mlsanityData to 7 Oct 2026

SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQL

arXiv 2111.00653 ↗First posted 1 Nov 2021cs.CLcited by 43

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Abstract (arXiv)

The Text-to-SQL task, aiming to translate the natural language of the questions into SQL queries, has drawn much attention recently. One of the most challenging problems of Text-to-SQL is how to generalize the trained model to the unseen database schemas, also known as the cross-domain Text-to-SQL task. The key lies in the generalizability of (i) the encoding method to model the question and the database schema and (ii) the question-schema linking method to learn the mapping between words in the question and tables/columns in the database schema. Focusing on the above two key issues, we propose a Structure-Aware Dual Graph Aggregation Network (SADGA) for cross-domain Text-to-SQL. In SADGA, we adopt the graph structure to provide a unified encoding model for both the natural language question and database schema. Based on the proposed unified modeling, we further devise a structure-aware aggregation method to learn the mapping between the question-graph and schema-graph. The structure-aware aggregation method is featured with Global Graph Linking, Local Graph Linking, and Dual-Graph Aggregation Mechanism. We not only study the performance of our proposal empirically but also achieved 3rd place on the challenging Text-to-SQL benchmark Spider at the time of writing.

Key facts. Cited by 43 papers in the map (data through 7 Oct 2026). Builds on 32 of its 46 references that are in the map. First posted on arXiv 1 Nov 2021.

Builds on

32 of 46 references.

References · 32

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  6. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
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  9. 2020TAPAS: Weakly Supervised Table Parsing via Pre-trainingcited by 432
  10. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 420
  11. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
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20 more
  1. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  2. 2020GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsingcited by 171
  3. 2017SQLNet: Generating Structured Queries From Natural Language Without Reinforcement Learningcited by 135
  4. 2020Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsingcited by 133
  5. 2020Structure-Grounded Pretraining for Text-to-SQLcited by 126
  6. 2021LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relationscited by 119
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  8. 2019A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualizationcited by 88
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  11. 2019Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsingcited by 74
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  14. 2019Global Reasoning over Database Structures for Text-to-SQL Parsingcited by 43
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  16. 2021ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parsercited by 35
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  18. 2020DuoRAT: Towards Simpler Text-to-SQL Modelscited by 17
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 9; 2023: 10; 2024: 12; 2025: 9; 2026: 3.

43 papers.

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  1. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  2. 2022Multimodal Learning with Transformers: A Surveycited by 399
  3. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  4. 2024CHESS: Contextual Harnessing for Efficient SQL Synthesiscited by 164
  5. 2024CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQLcited by 132
  6. 2023Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsingcited by 93
  7. 2025VerlTool: Towards Holistic Agentic Reinforcement Learning with Tool Usecited by 92
  8. 2025OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scalecited by 90
  9. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  10. 2025Reasoning-SQL: Reinforcement Learning with SQL Tailored Partial Rewards for Reasoning-Enhanced Text-to-SQLcited by 59
  11. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 51
  12. 2024RSL-SQL: Robust Schema Linking in Text-to-SQL Generationcited by 51
31 more
  1. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  2. 2024DTS-SQL: Decomposed Text-to-SQL with Small Large Language Modelscited by 45
  3. 2023SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)cited by 42
  4. 2024SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Modelscited by 32
  5. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  6. 2025LinkAlign: Scalable Schema Linking for Real-World Large-Scale Multi-Database Text-to-SQLcited by 26
  7. 2024Materials science in the era of large language models: a perspectivecited by 23
  8. 2024MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQLcited by 22
  9. 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 19
  10. 2025AutoLink: Autonomous Schema Exploration and Expansion for Scalable Schema Linking in Text-to-SQL at Scalecited by 15
  11. 2023Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chaincited by 12
  12. 2024EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructionscited by 8
  13. 2025Graph Neural Networks for Databases: A Surveycited by 6
  14. 2022MIGA: A Unified Multi-task Generation Framework for Conversational Text-to-SQLcited by 5
  15. 2023Wav2SQL: Direct Generalizable Speech-To-SQL Parsingcited by 4
  16. 2024DataGpt-SQL-7B: An Open-Source Language Model for Text-to-SQLcited by 4
  17. 2022FormLM: Recommending Creation Ideas for Online Forms by Modelling Semantic and Structural Informationcited by 3
  18. 2023SQLformer: Deep Auto-Regressive Query Graph Generation for Text-to-SQL Translationcited by 3
  19. 2024Enhancing LLM Fine-tuning for Text-to-SQLs by SQL Quality Measurementcited by 3
  20. 2022On the Security Vulnerabilities of Text-to-SQL Modelscited by 2
  21. 2024Can the Rookies Cut the Tough Cookie? Exploring the Use of LLMs for SQL Equivalence Checkingcited by 2
  22. 2025SDE-SQL: Enhancing Text-to-SQL Generation in Large Language Models via Self-Driven Exploration with SQL Probescited by 2
  23. 2025RetrySQL: text-to-SQL training with retry data for self-correcting query generationcited by 2
  24. 2022AskYourDB: An end-to-end system for querying and visualizing relational databases using natural languagecited by 1
  25. 2023Decoupling SQL Query Hardness Parsing for Text-to-SQLcited by 1
  26. 2024KeyInst: Keyword Instruction for Improving SQL Formulation in Text-to-SQLcited by 1
  27. 2022Searching for Better Database Queries in the Outputs of Semantic Parserscited by 0
  28. 2023Translating Natural Language Queries to SQL Using the T5 Modelcited by 0
  29. 2026Boundary-Aware NL2SQL: Integrating Reliability through Hybrid Reward and Data Synthesiscited by 0
  30. 2026LeGo-Code: Can Modular Curriculum Learning Advance Complex Code Generation? Insights from Text-to-SQLcited by 0
  31. 2026CHS-SQL: A Text-to-SQL approach based on Confidence-Guided Heuristic Search Schema Linking processcited by 0