Responsible Detection and Mitigation of AI-Generated Text Using Hybrid Neural Networks and Feature Fusion: Toward Trustworthy Content Management in the Era of Large Language Models.

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Bibliographic Details
Title: Responsible Detection and Mitigation of AI-Generated Text Using Hybrid Neural Networks and Feature Fusion: Toward Trustworthy Content Management in the Era of Large Language Models.
Authors: Alharthi R; Department of Computer Science and Engineering, University of Hafr Al-Batin, Hafr Al-Batin, 31991 Saudi Arabia., Ojo S; Department of Electrical and Computer Engineering, College of Engineering, Anderson University, Anderson, SC USA., Nathaniel TI; School of Medicine Greenville, University of South Carolina, South Carolina, USA., Samee NA; Department of Information Technology, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, P.O. Box 84428 Saudi Arabia., Umer M; Department of Computer Science and Information Technology, The Islamia University of Bahawalpur, Bahawalpur, Pakistan., Jamjoom MM; Department of Computer Sciences, College of Computer and Information Sciences, Princess Nourah bint Abdulrahman University, Riyadh, P.O. Box 84428 Saudi Arabia., Alsubai S; Department of Computer Science, College of Computer Engineering and Sciences, Prince Sattam bin Abdulaziz University, Al-Kharj, 11942 Saudi Arabia., Khan J; School of Computing, Gachon University, Seongnam, 13120 Republic of Korea.
Source: International journal of computational intelligence systems [Int J Comput Intell Syst] 2025; Vol. 18 (1), pp. 274. Date of Electronic Publication: 2025 Nov 03.
Publication Type: Journal Article
Journal Info: Publisher: Taylor & Francis Country of Publication: England NLM ID: 9919032404006676 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1875-6883 (Electronic) Linking ISSN: 18756883 NLM ISO Abbreviation: Int J Comput Intell Syst Subsets: PubMed not MEDLINE
Database: MEDLINE Ultimate
Description
ISSN:1875-6883
DOI:10.1007/s44196-025-01025-w