mlsanityData to 7 Oct 2026

Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expect

arXiv 2208.10099 ↗First posted 22 Aug 2022cs.CLcited by 47

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Abstract (arXiv)

Text-to-SQL has attracted attention from both the natural language processing and database communities because of its ability to convert the semantics in natural language into SQL queries and its practical application in building natural language interfaces to database systems. The major challenges in text-to-SQL lie in encoding the meaning of natural utterances, decoding to SQL queries, and translating the semantics between these two forms. These challenges have been addressed to different extents by the recent advances. However, there is still a lack of comprehensive surveys for this task. To this end, we review recent progress on text-to-SQL for datasets, methods, and evaluation and provide this systematic survey, addressing the aforementioned challenges and discussing potential future directions. We hope that this survey can serve as quick access to existing work and motivate future research.

Key facts. Cited by 47 papers in the map (data through 7 Oct 2026). Builds on 104 of its 158 references that are in the map. First posted on arXiv 22 Aug 2022.

Builds on

104 of 158 references.

References · 104

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38 more
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  16. 2020Semantic Evaluation for Text-to-SQL with Distilled Test Suitescited by 123
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Citing papers per year: 2023: 6; 2024: 19; 2025: 13; 2026: 9.

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  1. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  2. 2023MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQLcited by 158
  3. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  4. 2024The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Modelscited by 67
  5. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  6. 2024FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysiscited by 35
  7. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  8. 2025ExeSQL: Self-Taught Text-to-SQL Models with Execution-Driven Bootstrapping for SQL Dialectscited by 11
  9. 2024BookSQL: A Large Scale Text-to-SQL Dataset for Accounting Domaincited by 10
  10. 2024Auto-Cypher: Improving LLMs on Cypher generation via LLM-supervised generation-verification frameworkcited by 10
  11. 2023Reboost Large Language Model-based Text-to-SQL, Text-to-Python, and Text-to-Function -- with Real Applications in Traffic Domaincited by 9
  12. 2025ReEx-SQL: Reasoning with Execution-Aware Reinforcement Learning for Text-to-SQLcited by 8
35 more
  1. 2024R3: "This is My SQL, Are You With Me?" A Consensus-Based Multi-Agent System for Text-to-SQL Taskscited by 7
  2. 2024ProbGate at EHRSQL 2024: Enhancing SQL Query Generation Accuracy through Probabilistic Threshold Filtering and Error Handlingcited by 6
  3. 2024Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systemscited by 6
  4. 2024DAC: Decomposed Automation Correction for Text-to-SQLcited by 6
  5. 2024Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Modelscited by 5
  6. 2024SelECT-SQL: Self-correcting ensemble Chain-of-Thought for Text-to-SQLcited by 4
  7. 2025JOLT-SQL: Joint Loss Tuning of Text-to-SQL with Confusion-aware Noisy Schema Samplingcited by 4
  8. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  9. 2025Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQLcited by 4
  10. 2024AnnotatedTables: A Large Tabular Dataset with Language Model Annotationscited by 3
  11. 2024Towards Automated Data Sciences with Natural Language and SageCopilot: Practices and Lessons Learnedcited by 3
  12. 2025MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstractioncited by 3
  13. 2025OraPlan-SQL: A Planning-Centric Framework for Complex Bilingual NL2SQL Reasoningcited by 3
  14. 2024DeTriever: Decoder-representation-based Retriever for Improving NL2SQL In-Context Learningcited by 2
  15. 2025EICopilot: Search and Explore Enterprise Information over Large-scale Knowledge Graphs with LLM-driven Agentscited by 2
  16. 2026Disentangling Ambiguity from Instability in Large Language Models: A Clinical Text-to-SQL Case Studycited by 2
  17. 2023Semantic Parsing for Complex Data Retrieval: Targeting Query Plans vs. SQL for No-Code Access to Relational Databasescited by 1
  18. 2024From Text to CQL: Bridging Natural Language and Corpus Search Enginecited by 1
  19. 2024An Actor-Critic Approach to Boosting Text-to-SQL Large Language Modelcited by 1
  20. 2024Talking with Tables for Better LLM Factual Data Interactionscited by 1
  21. 2025SQLong: Enhanced NL2SQL for Longer Contexts with LLMscited by 1
  22. 2025Text-to-SQL Task-oriented Dialogue Ontology Constructioncited by 1
  23. 2026SQLStructEval: Structural Evaluation of LLM Text-to-SQL Generationcited by 1
  24. 2026EXPO-SQL: Execution-based Clause-level Policy Optimization for Text-to-SQLcited by 1
  25. 2023Translating Natural Language Queries to SQL Using the T5 Modelcited by 0
  26. 2024Evaluating Automatic Speech Recognition Systems for Korean Meteorological Expertscited by 0
  27. 2025Datrics Text2SQL: A Framework for Natural Language to SQL Query Generationcited by 0
  28. 2025HI-SQL: Optimizing Text-to-SQL Systems through Dynamic Hint Integrationcited by 0
  29. 2025GEMMA-SQL: A Novel Text-to-SQL Model Based on Large Language Modelscited by 0
  30. 2026Cluster Workload Allocation: Semantic Soft Affinity Using Natural Language Processingcited by 0
  31. 2026CAPER: Clause-Aligned Process Supervision for Text-to-SQLcited by 0
  32. 2026ACE-SQL: Adaptive Co-Optimization via Empirical Credit Assignment for Text-to-SQLcited by 0
  33. 2026ZAS-SQL: Distilling Rules from Failures for Zero-Shot Text-to-SQLcited by 0
  34. 2026Replacing Training with Memory: Listwise Selection for Text-to-SQLcited by 0
  35. 2026Auditing and Repairing LLM-as-Judge Failures in a Production Text-to-SQL Pipelinecited by 0