Unsupervised Thematic Context Discovery for Explainable AI in Fact Verification: Advancing the CARAG Framework

Authors

Héctor Allende‐Cid (ORCID: https://orcid.org/0000-0003-3047-8817)
Wei Qi Yan (ORCID: https://orcid.org/0009-0006-5891-9919)
Parma Nand (ORCID: https://orcid.org/0000-0001-6853-017X)
Manju Vallayil (ORCID: https://orcid.org/0000-0003-1962-8837)

Institutions

Pontificia Universidad Católica de Valparaíso (CL)
Auckland University of Technology (NZ)
Fraunhofer Institute for Intelligent Analysis and Information Systems (DE)
Lamarr Institute for Machine Learning and Artificial Intelligence

Publication Details

Published: 2025-01-01
DOI: https://doi.org/10.5220/0013683400004000
Primary Topic: Topic Modeling
Type: article
Field-Weighted Citation Impact: 0.00

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article

Unsupervised Thematic Context Discovery for Explainable AI in Fact Verification: Advancing the CARAG Framework

Héctor Allende‐Cid, Wei Qi Yan, Parma Nand, Manju Vallayil

Jan 1, 2025

Topic Modeling

article

Unsupervised Thematic Context Discovery for Explainable AI in Fact Verification: Advancing the CARAG Framework

Héctor Allende‐Cid, Wei Qi Yan, Parma Nand, Manju Vallayil

January 1, 2025article en

Abstract

No abstract available for this paper.

Pontificia Universidad Católica de Valparaíso (CL), Auckland University of Technology (NZ), Fraunhofer Institute for Intelligent Analysis and Information Systems (DE), Lamarr Institute for Machine Learning and Artificial Intelligence

Openalex Percentile: Top 83%

Topic Modeling

DOI Open Access PDF OpenAlex

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