mlsanityData to 7 Oct 2026

Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLM

arXiv 2402.11517 ↗First posted 18 Feb 2024cs.CLcited by 35

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Abstract (arXiv)

Generating accurate SQL queries for user questions (text-to-SQL) has been a long-standing challenge since it requires a deep understanding of both the user's question and the corresponding database schema in order to retrieve the desired content accurately. Existing methods rely on the comprehensive capability of large language models (LLMs) to generate the SQL. However, some necessary knowledge is not explicitly included in the database schema and user question or has been learned by LLMs. Thus, the generated SQL of the knowledge-insufficient questions may be inaccurate, negatively influencing the text-to-SQL models' performance and robustness. To address this challenge, we propose the Knowledge-to-SQL framework, which employs tailored Data Expert LLM (DELLM) to provide helpful knowledge for all text-to-SQL models. Specifically, we introduce the detailed implementation of DELLM regarding table reading and the basic fine-tuning process. We further propose a Preference Learning via Database Feedback (PLDBF) strategy, refining the DELLM to generate more helpful knowledge for LLMs. Extensive experiments verify that DELLM can enhance the state-of-the-art approaches for text-to-SQL tasks. The corresponding code of DELLM is released for further research.

Key facts. Cited by 35 papers in the map (data through 7 Oct 2026). Builds on 27 of its 46 references that are in the map. First posted on arXiv 18 Feb 2024.

Builds on

27 of 46 references.

References · 27

  1. 2020Language Models are Few-Shot Learnerscited by 32,199
  2. 2022Training language models to follow instructions with human feedbackcited by 15,712
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2017Proximal Policy Optimization Algorithmscited by 14,441
  5. 2021LoRA: Low-Rank Adaptation of Large Language Modelscited by 14,084
  6. 2023Llama 2: Open Foundation and Fine-Tuned Chat Modelscited by 12,865
  7. 2020Retrieval-Augmented Generation for Knowledge-Intensive NLP Taskscited by 9,160
  8. 2023Direct Preference Optimization: Your Language Model is Secretly a Reward Modelcited by 7,916
  9. 2017Deep reinforcement learning from human preferencescited by 3,846
  10. 2021Finetuned Language Models Are Zero-Shot Learnerscited by 3,747
  11. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  12. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
15 more
  1. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  2. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
  3. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  4. 2022Binding Language Models in Symbolic Languagescited by 224
  5. 2023C3: Zero-shot Text-to-SQL with ChatGPTcited by 159
  6. 2023A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capabilitycited by 118
  7. 2023Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsingcited by 93
  8. 2021Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalizationcited by 92
  9. 2020Grounded Adaptation for Zero-shot Executable Semantic Parsingcited by 76
  10. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  11. 2023How to Prompt LLMs for Text-to-SQL: A Study in Zero-shot, Single-domain, and Cross-domain Settingscited by 57
  12. 2024Macro Graph Neural Networks for Online Billion-Scale Recommender Systemscited by 40
  13. 2023Exploring the Upper Limits of Text-Based Collaborative Filtering Using Large Language Models: Discoveries and Insightscited by 38
  14. 2023Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based Techniquescited by 23
  15. 2023Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledgecited by 18

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2024: 12; 2025: 16; 2026: 7.

35 papers.

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  1. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  2. 2025A Survey of Graph Retrieval-Augmented Generation for Customized Large Language Modelscited by 85
  3. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  4. 2025Text-to-CAD Generation Through Infusing Visual Feedback in Large Language Modelscited by 43
  5. 2025Arctic-Text2SQL-R1: Simple Rewards, Strong Reasoning in Text-to-SQLcited by 38
  6. 2025Table-R1: Region-based Reinforcement Learning for Table Understandingcited by 35
  7. 2025FaithfulRAG: Fact-Level Conflict Modeling for Context-Faithful Retrieval-Augmented Generationcited by 27
  8. 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 19
  9. 2024From Natural Language to SQL: Review of LLM-based Text-to-SQL Systemscited by 15
  10. 2024Structure Guided Large Language Model for SQL Generationcited by 9
  11. 2025Knapsack Optimization-based Schema Linking for LLM-based Text-to-SQL Generationcited by 9
  12. 2025Knowledge Base Construction for Knowledge-Augmented Text-to-SQLcited by 9
23 more
  1. 2024Towards Better Question Generation in QA-based Event Extractioncited by 6
  2. 2024Synthetic SQL Column Descriptions and Their Impact on Text-to-SQL Performancecited by 6
  3. 2024DAC: Decomposed Automation Correction for Text-to-SQLcited by 6
  4. 2026Arming Data Agents with Tribal Knowledgecited by 6
  5. 2024When LLMs Learn to be Students: The SOEI Framework for Modeling and Evaluating Virtual Student Agents in Educational Interactioncited by 4
  6. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  7. 2025LoSemB: Logic-Guided Semantic Bridging for Inductive Tool Retrievalcited by 3
  8. 2024Cost-efficient Knowledge-based Question Answering with Large Language Modelscited by 2
  9. 2025SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probescited by 2
  10. 2025Macro Graph of Experts for Billion-Scale Multi-Task Recommendationcited by 2
  11. 2024An Actor-Critic Approach to Boosting Text-to-SQL Large Language Modelcited by 1
  12. 2024Talking with Tables for Better LLM Factual Data Interactionscited by 1
  13. 2025ORANGE: An Online Reflection ANd GEneration framework with Domain Knowledge for Text-to-SQLcited by 1
  14. 2025Effective and Efficient Threat Hunting with Small Language Modelscited by 1
  15. 2026ErrorLLM: Modeling SQL Errors for Text-to-SQL Refinementcited by 1
  16. 2024LR-SQL: A Supervised Fine-Tuning Method for Text2SQL Tasks under Low-Resource Scenarioscited by 0
  17. 2025GradeSQL: Test-Time Inference with Outcome Reward Models for Text-to-SQL Generation from Large Language Modelscited by 0
  18. 2025Retrieval and Augmentation of Domain Knowledge for Text-to-SQL Semantic Parsingcited by 0
  19. 2026SemanticAgent: A Semantics-Aware Framework for Text-to-SQL Data Synthesiscited by 0
  20. 2026Retrieve Only Relevant Tables Whether Few or Many: Adaptive Table Retrieval Methodcited by 0
  21. 2026Bootstrapping Semantic Layer from Execution for Text-to-SQLcited by 0
  22. 2026Are These Modules Worth Their Cost? A Paradigm-Level Accuracy-Cost Analysis of In-context Learning Text-to-SQLcited by 0
  23. 2026From Question-First to Analyst-First: Domain-Expert Skills and Verified Knowledge Compilation for Proactive Enterprise Analyticscited by 0