mlsanityData to 7 Oct 2026

DataGpt-SQL-7B: An Open-Source Language Model for Text-to-SQL

arXiv 2409.15985 ↗First posted 24 Sep 2024cs.AIcited by 4

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Abstract (arXiv)

In addressing the pivotal role of translating natural language queries into SQL commands, we propose a suite of compact, fine-tuned models and self-refine mechanisms to democratize data access and analysis for non-expert users, mitigating risks associated with closed-source Large Language Models. Specifically, we constructed a dataset of over 20K sample for Text-to-SQL as well as the preference dateset, to improve the efficiency in the domain of SQL generation. To further ensure code validity, a code corrector was integrated into the model. Our system, DataGpt-sql, achieved 87.2% accuracy on the spider-dev, respectively, showcasing the effectiveness of our solution in text-to-SQL conversion tasks. Our code, data, and models are available at urlhttps://github.com/CainiaoTechAi/datagpt-sql-7b

Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). Builds on 18 of its 19 references that are in the map. First posted on arXiv 24 Sep 2024.

Builds on

18 of 19 references.

References · 18

  1. 2017Attention Is All You Needcited by 59,932
  2. 2022Chain-of-Thought Prompting Elicits Reasoning in Large Language Modelscited by 12,302
  3. 2022Self-Consistency Improves Chain of Thought Reasoning in Language Modelscited by 5,601
  4. 2023Qwen Technical Reportcited by 3,273
  5. 2014Sequence to Sequence Learning with Neural Networkscited by 2,974
  6. 2018Spider: A Large-Scale Human-Labeled Dataset for Complex and Cross-Domain Semantic Parsing and Text-to-SQL Taskcited by 1,120
  7. 2023DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correctioncited by 465
  8. 2019RAT-SQL: Relation-Aware Schema Encoding and Linking for Text-to-SQL Parserscited by 420
  9. 2023Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluationcited by 378
  10. 2019Towards Complex Text-to-SQL in Cross-Domain Database with Intermediate Representationcited by 210
  11. 2024CodeS: Towards Building Open-source Language Models for Text-to-SQLcited by 183
  12. 2020Semantic Evaluation for Text-to-SQL with Distilled Test Suitescited by 123
6 more
  1. 2021LGESQL: Line Graph Enhanced Text-to-SQL Model with Mixed Local and Non-Local Relationscited by 119
  2. 2022Evaluating the Text-to-SQL Capabilities of Large Language Modelscited by 101
  3. 2022RASAT: Integrating Relational Structures into Pretrained Seq2Seq Model for Text-to-SQLcited by 85
  4. 2024Synthesizing Text-to-SQL Data from Weak and Strong LLMscited by 53
  5. 2022A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directionscited by 51
  6. 2021SADGA: Structure-Aware Dual Graph Aggregation Network for Text-to-SQLcited by 43

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Cited by year

Citing papers per year: 2025: 4.

4 papers.

  1. 2025LearNAT: Learning NL2SQL with AST-guided Task Decomposition for Large Language Modelscited by 7
  2. 2025Exploring the Landscape of Text-to-SQL with Large Language Models: Progresses, Challenges and Opportunitiescited by 4
  3. 2025Schema-R1: A reasoning training approach for schema linking in Text-to-SQL Taskcited by 1
  4. 2025Lightweight Transformers for Zero-Shot and Fine-Tuned Text-to-SQL Generation Using Spidercited by 0