案，却始终没点名 DEEP-PolyU/Awesome-LLM-based-Text2SQL。这就是要补上的差距。

  查看 AI 完整回答
• 品类问题

  What open-source projects and benchmarks exist for converting natural language to SQL using LLMs?

  你：未被推荐
  AI 推荐顺序：

  1. Spider
  2. Picard
  3. RAT-SQL
  4. SQLova
  5. NatSQL
  6. WikiSQL
  7. CoSQL
  8. SParC
  9. BIRD

  AI 推荐了 9 个替代方案，却始终没点名 DEEP-PolyU/Awesome-LLM-based-Text2SQL。这就是要补上的差距。

  查看 AI 完整回答

• Metadata completeness

  pass

• README presence

  pass

• Compared to common alternatives in this category, what is the core differentiator of DEEP-PolyU/Awesome-LLM-based-Text2SQL?

  pass
  ⚠AI 未点名 DEEP-PolyU/Awesome-LLM-based-Text2SQL —— 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 DEEP-PolyU/Awesome-LLM-based-Text2SQL in production, what risks or prerequisites should they evaluate first?

  pass
  ✓AI 明确点名了 DEEP-PolyU/Awesome-LLM-based-Text2SQL

  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 DEEP-PolyU/Awesome-LLM-based-Text2SQL solve, and who is the primary audience?

  pass
  ⚠AI 未点名 DEEP-PolyU/Awesome-LLM-based-Text2SQL —— 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？