OmniTune: A Universal Framework for Query Refinement via LLMs
Summary: OmniTune is a universal framework for SQL query refinement using an LLM-based multi-agent architecture. It features a natural-language Refinement Task Wizard and a flexible Refinement Engine for diverse refinement tasks, demonstrated on real datasets. (summarized by gpt-5-nano on Feb 09 2026)
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Authors
- 1. Eldar Hacohen (Bar-Ilan University)
- 2. Yuval Moskovitch (Ben Gurion University)
- 3. Amit Somech (Bar-Ilan University)
BibTeX Citation
@inproceedings{hacohen_sigmod25,
title = {{OmniTune: A Universal Framework for Query Refinement via LLMs}},
author = {Hacohen, Eldar and Moskovitch, Yuval and Somech, Amit},
series = {{SIGMOD} '25},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/3722212.3725121},
url = {https://dl.acm.org/doi/10.1145/3722212.3725121},
year = {2025}
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| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 6,293 | Query Refinement for Diversity Constraint Satisfaction | 2024 | VLDB | 5.9247942e-05 |
| 6,389 | Query Refinement for Diverse Top-k Selection | 2024 | SIGMOD | 5.8895166e-05 |
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