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Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models

Muhammad Sohail Orcid Logo, Zan Hongying, Muhammad Abdullah Orcid Logo, Fabio Caraffini Orcid Logo, Arifa Javed Orcid Logo, Hassan Eshkiki Orcid Logo

Knowledge-Based Systems, Volume: 335, Start page: 115206

Swansea University Authors: Fabio Caraffini Orcid Logo, Hassan Eshkiki Orcid Logo

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DOI (Published version): 10.1016/j.knosys.2025.115206

Published in: Knowledge-Based Systems
ISSN: 0950-7051
Published: Elsevier BV 2026
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URI: https://cronfa.swan.ac.uk/Record/cronfa71166
first_indexed 2025-12-22T11:44:39Z
last_indexed 2026-01-23T06:52:03Z
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spelling 2026-01-22T11:43:48.9081678 v2 71166 2025-12-22 Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models d0b8d4e63d512d4d67a02a23dd20dfdb 0000-0001-9199-7368 Fabio Caraffini Fabio Caraffini true false c9972b26a83de11ffe211070f26fe16b 0000-0001-7795-453X Hassan Eshkiki Hassan Eshkiki true false 2025-12-22 MACS Journal Article Knowledge-Based Systems 335 115206 Elsevier BV 0950-7051 Natural language processing; Generative artificial intelligence; Large language models; AI-generated text detection; Continual learning; Elastic weight consolidation 28 2 2026 2026-02-28 10.1016/j.knosys.2025.115206 COLLEGE NANME Mathematics and Computer Science School COLLEGE CODE MACS Swansea University 2026-01-22T11:43:48.9081678 2025-12-22T11:23:53.5049869 Faculty of Science and Engineering School of Mathematics and Computer Science - Computer Science Muhammad Sohail 0000-0003-0284-4867 1 Zan Hongying 2 Muhammad Abdullah 0009-0000-9434-7977 3 Fabio Caraffini 0000-0001-9199-7368 4 Arifa Javed 0009-0002-6112-6398 5 Hassan Eshkiki 0000-0001-7795-453X 6 71166__35884__550f17498c0e470e873e4b7b898b921f.pdf AAM.pdf 2025-12-22T11:46:14.2975001 Output 8263997 application/pdf Accepted Manuscript true Author accepted manuscript document released under the terms of a Creative Commons CC-BY licence using the Swansea University Research Publications Policy (rights retention). true eng https://creativecommons.org/licenses/by/4.0/deed.en
title Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
spellingShingle Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
Fabio Caraffini
Hassan Eshkiki
title_short Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
title_full Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
title_fullStr Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
title_full_unstemmed Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
title_sort Multi-scale feature fusion-based dynamic framework using continual learning to identify text generated by multiple large language models
author_id_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb
c9972b26a83de11ffe211070f26fe16b
author_id_fullname_str_mv d0b8d4e63d512d4d67a02a23dd20dfdb_***_Fabio Caraffini
c9972b26a83de11ffe211070f26fe16b_***_Hassan Eshkiki
author Fabio Caraffini
Hassan Eshkiki
author2 Muhammad Sohail
Zan Hongying
Muhammad Abdullah
Fabio Caraffini
Arifa Javed
Hassan Eshkiki
format Journal article
container_title Knowledge-Based Systems
container_volume 335
container_start_page 115206
publishDate 2026
institution Swansea University
issn 0950-7051
doi_str_mv 10.1016/j.knosys.2025.115206
publisher Elsevier BV
college_str Faculty of Science and Engineering
hierarchytype
hierarchy_top_id facultyofscienceandengineering
hierarchy_top_title Faculty of Science and Engineering
hierarchy_parent_id facultyofscienceandengineering
hierarchy_parent_title Faculty of Science and Engineering
department_str School of Mathematics and Computer Science - Computer Science{{{_:::_}}}Faculty of Science and Engineering{{{_:::_}}}School of Mathematics and Computer Science - Computer Science
document_store_str 1
active_str 0
published_date 2026-02-28T05:34:37Z
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score 11.096027

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