mlsanityData to 7 Oct 2026

RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQL

arXiv 2205.06983 ↗First posted 14 May 2022cs.CL cs.AI cs.DBcited by 85

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Abstract (arXiv)

Relational structures such as schema linking and schema encoding have been validated as a key component to qualitatively translating natural language into SQL queries. However, introducing these structural relations comes with prices: they often result in a specialized model structure, which largely prohibits using large pretrained models in text-to-SQL. To address this problem, we propose RASAT: a Transformer seq2seq architecture augmented with relation-aware self-attention that could leverage a variety of relational structures while inheriting the pretrained parameters from the T5 model effectively. Our model can incorporate almost all types of existing relations in the literature, and in addition, we propose introducing co-reference relations for the multi-turn scenario. Experimental results on three widely used text-to-SQL datasets, covering both single-turn and multi-turn scenarios, have shown that RASAT could achieve state-of-the-art results across all three benchmarks (75.5% EX on Spider, 52.6% IEX on SParC, and 37.4% IEX on CoSQL).

Key facts. Cited by 85 papers in the map (data through 7 Oct 2026). Builds on 36 of its 44 references that are in the map. First posted on arXiv 14 May 2022.

Builds on

36 of 44 references.

References · 36

  1. 2017Attention Is All You Needcited by 59,932
  2. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  3. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  4. 2018Self-Attention with Relative Position Representationscited by 1,112
  5. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 896
  6. 2020Stanza: A Python Natural Language Processing Toolkit for Many Human Languagescited by 719
  7. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  8. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 420
  9. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
  10. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  11. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  12. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 180
24 more
  1. 2020Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?cited by 147
  2. 2019SParC: Cross-Domain Semantic Parsing in Contextcited by 141
  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
  7. 2020Relational Graph Attention Network for Aspect-based Sentiment Analysiscited by 104
  8. 2020SmBoP: Semi-autoregressive Bottom-up Semantic Parsingcited by 97
  9. 2019A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualizationcited by 88
  10. 2018TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generationcited by 81
  11. 2019Editing-Based SQL Query Generation for Cross-Domain Context-Dependent Questionscited by 80
  12. 2020Grounded Adaptation for Zero-shot Executable Semantic Parsingcited by 76
  13. 2019Representing Schema Structure with Graph Neural Networks for Text-to-SQL Parsingcited by 74
  14. 2021Natural SQL: Making SQL Easier to Infer from Natural Language Specificationscited by 66
  15. 2020RYANSQL: Recursively Applying Sketch-based Slot Fillings for Complex Text-to-SQL in Cross-Domain Databasescited by 63
  16. 2018A Survey on Semantic Parsingcited by 62
  17. 2019Global Reasoning over Database Structures for Text-to-SQL Parsingcited by 43
  18. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43
  19. 2022S2SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parserscited by 41
  20. 2020IGSQL: Database Schema Interaction Graph Based Neural Model for Context-Dependent Text-to-SQL Generationcited by 29
  21. 2022HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsingcited by 26
  22. 2019X-SQL: reinforce schema representation with contextcited by 22
  23. 2020Tracking Interaction States for Multi-Turn Text-to-SQL Semantic Parsingcited by 18
  24. 2021Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQLcited by 5

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Cited by year (2026 to 7 Oct)

Citing papers per year: 2022: 4; 2023: 31; 2024: 30; 2025: 13; 2026: 7.

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  1. 2023Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLscited by 667
  2. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  3. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  4. 2023StructGPT: A General Framework for Large Language Model to Reason over Structured Datacited by 339
  5. 2023LEVER: Learning to Verify Language-to-Code Generation with Executioncited by 228
  6. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 191
  7. 2024CHESS: Contextual Harnessing for Efficient SQL Synthesiscited by 164
  8. 2023A comprehensive evaluation of ChatGPT's zero-shot Text-to-SQL capabilitycited by 118
  9. 2024MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generationcited by 103
  10. 2023Graphix-T5: Mixing Pre-Trained Transformers with Graph-Aware Layers for Text-to-SQL Parsingcited by 93
  11. 2023Exploring Chain-of-Thought Style Prompting for Text-to-SQLcited by 69
  12. 2023Is GPT-4 a Good Data Analyst?cited by 69
38 more
  1. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  2. 2023ACT-SQL: In-Context Learning for Text-to-SQL with Automatically-Generated Chain-of-Thoughtcited by 65
  3. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  4. 2024Synthesizing Text-to-SQL Data from Weak and Strong LLMscited by 53
  5. 2024Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generationcited by 49
  6. 2023Skill-Based Few-Shot Selection for In-Context Learningcited by 46
  7. 2024DTS-SQL: Decomposed Text-to-SQL with Small Large Language Modelscited by 45
  8. 2023SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)cited by 42
  9. 2024PURPLE: Making a Large Language Model a Better SQL Writercited by 34
  10. 2024SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Modelscited by 32
  11. 2024StructLM: Towards Building Generalist Models for Structured Knowledge Groundingcited by 29
  12. 2022Importance of Synthesizing High-quality Data for Text-to-SQL Parsingcited by 27
  13. 2025LinkAlign: Scalable Schema Linking for Real-World Large-Scale Multi-Database Text-to-SQLcited by 26
  14. 2023Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generationcited by 24
  15. 2023Improving Generalization in Language Model-Based Text-to-SQL Semantic Parsing: Two Simple Semantic Boundary-Based Techniquescited by 23
  16. 2023Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrievalcited by 16
  17. 2023SQLPrompt: In-Context Text-to-SQL with Minimal Labeled Datacited by 16
  18. 2023UNITE: A Unified Benchmark for Text-to-SQL Evaluationcited by 14
  19. 2024CoE-SQL: In-Context Learning for Multi-Turn Text-to-SQL with Chain-of-Editionscited by 13
  20. 2023Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chaincited by 12
  21. 2024Using LLM to select the right SQL Query from candidatescited by 12
  22. 2024Evaluating the Data Model Robustness of Text-to-SQL Systems Based on Real User Queriescited by 12
  23. 2024TrustUQA: A Trustful Framework for Unified Structured Data Question Answeringcited by 12
  24. 2022CQR-SQL: Conversational Question Reformulation Enhanced Context-Dependent Text-to-SQL Parserscited by 11
  25. 2023Error Detection for Text-to-SQL Semantic Parsingcited by 11
  26. 2023Reboost Large Language Model-based Text-to-SQL, Text-to-Python, and Text-to-Function -- with Real Applications in Traffic Domaincited by 9
  27. 2024Structure Guided Large Language Model for SQL Generationcited by 9
  28. 2024A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challengescited by 9
  29. 2022NL2INTERFACE: Interactive Visualization Interface Generation from Natural Language Queriescited by 8
  30. 2023Adapt and Decompose: Efficient Generalization of Text-to-SQL via Domain Adapted Least-To-Most Promptingcited by 8
  31. 2024EPI-SQL: Enhancing Text-to-SQL Translation with Error-Prevention Instructionscited by 8
  32. 2025Text-to-SQL as Dual-State Reasoning: Integrating Adaptive Context and Progressive Generationcited by 8
  33. 2024SQLfuse: Enhancing Text-to-SQL Performance through Comprehensive LLM Synergycited by 7
  34. 2024Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systemscited by 6
  35. 2022MIGA: A Unified Multi-task Generation Framework for Conversational Text-to-SQLcited by 5
  36. 2024Open-SQL Framework: Enhancing Text-to-SQL on Open-source Large Language Modelscited by 5
  37. 2024EHR-SeqSQL : A Sequential Text-to-SQL Dataset For Interactively Exploring Electronic Health Recordscited by 5
  38. 2025MTSQL-R1: Towards Long-Horizon Multi-Turn Text-to-SQL via Agentic Trainingcited by 5

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