mlsanityData to 14 Oct 2026

Global Reasoning over Database Structures for Text-to-SQL Parsing

arXiv 1908.11214 ↗First posted 29 Aug 2019cs.CLcited by 43

Not on the map. Why?

Abstract (arXiv)

State-of-the-art semantic parsers rely on auto-regressive decoding, emitting one symbol at a time. When tested against complex databases that are unobserved at training time (zero-shot), the parser often struggles to select the correct set of database constants in the new database, due to the local nature of decoding. In this work, we propose a semantic parser that globally reasons about the structure of the output query to make a more contextually-informed selection of database constants. We use message-passing through a graph neural network to softly select a subset of database constants for the output query, conditioned on the question. Moreover, we train a model to rank queries based on the global alignment of database constants to question words. We apply our techniques to the current state-of-the-art model for Spider, a zero-shot semantic parsing dataset with complex databases, increasing accuracy from 39.4% to 47.4%.

Key facts. Cited by 43 papers in the map (data through 14 Oct 2026). First posted on arXiv 29 Aug 2019.

Builds on

No reference list yet.

Built on by

Cited by year (2026 to 14 Oct)

Citing papers per year: 2021: 11; 2022: 10; 2023: 9; 2024: 6; 2025: 6; 2026: 1.

43 papers.

Sort:

  1. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  2. 2023RESDSQL: Decoupling Schema Linking and Skeleton Parsing for Text-to-SQLcited by 195
  3. 2024CodeS: Towards Building Open-source Language Models for Text-to-SQLcited by 187
  4. 2021LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relationscited by 119
  5. 2021Towards Robustness of Text-to-SQL Models against Synonym Substitutioncited by 110
  6. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  7. 2021Natural SQL: Making SQL Easier to Infer from Natural Language Specificationscited by 68
  8. 2025OpenSearch-SQL: Enhancing Text-to-SQL with Dynamic Few-shot and Consistency Alignmentcited by 53
  9. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 52
  10. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  11. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43
  12. 2023SQL-PaLM: Improved Large Language Model Adaptation for Text-to-SQL (extended)cited by 42
31 more
  1. 2022S2SQL: Injecting Syntax to Question-Schema Interaction Graph Encoder for Text-to-SQL Parserscited by 41
  2. 2021ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parsercited by 35
  3. 2024PURPLE: Making a Large Language Model a Better SQL Writercited by 34
  4. 2025LinkAlign: Scalable Schema Linking for Real-World Large-Scale Multi-Database Text-to-SQLcited by 29
  5. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  6. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  7. 2022HIE-SQL: History Information Enhanced Network for Context-Dependent Text-to-SQL Semantic Parsingcited by 26
  8. 2022Semantic Enhanced Text-to-SQL Parsing via Iteratively Learning Schema Linking Graphcited by 22
  9. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  10. 2025Reliable Text-to-SQL with Adaptive Abstentioncited by 20
  11. 2024Metasql: A Generate-then-Rank Framework for Natural Language to SQL Translationcited by 17
  12. 2022Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Databasecited by 16
  13. 2023Error Detection for Text-to-SQL Semantic Parsingcited by 12
  14. 2024Using LLM to select the right SQL Query from candidatescited by 12
  15. 2024Structsum Generation for Faster Text Comprehensioncited by 9
  16. 2021SPARQLing Database Queries from Intermediate Question Decompositionscited by 7
  17. 2022Towards Generalizable and Robust Text-to-SQL Parsingcited by 7
  18. 2024DAC: Decomposed Automation Correction for Text-to-SQLcited by 6
  19. 2025Graph Neural Networks for Databases: A Surveycited by 6
  20. 2025Enhancing Text2Cypher with Schema Filteringcited by 6
  21. 2021GP: Context-free Grammar Pre-training for Text-to-SQL Parserscited by 5
  22. 2021An Investigation Between Schema Linking and Text-to-SQL Performancecited by 5
  23. 2021Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQLcited by 5
  24. 2023Wav2SQL: Direct Generalizable Speech-To-SQL Parsingcited by 4
  25. 2023SQLformer: Deep Auto-Regressive Query Graph Generation for Text-to-SQL Translationcited by 3
  26. 2023Conversational Semantic Parsing using Dynamic Context Graphscited by 2
  27. 2021End-to-End Cross-Domain Text-to-SQL Semantic Parsing with Auxiliary Taskcited by 1
  28. 2023On the Structural Generalization in Text-to-SQLcited by 1
  29. 2023Decoupling SQL Query Hardness Parsing for Text-to-SQLcited by 1
  30. 2025Scaling Text2SQL via LLM-efficient Schema Filtering with Functional Dependency Graph Rerankerscited by 1
  31. 2026DRL: A Deterministic Relational Middleware Layer for Transaction-Safe Enterprise NL2SQL Under Schema-Graph Scalingcited by 0