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OmniTune

A Universal Framework for Query Refinement via LLMs

Eldar Hacohen, Yuval Moskovitch, Amit Somech

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.

שפת פרסום אנגלית
דפים 111-114
סטטוס פרסום פורסם - 22.06.2025

Keywords

database query refinement
large language models (LLMs)

ASJC Scopus subject areas

Software
Information Systems
גישה למסמך
10.1145/3722212.3725121
קבצים וקישורים אחרים
Link to publication in Scopus