Detecting Misleading Information with LLMs and Explainable ASP

Quang-Anh Nguyen, Thu-Trang Pham, Thi-Hai-yen Vuong, Van-Giang Trinh, Nguyen Ha Thanh, Nguyen Ha Thanh

2025

Abstract

Answer Set Programming (ASP) is traditionally constrained by predefined rule sets and domains, which limits the scalability of ASP systems. While Large Language Models (LLMs) exhibit remarkable capabilities in linguistic comprehension and information representation, they are limited in logical reasoning which is the notable strength of ASP. Hence, there is growing research interest in integrating LLMs with ASP to leverage these abilities. Although many models combining LLMs and ASP have demonstrated competitive results, issues related to misleading input information which directly affect the incorrect solutions produced by these models have not been adequately addressed. In this study, we propose a method integrating LLMs with explainable ASP to trace back and identify misleading segments in the provided input. Experiments conducted on the CLUTRR dataset show promising results, laying a foundation for future research on error correction to enhance the accuracy of question-answering models. Furthermore, we discuss current challenges, potential advancements, and issues related to the utilization of hybrid AI systems.

Paper Citation

in EndNote Style

TY - CONF

JO - Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART
TI - Detecting Misleading Information with LLMs and Explainable ASP
SN - 978-989-758-737-5
AU - Nguyen Q.
AU - Pham T.
AU - Vuong T.
AU - Trinh V.
AU - Thanh N.
PY - 2025
SP - 1327
EP - 1334
DO - 10.5220/0013357400003890
PB - SciTePress

in Harvard Style

Nguyen Q., Pham T., Vuong T., Trinh V. and Thanh N. (2025). Detecting Misleading Information with LLMs and Explainable ASP. In Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART; ISBN 978-989-758-737-5, SciTePress, pages 1327-1334. DOI: 10.5220/0013357400003890

in Bibtex Style

@conference{icaart25,
author={Quang-Anh Nguyen and Thu-Trang Pham and Thi-Hai-yen Vuong and Van-Giang Trinh and Nguyen Thanh},
title={Detecting Misleading Information with LLMs and Explainable ASP},
booktitle={Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 3: ICAART},
year={2025},
pages={1327-1334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0013357400003890},
isbn={978-989-758-737-5},
}