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Hybrid Ranking Network for Text-to-SQL

arXiv 2008.04759 ↗First posted 11 Aug 2020cs.CLcited by 33

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Abstract (arXiv)

In this paper, we study how to leverage pre-trained language models in Text-to-SQL. We argue that previous approaches under utilize the base language models by concatenating all columns together with the NL question and feeding them into the base language model in the encoding stage. We propose a neat approach called Hybrid Ranking Network (HydraNet) which breaks down the problem into column-wise ranking and decoding and finally assembles the column-wise outputs into a SQL query by straightforward rules. In this approach, the encoder is given a NL question and one individual column, which perfectly aligns with the original tasks BERT/RoBERTa is trained on, and hence we avoid any ad-hoc pooling or additional encoding layers which are necessary in prior approaches. Experiments on the WikiSQL dataset show that the proposed approach is very effective, achieving the top place on the leaderboard.

Key facts. Cited by 33 papers in the map (data through 7 Oct 2026). First posted on arXiv 11 Aug 2020.

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Citing papers per year: 2021: 8; 2022: 5; 2023: 6; 2024: 7; 2025: 6; 2026: 1.

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  1. 2024Next-Generation Database Interfaces: A Survey of LLM-based Text-to-SQLcited by 118
  2. 2024A Survey on Employing Large Language Models for Text-to-SQL Taskscited by 67
  3. 2024The Death of Schema Linking? Text-to-SQL in the Age of Well-Reasoned Language Modelscited by 67
  4. 2023Unifying the Perspectives of NLP and Software Engineering: A Survey on Language Models for Codecited by 62
  5. 2022Recent Advances in Text-to-SQL: A Survey of What We Have and What We Expectcited by 47
  6. 2021Data Augmentation with Hierarchical SQL-to-Question Generation for Cross-domain Text-to-SQL Parsingcited by 32
  7. 2024SQLBench: A Comprehensive Evaluation for Text-to-SQL Capabilities of Large Language Modelscited by 32
  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. 2024PET-SQL: A Prompt-Enhanced Two-Round Refinement of Text-to-SQL with Cross-consistencycited by 26
  11. 2021Improving Text-to-SQL with Schema Dependency Learningcited by 25
  12. 2021Dual Reader-Parser on Hybrid Textual and Tabular Evidence for Open Domain Question Answeringcited by 25
21 more
  1. 2022UniSAr: A Unified Structure-Aware Autoregressive Language Model for Text-to-SQLcited by 20
  2. 2022Uni-Parser: Unified Semantic Parser for Question Answering on Knowledge Base and Databasecited by 16
  3. 2023Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrievalcited by 16
  4. 2021mRAT-SQL+GAP:A Portuguese Text-to-SQL Transformercited by 15
  5. 2025Understanding, Detecting, and Repairing Real-World In-Context-Learning-Based Text-to-SQL Errorscited by 14
  6. 2023Retrieval-augmented GPT-3.5-based Text-to-SQL Framework with Sample-aware Prompting and Dynamic Revision Chaincited by 12
  7. 2025BASE-SQL: A powerful open source Text-To-SQL baseline approachcited by 9
  8. 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
  9. 2021Pay More Attention to History: A Context Modelling Strategy for Conversational Text-to-SQLcited by 5
  10. 2021Leveraging Table Content for Zero-shot Text-to-SQL with Meta-Learningcited by 3
  11. 2022Korean-Specific Dataset for Table Question Answeringcited by 3
  12. 2021A Mutual Information Maximization Approach for the Spurious Solution Problem in Weakly Supervised Question Answeringcited by 2
  13. 2023Enhancing Open-Domain Table Question Answering via Syntax- and Structure-aware Dense Retrievalcited by 2
  14. 2025Taming SQL Complexity: LLM-Based Equivalence Evaluation for Text-to-SQLcited by 2
  15. 2025Empowering Real-World: A Survey on the Technology, Practice, and Evaluation of LLM-driven Industry Agentscited by 2
  16. 2022Application of Deep Learning in Generating Structured Radiology Reports: A Transformer-Based Techniquecited by 0
  17. 2023Feature Representation Learning for NL2SQL Generation Based on Coupling and Decouplingcited by 0
  18. 2024AraSpider: Democratizing Arabic-to-SQLcited by 0
  19. 2025Domain Specific Question to SQL Conversion with Embedded Data Balancing Techniquecited by 0
  20. 2025Prompt Tuning for Natural Language to SQL with Embedding Fine-Tuning and RAGcited by 0
  21. 2026Beyond Static Rules: Automated Discovery of Latent Vulnerabilities in Text-to-SQLcited by 0