mlsanityData to 14 Oct 2026

DuoRAT: Towards Simpler Text-to-SQL Models

arXiv 2010.11119 ↗First posted 21 Oct 2020cs.CLcited by 17

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Abstract (arXiv)

Recent neural text-to-SQL models can effectively translate natural language questions to corresponding SQL queries on unseen databases. Working mostly on the Spider dataset, researchers have proposed increasingly sophisticated solutions to the problem. Contrary to this trend, in this paper we focus on simplifications. We begin by building DuoRAT, a re-implementation of the state-of-the-art RAT-SQL model that unlike RAT-SQL is using only relation-aware or vanilla transformers as the building blocks. We perform several ablation experiments using DuoRAT as the baseline model. Our experiments confirm the usefulness of some techniques and point out the redundancy of others, including structural SQL features and features that link the question with the schema.

Key facts. Cited by 17 papers in the map (data through 14 Oct 2026). First posted on arXiv 21 Oct 2020.

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Citing papers per year: 2021: 3; 2022: 7; 2023: 7.

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  1. 2023Dr.Spider: A Diagnostic Evaluation Benchmark towards Text-to-SQL Robustnesscited by 53
  2. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  3. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43
  4. 2023Benchmarking and Improving Text-to-SQL Generation under Ambiguitycited by 34
  5. 2021NL-EDIT: Correcting semantic parse errors through natural language interactioncited by 33
  6. 2022Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbationcited by 28
  7. 2021The Power of Prompt Tuning for Low-Resource Semantic Parsingcited by 21
  8. 2023SUQL: Conversational Search over Structured and Unstructured Data with Large Language Modelscited by 13
  9. 2022Non-Programmers Can Label Programs Indirectly via Active Examples: A Case Study with Text-to-SQLcited by 12
  10. 2022Diverse Parallel Data Synthesis for Cross-Database Adaptation of Text-to-SQL Parserscited by 7
  11. 2022A Copy Mechanism for Handling Knowledge Base Elements in SPARQL Neural Machine Translationcited by 4
  12. 2023Structured Case-based Reasoning for Inference-time Adaptation of Text-to-SQL parserscited by 3
5 more
  1. 2023ASTormer: An AST Structure-aware Transformer Decoder for Text-to-SQLcited by 2
  2. 2023QURG: Question Rewriting Guided Context-Dependent Text-to-SQL Semantic Parsingcited by 1
  3. 2022Faster and Better Grammar-based Text-to-SQL Parsing via Clause-level Parallel Decoding and Alignment Losscited by 0
  4. 2022SeSQL: Yet Another Large-scale Session-level Chinese Text-to-SQL Datasetcited by 0
  5. 2023dIR -- Discrete Information Retrieval: Conversational Search over Unstructured (and Structured) Data with Large Language Modelscited by 0