RTS+: Reliable Text to SQL
Summary: RTS+ extends reliable text-to-SQL with abstention under uncertainty, avoiding opaque, erroneous outputs. Incorporating human input for schema linking, it boosts precision and attains near-perfect results on standard T-SQL benchmarks. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
No non-self incoming citations found for this paper in this database.
Authors
- 1. Kaiwen Chen (University of Toronto)
- 2. Yueting Chen (Seattle University)
- 3. Nick Koudas (University of Toronto)
- 4. Xiaohui Yu (York University)
BibTeX Citation
@inproceedings{chen_sigmod25,
title = {{RTS+: Reliable Text to SQL}},
author = {Chen, Kaiwen and Chen, Yueting and Koudas, Nick and Yu, Xiaohui},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725129},
url = {https://dl.acm.org/doi/10.1145/3722212.3725129},
year = {2025}
}Incoming Citations (Sorted by Pagerank)
Showing 0 of 0 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|
Previous
Page 1 / 1
Next
Outgoing Citations (Sorted by Pagerank)
Showing 2 of 2 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 |
| 6,936 | Reliable Text-to-SQL with Adaptive Abstention | 2025 | SIGMOD | 5.7349543e-05 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,499 | SchemaRAG: A Schema-aware Retrieval-Augmented Generation Framework for Text-to-SQL | 2026 | SIGMOD |
| 2 | 865 | Natural language to SQL: Where are we today? | 2020 | VLDB |
| 3 | 2,602 | NL2SQL is a solved problem... Not! | 2024 | CIDR |
| 4 | 10,398 | Reliable Answers for Recurring Questions: Boosting Text-to-SQL Accuracy with Template Constrained Decoding | 2026 | SIGMOD |
| 5 | 9,305 | The Power of Constraints in Natural Language to SQL Translation | 2025 | VLDB |
| 6 | 279 | Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation | 2024 | VLDB |
| 7 | 3,787 | Combining Small Language Models and Large Language Models for Zero-Shot NL2SQL | 2024 | VLDB |
| 8 | 10,510 | NL2SQLBench: A Modular Benchmarking Framework for LLM-Enabled NL2SQL Solutions | 2026 | VLDB |
| 9 | 9,870 | Natural Language to SQL: State of the Art and Open Problems | 2025 | VLDB |
| 10 | 6,936 | Reliable Text-to-SQL with Adaptive Abstention | 2025 | SIGMOD |