Text-To-SQL
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Benchmarks
spider
Spider 2.0
SParC
SPIDER
KaggleDBQA
2D KITTI Cars Easy
SEDE
SQL-Eval
Text-To-SQL
Most implemented
Non-local Neural Networks
Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learning
SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learning
Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Task
A Preview of XiYan-SQL: A Multi-Generator Ensemble Framework for Text-to-SQL
Content Enhanced BERT-based Text-to-SQL Generation
Papers
CogniSQL-R1-Zero: Lightweight Reinforced Reasoning for Efficient SQL Generation
Translating natural language into SQL (Text-to-SQL) remains a core challenge at the intersection of language understanding and structured data access. Although large language models (LLMs) have improved fluency, generati…
Reinforcement Learning (RL)TAGText to SQLText-To-SQLXiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQL
To leverage the advantages of LLM in addressing challenges in the Text-to-SQL task, we present XiYan-SQL, an innovative framework effectively generating and utilizing multiple SQL candidates. It consists of three compone…
Text to SQLText-To-SQLSWE-SQL: Illuminating LLM Pathways to Solve User SQL Issues in Real-World Applications
Resolution of complex SQL issues persists as a significant bottleneck in real-world database applications. Current Large Language Models (LLMs), while adept at text-to-SQL translation, have not been rigorously evaluated …
Text to SQLText-To-SQLSchema-R1: A reasoning training approach for schema linking in Text-to-SQL Task
Schema linking is a critical step in Text-to-SQL task, aiming to accurately predict the table names and column names required for the SQL query based on the given question. However, current fine-tuning approaches for sch…
reinforcement-learningReinforcement LearningText to SQLText-To-SQLBridging the Gap Between Open-Source and Proprietary LLMs in Table QA
This paper presents a system developed for SemEval 2025 Task 8: Question Answering (QA) over tabular data. Our approach integrates several key components: text-to-SQL and text-to-code generation modules, a self-correctio…
Code GenerationLanguage ModelingLanguage ModellingLarge Language Model+6LLM-Driven Data Generation and a Novel Soft Metric for Evaluating Text-to-SQL in Aviation MRO
The application of Large Language Models (LLMs) to text-to-SQL tasks promises to democratize data access, particularly in critical industries like aviation Maintenance, Repair, and Operation (MRO). However, progress is h…
Text to SQLText-To-SQL