OmniTune: A Universal Framework for Query Refinement via LLMs
Year: 2025
Type: conference-paper
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.
Authors: Eldar Hacohen, Yuval Moskovitch, Amit Somech
Institutions: Bar-Ilan University, Ben-Gurion University of the Negev
Language: English
Subfield: Computer Networks and Communications
Field: Computer Science
Domain: Physical Sciences
Open Access status: hybrid
OpenAlex ID: W4411374416