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LogiCode: An LLM-Driven Framework for Logical...
Journal article

LogiCode: An LLM-Driven Framework for Logical Anomaly Detection

Abstract

This paper presents LogiCode, a novel framework that leverages Large Language Models (LLMs) for identifying logical anomalies in industrial settings, moving beyond the traditional focus on structural inconsistencies. By harnessing LLMs for logical reasoning, LogiCode autonomously generates Python codes to pinpoint anomalies such as incorrect component quantities or missing elements, marking a significant leap forward in anomaly detection …

Authors

Zhang Y; Cao Y; Xu X; Shen W

Journal

IEEE Transactions on Automation Science and Engineering, Vol. 22, , pp. 7712–7723

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Publication Date

January 1, 2025

DOI

10.1109/tase.2024.3468464

ISSN

1545-5955