Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation
Summary: Systematic benchmark of prompt-engineering components (question representation, example selection/organization) and token-efficiency for LLM-based Text-to-SQL. Proposes DAIL-SQL (86.6% execution on Spider) and evaluates open-source LLMs with supervised fine-tuning, revealing accuracy/efficiency/cost trade-offs. (summarized by gpt-5-mini on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Dawei Gao (Alibaba)
- 2. Haibin Wang (Alibaba)
- 3. Yichen Qian (Alibaba)
- 4. Yaliang Li (Alibaba)
- 5. Bolin Ding (Alibaba)
- 6. Xiuyu Sun (Alibaba)
- 7. Jingren Zhou (Alibaba)
BibTeX Citation
@article{gao_vldb24,
title = {{Text-to-SQL Empowered by Large Language Models: A Benchmark Evaluation}},
author = {Gao, Dawei and Wang, Haibin and Qian, Yichen and Li, Yaliang and Ding, Bolin and Sun, Xiuyu and Zhou, Jingren},
journal = {PVLDB},
series = {{VLDB} '24},
volume = {17},
number = {5},
pages = {1132--1145},
doi = {10.14778/3641204.3641221},
url = {https://doi.org/10.14778/3641204.3641221},
year = {2024}
}Incoming Citations (Sorted by Pagerank)
Showing 50 of 67 citing papers.
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 |
|---|---|---|---|---|
| 1,750 | Duoquest: A Dual-Specification System for Expressive SQL Queries | 2020 | SIGMOD | 9.7140093e-05 |
| 1,931 | CodexDB: Synthesizing Code for Query Processing from Natural Language Instructions using GPT-3 Codex | 2022 | VLDB | 9.3449634e-05 |
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