Awesome-LLM-based-Text2SQL and Awesome-Text2SQL
Both are curated resource repositories covering overlapping domains (LLM-based Text-to-SQL), making them **complements** rather than competitors—a developer would likely consult both to access different survey papers, benchmarks, and open-source implementations across their combined collections.
About Awesome-LLM-based-Text2SQL
DEEP-PolyU/Awesome-LLM-based-Text2SQL
[TKDE2025] Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQL | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on large language model-based text-to-SQL.
About Awesome-Text2SQL
eosphoros-ai/Awesome-Text2SQL
Curated tutorials and resources for Large Language Models, Text2SQL, Text2DSL、Text2API、Text2Vis and more.
Maintains comprehensive leaderboards tracking performance across major benchmarks (WikiSQL, Spider, BIRD) with exact match and execution accuracy metrics, alongside organized resources covering classic models, fine-tuning techniques, datasets, and evaluation methodologies. Serves as a reference hub for both neural Text2SQL architectures and broader natural language-to-code generation patterns including DSLs, APIs, and visualizations, with curated links to libraries, datasets, and practice implementations.
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