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LogicLM: Robust Application of Large Language Models with Logic Programming for Data Analytics

  • Evgeny Skvortsov
    ,
  • Shayan Mirjafari
    ,
  • Ojaswa Garg
    ,
  • Yilin Xia
    ,
  • ,
  • Bertram Ludäscher
Research Output:
Contribution to conference
Paper

Open access

Abstract

We present LogicLM, an OLAP-style interactive data analysis system that leverages large language models (LLMs) and is configured using Logica, an enhanced logic programming language with aggregation support that compiles to SQL. LogicLM uses an LLM to translate natural language queries by end users into executable code for automatically generating data visualizations. For each natural-language query, LogicLM provides a verifiable OLAP-based configuration that users can view and modify to help ensure results are reliable and accurate. This configuration, with measures, dimensions, and filters defined as logical predicates, offers a unified and user-friendly approach to naturallanguage data exploration, while keeping end users in control of the analysis process.

Bibliographic Information

Output type

Research Output:
Contribution to conference
Paper

Original language

English

Pages from-to (Number of pages)

Pages 1086-1089 (4 pages)

Publication milestones

  • Published - 10/03/2025

Publication status

Published - 10/03/2025

Publication IDs

  • Scopus: 105007914359