SchemaRAG: A Schema-aware Retrieval-Augmented Generation Framework for Text-to-SQL
Summary: Schema-aware RAG for Text-to-SQL: fine-tuned SchemaLinker distills CoT/GRPO to align NL with schema items, plus schema-conditioned example retrieval. Pareto-optimal candidate selection boosts robustness/validity, outperforming prior LLM Text-to-SQL baselines. (summarized by gpt-5-mini on Apr 11 2026)
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Authors
- 1. Di Wu (Southwest University)
- 2. Zetong Tang (Southwest University)
- 3. Yi He (College of William & Mary)
- 4. Xin Luo (Southwest University)
BibTeX Citation
@inproceedings{wu_sigmod26,
title = {{SchemaRAG: A Schema-aware Retrieval-Augmented Generation Framework for Text-to-SQL}},
author = {Wu, Di and Tang, Zetong and He, Yi and Luo, Xin},
series = {{SIGMOD} '26},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3786696},
url = {https://dl.acm.org/doi/10.1145/3786696},
year = {2026}
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Showing 3 of 3 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 756 | CodeS: Towards Building Open-source Language Models for Text-to-SQL | 2024 | SIGMOD | 0.0001431656 |
| 1,444 | CatSQL: Towards Real World Natural Language to SQL Applications | 2023 | VLDB | 0.00010769944 |
| 4,251 | FinSQL: Model-Agnostic LLMs-based Text-to-SQL Framework for Financial Analysis | 2024 | SIGMOD | 6.8031106e-05 |
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