mlsanityData to 7 Oct 2026

RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQL

arXiv 2302.05965 ↗First posted 12 Feb 2023cs.CLcited by 191

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Abstract (arXiv)

One of the recent best attempts at Text-to-SQL is the pre-trained language model. Due to the structural property of the SQL queries, the seq2seq model takes the responsibility of parsing both the schema items (i.e., tables and columns) and the skeleton (i.e., SQL keywords). Such coupled targets increase the difficulty of parsing the correct SQL queries especially when they involve many schema items and logic operators. This paper proposes a ranking-enhanced encoding and skeleton-aware decoding framework to decouple the schema linking and the skeleton parsing. Specifically, for a seq2seq encoder-decode model, its encoder is injected by the most relevant schema items instead of the whole unordered ones, which could alleviate the schema linking effort during SQL parsing, and its decoder first generates the skeleton and then the actual SQL query, which could implicitly constrain the SQL parsing. We evaluate our proposed framework on Spider and its three robustness variants: Spider-DK, Spider-Syn, and Spider-Realistic. The experimental results show that our framework delivers promising performance and robustness. Our code is available at https://github.com/RUCKBReasoning/RESDSQL.

Key facts. Cited by 191 papers in the map (data through 7 Oct 2026). Builds on 39 of its 49 references that are in the map. First posted on arXiv 12 Feb 2023.

Builds on

39 of 49 references.

References · 39

  1. 2017Attention Is All You Needcited by 59,932
  2. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,204
  3. 2019Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformercited by 14,491
  4. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,266
  5. 2019BART: Denoising Sequence-to-Sequence Pre-training for Natural Language Generation, Translation, and Comprehensioncited by 5,874
  6. 2017Modeling Relational Data with Graph Convolutional Networkscited by 1,684
  7. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  8. 2018Self-Attention with Relative Position Representationscited by 1,112
  9. 2018Adafactor: Adaptive Learning Rates with Sublinear Memory Costcited by 896
  10. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
  11. 2019Measuring and Relieving the Over-smoothing Problem for Graph Neural Networks from the Topological Viewcited by 544
  12. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 420
27 more
  1. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
  2. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  3. 2020GraPPa: Grammar-Augmented Pre-Training for Table Semantic Parsingcited by 171
  4. 2020Compositional Generalization and Natural Language Variation: Can a Semantic Parsing Approach Handle Both?cited by 147
  5. 2020Bridging Textual and Tabular Data for Cross-Domain Text-to-SQL Semantic Parsingcited by 133
  6. 2020Structure-Grounded Pretraining for Text-to-SQLcited by 126
  7. 2020Semantic Evaluation for Text-to-SQL with Distilled Test Suitescited by 123
  8. 2021LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relationscited by 119
  9. 2021Towards Robustness of Text-to-SQL Models against Synonym Substitutioncited by 110
  10. 2020Relational Graph Attention Network for Aspect-based Sentiment Analysiscited by 104
  11. 2020When Do You Need Billions of Words of Pretraining Data?cited by 104
  12. 2017Learning a Neural Semantic Parser from User Feedbackcited by 98
  13. 2020SmBoP: Semi-autoregressive Bottom-up Semantic Parsingcited by 97
  14. 2021Exploring Underexplored Limitations of Cross-Domain Text-to-SQL Generalizationcited by 92
  15. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  16. 2018TypeSQL: Knowledge-based Type-Aware Neural Text-to-SQL Generationcited by 81
  17. 2018SyntaxSQLNet: Syntax Tree Networks for Complex and Cross-DomainText-to-SQL Taskcited by 74
  18. 2021Natural SQL: Making SQL Easier to Infer from Natural Language Specificationscited by 66
  19. 2020Learning Contextual Representations for Semantic Parsing with Generation-Augmented Pre-Trainingcited by 65
  20. 2018Robust Text-to-SQL Generation with Execution-Guided Decodingcited by 51
  21. 2019Global Reasoning over Database Structures for Text-to-SQL Parsingcited by 43
  22. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43
  23. 2020Optimizing Deeper Transformers on Small Datasetscited by 41
  24. 2022S2SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parserscited by 41
  25. 2017An Encoder-Decoder Framework Translating Natural Language to Database Queriescited by 23
  26. 2022SUN: Exploring Intrinsic Uncertainties in Text-to-SQL Parserscited by 7
  27. 2022Towards Generalizable and Robust Text-to-SQL Parsingcited by 7

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Citing papers per year: 2023: 22; 2024: 64; 2025: 60; 2026: 45.

191 papers.

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  1. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  2. 2024Retrieval-Augmented Generation for AI-Generated Content: A Surveycited by 352
  3. 2024CodeS: Towards Building Open-source Language Models for Text-to-SQLcited by 183
  4. 2024CHESS: Contextual Harnessing for Efficient SQL Synthesiscited by 164
  5. 2024Large Language Models(LLMs) on Tabular Data: Prediction, Generation, and Understanding -- A Surveycited by 157
  6. 2024CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQLcited by 132
  7. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  8. 2024MCS-SQL: Leveraging Multiple Prompts and Multiple-Choice Selection For Text-to-SQL Generationcited by 103
  9. 2025OmniSQL: Synthesizing High-quality Text-to-SQL Data at Scalecited by 90
  10. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  11. 2024Retrieval Augmented Generation (RAG) and Beyond: A Comprehensive Survey on How to Make your LLMs use External Data More Wiselycited by 65
  12. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
38 more
  1. 2024Synthesizing Text-to-SQL Data from Weak and Strong LLMscited by 53
  2. 2024Large Language Model for Table Processing: A Surveycited by 52
  3. 2024RSL-SQL: Robust Schema Linking in Text-to-SQL Generationcited by 51
  4. 2024Before Generation, Align it! A Novel and Effective Strategy for Mitigating Hallucinations in Text-to-SQL Generationcited by 49
  5. 2023Skill-Based Few-Shot Selection for In-Context Learningcited by 46
  6. 2024DTS-SQL: Decomposed Text-to-SQL with Small Large Language Modelscited by 45
  7. 2023SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)cited by 42
  8. 2023ScienceBenchmark: A Complex Real-World Benchmark for Evaluating Natural Language to SQL Systemscited by 42
  9. 2025XiYan-SQL: A Novel Multi-Generator Framework For Text-to-SQLcited by 40
  10. 2024BEAVER: An Enterprise Benchmark for Text-to-SQLcited by 37
  11. 2024FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysiscited by 35
  12. 2024E-SQL: Direct Schema Linking via Question Enrichment in Text-to-SQLcited by 35
  13. 2025LLM-JEPA: Large Language Models Meet Joint Embedding Predictive Architecturescited by 35
  14. 2024PURPLE: Making a Large Language Model a Better SQL Writercited by 34
  15. 2025ReFoRCE: A Text-to-SQL Agent with Self-Refinement, Consensus Enforcement, and Column Explorationcited by 34
  16. 2024SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Modelscited by 32
  17. 2023Benchmarking and Improving Text-to-SQL Generation under Ambiguitycited by 31
  18. 2024Decomposition for Enhancing Attention: Improving LLM-based Text-to-SQL through Workflow Paradigmcited by 31
  19. 2024Text2Cypher: Bridging Natural Language and Graph Databasescited by 30
  20. 2025Is Long Context All You Need? Leveraging LLM's Extended Context for NL2SQLcited by 30
  21. 2024A Survey of Table Reasoning with Large Language Modelscited by 29
  22. 2024StructLM: Towards Building Generalist Models for Structured Knowledge Groundingcited by 29
  23. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  24. 2024PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistencycited by 26
  25. 2023Interleaving Pre-Trained Language Models and Large Language Models for Zero-Shot NL2SQL Generationcited by 24
  26. 2023FC-KBQA: A Fine-to-Coarse Composition Framework for Knowledge Base Question Answeringcited by 21
  27. 2023Selective Demonstrations for Cross-domain Text-to-SQLcited by 21
  28. 2023Divide and Prompt: Chain of Thought Prompting for Text-to-SQLcited by 20
  29. 2023Interactive Text-to-SQL Generation via Editable Step-by-Step Explanationscited by 19
  30. 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 19
  31. 2025SQL-o1: A Self-Reward Heuristic Dynamic Search Method for Text-to-SQLcited by 19
  32. 2024Metasql: A Generate-then-Rank Framework for Natural Language to SQL Translationcited by 17
  33. 2024MSc-SQL: Multi-Sample Critiquing Small Language Models For Text-To-SQL Translationcited by 17
  34. 2024Improving Retrieval-augmented Text-to-SQL with AST-based Ranking and Schema Pruningcited by 16
  35. 2024SQL-GEN: Bridging the Dialect Gap for Text-to-SQL Via Synthetic Data And Model Mergingcited by 16
  36. 2024From Natural Language to SQL: Review of LLM-based Text-to-SQL Systemscited by 15
  37. 2025Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errorscited by 14
  38. 2024Archer: A Human-Labeled Text-to-SQL Dataset with Arithmetic, Commonsense and Hypothetical Reasoningcited by 13

50 most cited of 191 All 191 (JSON)