OmniTune: A Universal Framework for Query Refinement via LLMs

Eldar Hacohen; Yuval Moskovitch; Amit Somech

doi:10.1145/3722212.3725121

OmniTune: A Universal Framework for Query Refinement via LLMs

Eldar Hacohen
, Yuval Moskovitch
, Amit Somech

Ben-Gurion University of the Negev

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

Abstract

Numerous studies have proposed solutions for SQL query refinement, where the goal is to make minimal adjustments to an input query to satisfy a given set of constraints. While effective, these approaches typically address specific query types and constraints, whereas, in practice, users may need to refine a diverse range of queries based on their requirements. To address this, we present OmniTune, a universal framework for query refinement. OmniTune features a Refinement Problem Wizard for defining refinement tasks in natural language and a flexible Refinement Engine, which employs an LLM-based multi-agent architecture to support any query refinement problem. We demonstrate OmniTune across various query refinement scenarios using real-world datasets.

Original language	English
Title of host publication	SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data
Editors	Amol Deshpande, Ashraf Aboulnaga, Babak Salimi, Badrish Chandramouli, Bill Howe, Boon Thau Loo, Boris Glavic, Carlo Curino, Daisy Zhe Wang, Dan Suciu, Daniel Abadi, Divesh Srivastava, Eugene Wu, Faisal Nawab, Ihab Ilyas, Jeffrey Naughton, Jennie Rogers, Jignesh Patel, Joy Arulraj, Jun Yang, Karima Echihabi, Kenneth Ross, Khuzaima Daudjee, Laks Lakshmanan, Minos Garofalakis, Mirek Riedewald, Mohamed Mokbel, Mourad Ouzzani, Oliver Kennedy, Oliver Kennedy, Paolo Papotti, Peter Alvaro, Peter Bailis, Renee Miller, Senjuti Basu Roy, Sergey Melnik, Stratos Idreos, Sudeepa Roy, Theodoros Rekatsinas, Viktor Leis, Wenchao Zhou, Wolfgang Gatterbauer, Zack Ives
Publisher	Association for Computing Machinery
Pages	111-114
Number of pages	4
ISBN (Electronic)	9798400715648
DOIs	https://doi.org/10.1145/3722212.3725121
State	Published - 22 Jun 2025
Event	2025 ACM SIGMOD/PODS International Conference on Management of Data, SIGMOD-Companion 2025 - Berlin, Germany Duration: 22 Jun 2025 → 27 Jun 2025

Publication series

Name	Proceedings of the ACM SIGMOD International Conference on Management of Data
ISSN (Print)	0730-8078

Conference

Conference	2025 ACM SIGMOD/PODS International Conference on Management of Data, SIGMOD-Companion 2025
Country/Territory	Germany
City	Berlin
Period	22/06/25 → 27/06/25

Bibliographical note

Publisher Copyright:
© 2025 Copyright held by the owner/author(s).

Keywords

database query refinement
large language models (LLMs)

Access to Document

10.1145/3722212.3725121

Cite this

Hacohen, E., Moskovitch, Y., & Somech, A. (2025). OmniTune: A Universal Framework for Query Refinement via LLMs. In A. Deshpande, A. Aboulnaga, B. Salimi, B. Chandramouli, B. Howe, B. T. Loo, B. Glavic, C. Curino, D. Zhe Wang, D. Suciu, D. Abadi, D. Srivastava, E. Wu, F. Nawab, I. Ilyas, J. Naughton, J. Rogers, J. Patel, J. Arulraj, J. Yang, K. Echihabi, K. Ross, K. Daudjee, L. Lakshmanan, M. Garofalakis, M. Riedewald, M. Mokbel, M. Ouzzani, O. Kennedy, O. Kennedy, P. Papotti, P. Alvaro, P. Bailis, R. Miller, S. B. Roy, S. Melnik, S. Idreos, S. Roy, T. Rekatsinas, V. Leis, W. Zhou, W. Gatterbauer, ... Z. Ives (Eds.), SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data (pp. 111-114). (Proceedings of the ACM SIGMOD International Conference on Management of Data). Association for Computing Machinery. https://doi.org/10.1145/3722212.3725121

Hacohen, Eldar ; Moskovitch, Yuval ; Somech, Amit. / OmniTune : A Universal Framework for Query Refinement via LLMs. SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data. editor / Amol Deshpande ; Ashraf Aboulnaga ; Babak Salimi ; Badrish Chandramouli ; Bill Howe ; Boon Thau Loo ; Boris Glavic ; Carlo Curino ; Daisy Zhe Wang ; Dan Suciu ; Daniel Abadi ; Divesh Srivastava ; Eugene Wu ; Faisal Nawab ; Ihab Ilyas ; Jeffrey Naughton ; Jennie Rogers ; Jignesh Patel ; Joy Arulraj ; Jun Yang ; Karima Echihabi ; Kenneth Ross ; Khuzaima Daudjee ; Laks Lakshmanan ; Minos Garofalakis ; Mirek Riedewald ; Mohamed Mokbel ; Mourad Ouzzani ; Oliver Kennedy ; Oliver Kennedy ; Paolo Papotti ; Peter Alvaro ; Peter Bailis ; Renee Miller ; Senjuti Basu Roy ; Sergey Melnik ; Stratos Idreos ; Sudeepa Roy ; Theodoros Rekatsinas ; Viktor Leis ; Wenchao Zhou ; Wolfgang Gatterbauer ; Zack Ives. Association for Computing Machinery, 2025. pp. 111-114 (Proceedings of the ACM SIGMOD International Conference on Management of Data).

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Hacohen, E, Moskovitch, Y & Somech, A 2025, OmniTune: A Universal Framework for Query Refinement via LLMs. in A Deshpande, A Aboulnaga, B Salimi, B Chandramouli, B Howe, BT Loo, B Glavic, C Curino, D Zhe Wang, D Suciu, D Abadi, D Srivastava, E Wu, F Nawab, I Ilyas, J Naughton, J Rogers, J Patel, J Arulraj, J Yang, K Echihabi, K Ross, K Daudjee, L Lakshmanan, M Garofalakis, M Riedewald, M Mokbel, M Ouzzani, O Kennedy, O Kennedy, P Papotti, P Alvaro, P Bailis, R Miller, SB Roy, S Melnik, S Idreos, S Roy, T Rekatsinas, V Leis, W Zhou, W Gatterbauer & Z Ives (eds), SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data. Proceedings of the ACM SIGMOD International Conference on Management of Data, Association for Computing Machinery, pp. 111-114, 2025 ACM SIGMOD/PODS International Conference on Management of Data, SIGMOD-Companion 2025, Berlin, Germany, 22/06/25. https://doi.org/10.1145/3722212.3725121

OmniTune: A Universal Framework for Query Refinement via LLMs. / Hacohen, Eldar; Moskovitch, Yuval; Somech, Amit.
SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data. ed. / Amol Deshpande; Ashraf Aboulnaga; Babak Salimi; Badrish Chandramouli; Bill Howe; Boon Thau Loo; Boris Glavic; Carlo Curino; Daisy Zhe Wang; Dan Suciu; Daniel Abadi; Divesh Srivastava; Eugene Wu; Faisal Nawab; Ihab Ilyas; Jeffrey Naughton; Jennie Rogers; Jignesh Patel; Joy Arulraj; Jun Yang; Karima Echihabi; Kenneth Ross; Khuzaima Daudjee; Laks Lakshmanan; Minos Garofalakis; Mirek Riedewald; Mohamed Mokbel; Mourad Ouzzani; Oliver Kennedy; Oliver Kennedy; Paolo Papotti; Peter Alvaro; Peter Bailis; Renee Miller; Senjuti Basu Roy; Sergey Melnik; Stratos Idreos; Sudeepa Roy; Theodoros Rekatsinas; Viktor Leis; Wenchao Zhou; Wolfgang Gatterbauer; Zack Ives. Association for Computing Machinery, 2025. p. 111-114 (Proceedings of the ACM SIGMOD International Conference on Management of Data).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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A2 - Yang, Jun

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A2 - Ross, Kenneth

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Hacohen E, Moskovitch Y, Somech A. OmniTune: A Universal Framework for Query Refinement via LLMs. In Deshpande A, Aboulnaga A, Salimi B, Chandramouli B, Howe B, Loo BT, Glavic B, Curino C, Zhe Wang D, Suciu D, Abadi D, Srivastava D, Wu E, Nawab F, Ilyas I, Naughton J, Rogers J, Patel J, Arulraj J, Yang J, Echihabi K, Ross K, Daudjee K, Lakshmanan L, Garofalakis M, Riedewald M, Mokbel M, Ouzzani M, Kennedy O, Kennedy O, Papotti P, Alvaro P, Bailis P, Miller R, Roy SB, Melnik S, Idreos S, Roy S, Rekatsinas T, Leis V, Zhou W, Gatterbauer W, Ives Z, editors, SIGMOD-Companion 2025 - Companion of the 2025 International Conference on Management of Data. Association for Computing Machinery. 2025. p. 111-114. (Proceedings of the ACM SIGMOD International Conference on Management of Data). doi: 10.1145/3722212.3725121

OmniTune: A Universal Framework for Query Refinement via LLMs

Abstract

Publication series

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Bibliographical note

Keywords

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