Natural Language to SQL: State of the Art and Open Problems
Summary: Comprehensive survey/tutorial of NL→SQL in the LLM era covering dataset collection/synthesis, LLM- and agent-driven translation techniques, debugging, and multi-angle, scenario-based evaluation. Provides practitioner guidance for system selection and a research roadmap highlighting open problems in data, robustness, interpretability, evaluation, and deployment. (summarized by gpt-5-mini on Feb 09 2026)
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Authors
- 1. Yuyu Luo
- 2. Guoliang Li
- 3. Ju Fan
- 4. Chengliang Chai
- 5. Nan Tang
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| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 10,301 | LEAD: Iterative Data Selection for Efficient LLM Instruction Tuning | 2026 | VLDB | 4.1905499e-05 |
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