mlsanityData to 14 Oct 2026

Grammar-based Neural Text-to-SQL Generation

arXiv 1905.13326 ↗First posted 30 May 2019cs.CLcited by 23

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Abstract (arXiv)

The sequence-to-sequence paradigm employed by neural text-to-SQL models typically performs token-level decoding and does not consider generating SQL hierarchically from a grammar. Grammar-based decoding has shown significant improvements for other semantic parsing tasks, but SQL and other general programming languages have complexities not present in logical formalisms that make writing hierarchical grammars difficult. We introduce techniques to handle these complexities, showing how to construct a schema-dependent grammar with minimal over-generation. We analyze these techniques on ATIS and Spider, two challenging text-to-SQL datasets, demonstrating that they yield 14--18% relative reductions in error.

Key facts. Cited by 23 papers in the map (data through 14 Oct 2026). First posted on arXiv 30 May 2019.

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Citing papers per year: 2021: 11; 2022: 3; 2023: 1; 2024: 2; 2025: 4; 2026: 2.

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  1. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 411
  2. 2024Personal LLM Agents: Insights and Survey about the Capability, Efficiency and Securitycited by 260
  3. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 56
  4. 2021ShadowGNN: Graph Projection Neural Network for Text-to-SQL Parsercited by 35
  5. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  6. 2021The Power of Prompt Tuning for Low-Resource Semantic Parsingcited by 21
  7. 2021Zero-Shot Cross-lingual Semantic Parsingcited by 19
  8. 2022End-to-End Table Question Answering via Retrieval-Augmented Generationcited by 14
  9. 2021CLTR: An End-to-End, Transformer-Based System for Cell Level Table Retrieval and Table Question Answeringcited by 9
  10. 2021Total Recall: a Customized Continual Learning Method for Neural Semantic Parserscited by 9
  11. 2021Few-Shot Semantic Parsing for New Predicatescited by 7
  12. 2021Memory-Based Semantic Parsingcited by 6
11 more
  1. 2025Valid Text-to-SQL Generation with Unification-based DeepStochLogcited by 3
  2. 2023Correcting Semantic Parses with Natural Language through Dynamic Schema Encodingcited by 2
  3. 2021ShopTalk: A System for Conversational Faceted Searchcited by 1
  4. 2021Self-supervised Text-to-SQL Learning with Header Alignment Trainingcited by 0
  5. 2022Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understandingcited by 0
  6. 2022Searching for Better Database Queries in the Outputs of Semantic Parserscited by 0
  7. 2025GEMMA-SQL: A Novel Text-to-SQL Model Based on Large Language Modelscited by 0
  8. 2025Bridging Global Intent with Local Details: A Hierarchical Representation Approach for Semantic Validation in Text-to-SQLcited by 0
  9. 2025Companion Agents: A Table-Information Mining Paradigm for Text-to-SQLcited by 0
  10. 2026LLMON: An LLM-native Markup Language to Leverage Structure and Semantics at the LLM Interfacecited by 0
  11. 2026Natural Language Interfaces for Spatial and Temporal Databases: A Comprehensive Overview of Methods, Taxonomy, and Future Directionscited by 0