mlsanityData to 7 Oct 2026

Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledge

arXiv 2301.01067 ↗First posted 3 Jan 2023cs.CLcited by 18

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Abstract (arXiv)

In this paper, we study the problem of knowledge-intensive text-to-SQL, in which domain knowledge is necessary to parse expert questions into SQL queries over domain-specific tables. We formalize this scenario by building a new Chinese benchmark KnowSQL consisting of domain-specific questions covering various domains. We then address this problem by presenting formulaic knowledge, rather than by annotating additional data examples. More concretely, we construct a formulaic knowledge bank as a domain knowledge base and propose a framework (ReGrouP) to leverage this formulaic knowledge during parsing. Experiments using ReGrouP demonstrate a significant 28.2% improvement overall on KnowSQL.

Key facts. Cited by 18 papers in the map (data through 7 Oct 2026). Builds on 28 of its 41 references that are in the map. First posted on arXiv 3 Jan 2023.

Builds on

28 of 41 references.

References · 28

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  7. 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. 2017Seq2SQL: Generating Structured Queries from Natural Language using Reinforcement Learningcited by 679
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  12. 2021PICARD: Parsing Incrementally for Constrained Auto-Regressive Decoding from Language Modelscited by 402
16 more
  1. 2020TaBERT: Pretraining for Joint Understanding of Textual and Tabular Datacited by 395
  2. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  3. 2019CoSQL: A Conversational Text-to-SQL Challenge Towards Cross-Domain Natural Language Interfaces to Databasescited by 180
  4. 2021Constrained Language Models Yield Few-Shot Semantic Parserscited by 162
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  8. 2020Meta-Learning for Domain Generalization in Semantic Parsingcited by 41
  9. 2021Controllable Semantic Parsing via Retrieval Augmentationcited by 35
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  11. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  12. 2020Photon: A Robust Cross-Domain Text-to-SQL Systemcited by 26
  13. 2019Don't paraphrase, detect! Rapid and Effective Data Collection for Semantic Parsingcited by 24
  14. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  15. 2021RETRONLU: Retrieval Augmented Task-Oriented Semantic Parsingcited by 15
  16. 2021On The Ingredients of an Effective Zero-shot Semantic Parsercited by 13

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Citing papers per year: 2023: 3; 2024: 7; 2025: 6; 2026: 2.

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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. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  3. 2024A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?cited by 54
  4. 2024Knowledge-to-SQL: Enhancing SQL Generation with Data Expert LLMcited by 35
  5. 2024A Survey of Table Reasoning with Large Language Modelscited by 29
  6. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  7. 2025BIRD-INTERACT: Re-imagining Text-to-SQL Evaluation for Large Language Models via Lens of Dynamic Interactionscited by 17
  8. 2024Archer: A Human-Labeled Text-to-SQL Dataset with Arithmetic, Commonsense and Hypothetical Reasoningcited by 13
  9. 2024Structure Guided Large Language Model for SQL Generationcited by 9
  10. 2025Knowledge Base Construction for Knowledge-Augmented Text-to-SQLcited by 9
  11. 2023MAGNIFICo: Evaluating the In-Context Learning Ability of Large Language Models to Generalize to Novel Interpretationscited by 7
  12. 2025LogicCat: A Chain-of-Thought Text-to-SQL Benchmark for Complex Reasoningcited by 7
6 more
  1. 2024Synthetic SQL Column Descriptions and Their Impact on Text-to-SQL Performancecited by 6
  2. 2025OraPlan-SQL: A Planning-Centric Framework for Complex Bilingual NL2SQL Reasoningcited by 3
  3. 2025Datrics Text2SQL: A Framework for Natural Language to SQL Query Generationcited by 0
  4. 2025Retrieval and Augmentation of Domain Knowledge for Text-to-SQL Semantic Parsingcited by 0
  5. 2026Bootstrapping Semantic Layer from Execution for Text-to-SQLcited by 0
  6. 2026BIRD-History: A Benchmark for History-Driven Text-to-SQL with Fine-Grained Knowledge Annotationscited by 0