mlsanityData to 7 Oct 2026

The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Models

arXiv 2408.07702 ↗First posted 14 Aug 2024cs.CL cs.AI cs.IRcited by 67

On the map: LLM reasoning → Knowledge- and tool-augmented reasoning

Abstract (arXiv)

Schema linking is a crucial step in Text-to-SQL pipelines. Its goal is to retrieve the relevant tables and columns of a target database for a user's query while disregarding irrelevant ones. However, imperfect schema linking can often exclude required columns needed for accurate query generation. In this work, we revisit schema linking when using the latest generation of large language models (LLMs). We find empirically that newer models are adept at utilizing relevant schema elements during generation even in the presence of large numbers of irrelevant ones. As such, our Text-to-SQL pipeline entirely forgoes schema linking in cases where the schema fits within the model's context window in order to minimize issues due to filtering required schema elements. Furthermore, instead of filtering contextual information, we highlight techniques such as augmentation, selection, and correction, and adopt them to improve the accuracy of our Text-to-SQL pipeline. Our approach ranks first on the BIRD benchmark achieving an accuracy of 71.83%.

Key facts. Cited by 67 papers in the map (data through 7 Oct 2026). Placed in Knowledge- and tool-augmented reasoning, one of 17 directions in LLM reasoning. Builds on 31 of its 38 references that are in the map. First posted on arXiv 14 Aug 2024.

Builds on

31 of 38 references.

References · 31

  1. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  2. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  3. 2022Large Language Models are Zero-Shot Reasonerscited by 4,323
  4. 2023Reflexion: Language Agents with Verbal Reinforcement Learningcited by 4,064
  5. 2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,175
  6. 2023Tree of Thoughts: Deliberate Problem Solving with Large Language Modelscited by 3,155
  7. 2023Graph of Thoughts: Solving Elaborate Problems with Large Language Modelscited by 873
  8. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  9. 2023Plan-and-Solve Prompting: Improving Zero-Shot Chain-of-Thought Reasoning by Large Language Modelscited by 550
  10. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  11. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  12. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
19 more
  1. 2024CHESS: Contextual Harnessing for Efficient SQL Synthesiscited by 164
  2. 2024Recursive Introspection: Teaching Language Model Agents How to Self-Improvecited by 162
  3. 2023C3: Zero-shot Text-to-SQL with ChatGPTcited by 159
  4. 2023MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQLcited by 158
  5. 2020Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsingcited by 133
  6. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  7. 2024MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generationcited by 103
  8. 2024Summary of a Haystack: A Challenge to Long-Context LLMs and RAG Systemscited by 87
  9. 2024The Dawn of Natural Language to SQL: Are We Fully Ready?cited by 78
  10. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  11. 2018Robust Text-to-SQL Generation with Execution-Guided Decodingcited by 51
  12. 2024Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generationcited by 49
  13. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  14. 2024MAGIC: Generating Self-Correction Guideline for In-Context Text-to-SQLcited by 34
  15. 2020Hybrid Ranking Network for Text-to-SQLcited by 33
  16. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  17. 2019X-SQL: reinforce schema representation with contextcited by 22
  18. 2022Natural Language Interfaces to Datacited by 14
  19. 2024End-to-end Text-to-SQL Generation within an Analytics Insight Enginecited by 7

Built on by

Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 8; 2025: 41; 2026: 18.

67 papers.

Sort:

By area:

  1. 2024CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQLcited by 132
  2. 2025OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scalecited by 90
  3. 2025Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQLcited by 59
  4. 2024RSL-SQL: Robust Schema Linking in Text-to-SQL Generationcited by 51
  5. 2025OpenSearch-SQL: Enhancing Text-to-SQL with Dynamic Few-shot and Consistency Alignmentcited by 51
  6. 2025XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQLcited by 40
  7. 2024E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQLcited by 35
  8. 2025ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Consensus Enforcement, and Column Explorationcited by 34
  9. 2025Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQLcited by 30
  10. 2025LinkAlign: Scalable Schema Linking for Real-World Large-Scale Multi-Database Text-to-SQLcited by 26
  11. 2025nvAgent: Automated Data Visualization from Natural Language via Collaborative Agent Workflowcited by 21
  12. 2024MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translationcited by 17
38 more
  1. 2025How Many Instructions Can LLMs Follow at Once?cited by 17
  2. 2025BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation for Large Language Models via Lens of Dynamic Interactionscited by 17
  3. 2025AutoLink: Autonomous Schema Exploration and Expansion for Scalable Schema Linking in Text-to-SQL at Scalecited by 15
  4. 2025Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errorscited by 14
  5. 2024ROUTE: Robust Multitask Tuning and Collaboration for Text-to-SQLcited by 13
  6. 2025Cheaper, Better, Faster, Stronger: Robust Text-to-SQL without Chain-of-Thought or Fine-Tuningcited by 13
  7. 2025SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQLcited by 10
  8. 2025Tabular Data Understanding with LLMs: A Survey of Recent Advances and Challengescited by 10
  9. 2024NAT-NL2GQL: A Novel Multi-Agent Framework for Translating Natural Language to Graph Query Languagecited by 9
  10. 2025BASE-SQL: A powerful open source Text-To-SQL baseline approachcited by 9
  11. 2025Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generationcited by 9
  12. 2025Plugging Schema Graph into Multi-Table QA: A Human-Guided Framework for Reducing LLM Reliancecited by 7
  13. 2025Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotationcited by 6
  14. 2025Enhancing Text2Cypher with Schema Filteringcited by 6
  15. 2025DS-STAR: Data Science Agent for Solving Diverse Tasks across Heterogeneous Formats and Open-Ended Queriescited by 6
  16. 2024Towards Optimizing SQL Generation via LLM Routingcited by 5
  17. 2024Leveraging Prior Experience: An Expandable Auxiliary Knowledge Base for Text-to-SQLcited by 5
  18. 2025DB-Explore: Automated Database Exploration and Instruction Synthesis for Text-to-SQLcited by 5
  19. 2025SING-SQL: A Synthetic Data Generation Framework for In-Domain Text-to-SQL Translationcited by 5
  20. 2025GenEdit: Compounding Operators and Continuous Improvement to Tackle Text-to-SQL in the Enterprisecited by 4
  21. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  22. 2025SEED: Enhancing Text-to-SQL Performance and Practical Usability Through Automatic Evidence Generationcited by 4
  23. 2025RASL: Retrieval Augmented Schema Linking for Massive Database Text-to-SQLcited by 4
  24. 2025Rethinking Schema Linking: A Context-Aware Bidirectional Retrieval Approach for Text-to-SQLcited by 4
  25. 2026Structured Context Engineering for File-Native Agentic Systems: Evaluating Schema Accuracy, Format Effectiveness, and Multi-File Navigation at Scalecited by 4
  26. 2025On the Role of Feedback in Test-Time Scaling of Agentic AI Workflowscited by 3
  27. 2025Pi-SQL: Enhancing Text-to-SQL with Fine-Grained Guidance from Pivot Programming Languagescited by 3
  28. 2025Text-to-SQL for Enterprise Data Analyticscited by 3
  29. 2025MaskSQL: Safeguarding Privacy for LLM-Based Text-to-SQL via Abstractioncited by 3
  30. 2026RoboPhD: Self-Improving Text-to-SQL Through Autonomous Agent Evolutioncited by 3
  31. 2026Memo-SQL: Structured Decomposition and Experience-Driven Self-Correction for Training-Free NL2SQLcited by 3
  32. 2026Semantic Layers for Reliable LLM-Powered Data Analytics: A Paired Benchmark of Accuracy and Hallucination Across Three Frontier Modelscited by 3
  33. 2025Rationalization Models for Text-to-SQLcited by 2
  34. 2025RetrySQL: text-to-SQL training with retry data for self-correcting query generationcited by 2
  35. 2025DeKeyNLU: Enhancing Natural Language to SQL Generation through Task Decomposition and Keyword Extractioncited by 1
  36. 2025LitE-SQL: A Lightweight and Efficient Text-to-SQL Framework with Vector-based Schema Linking and Execution-Guided Self-Correctioncited by 1
  37. 2026Benchmarking Text-to-Python against Text-to-SQL: The Impact of Explicit Logic and Ambiguitycited by 1
  38. 2026Fine-Grained Table Retrieval Through the Lens of Complex Queriescited by 1

50 most cited of 67 All 67 (JSON)

Similar, not cited

Close in wording, no citation either way

  1. 2024From Natural Language to SQL: Review of LLM-based Text-to-SQL Systems
  2. 2024DFIN-SQL: Integrating Focused Schema with DIN-SQL for Superior Accuracy in Large-Scale Databases
  3. 2024Lucy: Think and Reason to Solve Text-to-SQL
  4. 2025Auto prompt sql: a resource-efficient architecture for text-to-sql translation in constrained environments
  5. 2025LLMSQL: Upgrading WikiSQL for the LLM Era of Text-to-SQL
  6. 2025ORANGE: An Online Reflection ANd GEneration framework with Domain Knowledge for Text-to-SQL
  7. 2025Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Task
  8. 2024Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruning