An Iterative LangGraph Agent for Text-to-SQL: Natural Language Access to the Chicago Crime Database

arXiv:2609.22917 · cs.CL, cs.AI, cs.DB · Submitted 2026-09-19 · Read on arXiv

cs.CL, cs.AI, cs.DB

Submitted: 2026-09-19

Updated: 2026-10-14

Code: https://github.com/defog-ai/sqlcoder

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Benchmark — 2× in this paper · explained in 2 episodes
• Text-to-SQL — 2× in this paper · explained in 3 episodes
• Accuracy — 1× in this paper · explained in 1 episode
• Prompt Engineering — 1× in this paper · explained in 4 episodes

Sources

• A Survey on Text-to-SQL Parsing: Concepts, Methods, and Future Directions
• A Survey of Text-to-SQL in the Era of LLMs: Where are we, and where are we going?
• A Survey on Employing Large Language Models for Text-to-SQL Tasks
• Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
• DIN-SQL: Decomposed In-Context Learning of Text-to-SQL with Self-Correction
• GPT-4 Technical Report
• MAC-SQL: A Multi-Agent Collaborative Framework for Text-to-SQL
• Can LLM Already Serve as A Database Interface? A BIg Bench for Large-Scale Database Grounded Text-to-SQLs
• Billion-scale similarity search with GPUs
• Prompting GPT-3.5 for Text-to-SQL with De-semanticization and Skeleton Retrieval
• BERTScore: Evaluating Text Generation with BERT

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