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A Comprehensive Exploration on WikiSQL with Table-Aware Word Contextualization

arXiv 1902.01069 ↗First posted 4 Feb 2019cs.CLcited by 88

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Abstract (arXiv)

We present SQLova, the first Natural-language-to-SQL (NL2SQL) model to achieve human performance in WikiSQL dataset. We revisit and discuss diverse popular methods in NL2SQL literature, take a full advantage of BERT {Devlin et al., 2018) through an effective table contextualization method, and coherently combine them, outperforming the previous state of the art by 8.2% and 2.5% in logical form and execution accuracy, respectively. We particularly note that BERT with a seq2seq decoder leads to a poor performance in the task, indicating the importance of a careful design when using such large pretrained models. We also provide a comprehensive analysis on the dataset and our model, which can be helpful for designing future NL2SQL datsets and models. We especially show that our model's performance is near the upper bound in WikiSQL, where we observe that a large portion of the evaluation errors are due to wrong annotations, and our model is already exceeding human performance by 1.3% in execution accuracy.

Key facts. Cited by 88 papers in the map (data through 7 Oct 2026). First posted on arXiv 4 Feb 2019.

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Citing papers per year: 2021: 17; 2022: 20; 2023: 15; 2024: 16; 2025: 13; 2026: 7.

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  1. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  2. 2022UnifiedSKG: Unifying and Multi-Tasking Structured Knowledge Grounding with Text-to-Text Language Modelscited by 231
  3. 2024CHASE-SQL: Multi-Path Reasoning and Preference Optimized Candidate Selection in Text-to-SQLcited by 132
  4. 2021Case-based Reasoning for Natural Language Queries over Knowledge Basescited by 107
  5. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  6. 2023Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Codecited by 62
  7. 2022Don't Generate, Discriminate: A Proposal for Grounding Language Models to Real-World Environmentscited by 57
  8. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 51
  9. 2022ArcaneQA: Dynamic Program Induction and Contextualized Encoding for Knowledge Base Question Answeringcited by 48
  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. 2023ScienceBenchmark: A Complex Real-World Benchmark for Evaluating Natural Language to SQL Systemscited by 42
38 more
  1. 2022A Survey on Table Question Answering: Recent Advancescited by 41
  2. 2024Tables as Texts or Images: Evaluating the Table Reasoning Ability of LLMs and MLLMscited by 40
  3. 2024Middleware for LLMs: Tools Are Instrumental for Language Agents in Complex Environmentscited by 39
  4. 2021Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsingcited by 32
  5. 2024SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Modelscited by 32
  6. 2021Awakening Latent Grounding from Pretrained Language Models for Semantic Parsingcited by 28
  7. 2022Towards Robustness of Text-to-SQL Models Against Natural and Realistic Adversarial Table Perturbationcited by 28
  8. 2021SeaD: End-to-end Text-to-SQL Generation with Schema-aware Denoisingcited by 27
  9. 2023Natural Language Interfaces for Tabular Data Querying and Visualization: A Surveycited by 27
  10. 2021Improving Text-to-SQL with Schema Dependency Learningcited by 25
  11. 2021Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answeringcited by 25
  12. 2022Knowledge Base Question Answering: A Semantic Parsing Perspectivecited by 22
  13. 2024MAG-SQL: Multi-Agent Generative Approach with Soft Schema Linking and Iterative Sub-SQL Refinement for Text-to-SQLcited by 22
  14. 2021Representations for Question Answering from Documents with Tables and Textcited by 21
  15. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  16. 2023Interactive Text-to-SQL Generation via Editable Step-by-Step Explanationscited by 19
  17. 2022Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Databasecited by 16
  18. 2025STaR-SQL: Self-Taught Reasoner for Text-to-SQLcited by 16
  19. 2021Dynamic Hybrid Relation Network for Cross-Domain Context-Dependent Semantic Parsingcited by 15
  20. 2025Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errorscited by 14
  21. 2022GraphQ IR: Unifying the Semantic Parsing of Graph Query Languages with One Intermediate Representationcited by 13
  22. 2023Semantic Decomposition of Question and SQL for Text-to-SQL Parsingcited by 13
  23. 2021Structured Context and High-Coverage Grammar for Conversational Question Answering over Knowledge Graphscited by 10
  24. 2024SQLucid: Grounding Natural Language Database Queries with Interactive Explanationscited by 10
  25. 2021Question Answering for Complex Electronic Health Records Database using Unified Encoder-Decoder Architecturecited by 9
  26. 2024A Survey of Large Language Model-Based Generative AI for Text-to-SQL: Benchmarks, Applications, Use Cases, and Challengescited by 9
  27. 2021Reading StackOverflow Encourages Cheating: Adding Question Text Improves Extractive Code Generationcited by 8
  28. 2022Learn from Yesterday: A Semi-Supervised Continual Learning Method for Supervision-Limited Text-to-SQL Task Streamscited by 7
  29. 2024MFORT-QA: Multi-hop Few-shot Open Rich Table Question Answeringcited by 7
  30. 2024LG AI Research & KAIST at EHRSQL 2024: Self-Training Large Language Models with Pseudo-Labeled Unanswerable Questions for a Reliable Text-to-SQL System on EHRscited by 7
  31. 2022Optimization Techniques for Unsupervised Complex Table Reasoning via Self-Training Frameworkcited by 6
  32. 2024Unmasking Database Vulnerabilities: Zero-Knowledge Schema Inference Attacks in Text-to-SQL Systemscited by 6
  33. 2025Text-to-SQL Domain Adaptation via Human-LLM Collaborative Data Annotationcited by 6
  34. 2021Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQLcited by 5
  35. 2022Unveiling the Black Box of PLMs with Semantic Anchors: Towards Interpretable Neural Semantic Parsingcited by 5
  36. 2023Parameterizing Context: Unleashing the Power of Parameter-Efficient Fine-Tuning and In-Context Tuning for Continual Table Semantic Parsingcited by 5
  37. 2022From Examples to Rules: Neural Guided Rule Synthesis for Information Extractioncited by 4
  38. 2024Redefining Information Retrieval of Structured Database via Large Language Modelscited by 4

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