mlsanityData to 7 Oct 2026

Photon: A Robust Cross-Domain Text-to-SQL System

arXiv 2007.15280 ↗First posted 30 Jul 2020cs.CL cs.AI cs.DBcited by 26

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Abstract (arXiv)

Natural language interfaces to databases (NLIDB) democratize end user access to relational data. Due to fundamental differences between natural language communication and programming, it is common for end users to issue questions that are ambiguous to the system or fall outside the semantic scope of its underlying query language. We present Photon, a robust, modular, cross-domain NLIDB that can flag natural language input to which a SQL mapping cannot be immediately determined. Photon consists of a strong neural semantic parser (63.2% structure accuracy on the Spider dev benchmark), a human-in-the-loop question corrector, a SQL executor and a response generator. The question corrector is a discriminative neural sequence editor which detects confusion span(s) in the input question and suggests rephrasing until a translatable input is given by the user or a maximum number of iterations are conducted. Experiments on simulated data show that the proposed method effectively improves the robustness of text-to-SQL system against untranslatable user input. The live demo of our system is available at http://naturalsql.com.

Key facts. Cited by 26 papers in the map (data through 7 Oct 2026). First posted on arXiv 30 Jul 2020.

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Citing papers per year: 2021: 8; 2022: 5; 2023: 9; 2024: 1; 2025: 2; 2026: 1.

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  1. 2021Towards Robustness of Text-to-SQL Models against Synonym Substitutioncited by 110
  2. 2021KaggleDBQA: Realistic Evaluation of Text-to-SQL Parserscited by 105
  3. 2023Exploring Chain-of-Thought Style Prompting for Text-to-SQLcited by 69
  4. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  5. 2023RobuT: A Systematic Study of Table QA Robustness Against Human-Annotated Adversarial Perturbationscited by 41
  6. 2021MWPToolkit: An Open-Source Framework for Deep Learning-Based Math Word Problem Solverscited by 39
  7. 2022Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbationcited by 28
  8. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  9. 2023Text-to-SQL Error Correction with Language Models of Codecited by 21
  10. 2021Database Reasoning Over Textcited by 20
  11. 2023Learning to Simulate Natural Language Feedback for Interactive Semantic Parsingcited by 19
  12. 2023Towards Knowledge-Intensive Text-to-SQL Semantic Parsing with Formulaic Knowledgecited by 18
14 more
  1. 2023Error Detection for Text-to-SQL Semantic Parsingcited by 11
  2. 2025SQLens: An End-to-End Framework for Error Detection and Correction in Text-to-SQLcited by 10
  3. 2021NeurIPS 2020 NLC2CMD Competition: Translating Natural Language to Bash Commandscited by 7
  4. 2021Ember: No-Code Context Enrichment via Similarity-Based Keyless Joinscited by 7
  5. 2023Multimodal Neural Databasescited by 7
  6. 2021Code Generation from Natural Language with Less Prior and More Monolingual Datacited by 6
  7. 2022Know What I don't Know: Handling Ambiguous and Unanswerable Questions for Text-to-SQLcited by 6
  8. 2023NL2CMD: An Updated Workflow for Natural Language to Bash Commands Translationcited by 3
  9. 2025Abacus-SQL: A Text-to-SQL System Empowering Cross-Domain and Open-Domain Database Retrievalcited by 3
  10. 2022On the Security Vulnerabilities of Text-to-SQL Modelscited by 2
  11. 2021Turing: an Accurate and Interpretable Multi-Hypothesis Cross-Domain Natural Language Database Interfacecited by 1
  12. 2024Understanding the Effect of Algorithm Transparency of Model Explanations in Text-to-SQL Semantic Parsingcited by 1
  13. 2022Improving Text-to-SQL Semantic Parsing with Fine-grained Query Understandingcited by 0
  14. 2026CAPER: Clause-Aligned Process Supervision for Text-to-SQLcited by 0