Explainable AI over the Internet of Things (IoT): Overview, state-of-the-art and future directions
SK Jagatheesaperumal, QV Pham… - IEEE Open Journal …, 2022 - ieeexplore.ieee.org
Explainable Artificial Intelligence (XAI) is transforming the field of Artificial Intelligence (AI) by
enhancing the trust of end-users in machines. As the number of connected devices keeps on …
enhancing the trust of end-users in machines. As the number of connected devices keeps on …
Explainable, domain-adaptive, and federated artificial intelligence in medicine
Artificial intelligence (AI) continues to transform data analysis in many domains. Progress in
each domain is driven by a growing body of annotated data, increased computational …
each domain is driven by a growing body of annotated data, increased computational …
The landscape of user-centered misinformation interventions-a systematic literature review
Misinformation is one of the key challenges facing society today. User-centered
misinformation interventions as digital countermeasures that exert a direct influence on …
misinformation interventions as digital countermeasures that exert a direct influence on …
[HTML][HTML] Recent Applications of Explainable AI (XAI): A Systematic Literature Review
M Saarela, V Podgorelec - Applied Sciences, 2024 - mdpi.com
This systematic literature review employs the Preferred Reporting Items for Systematic
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Reviews and Meta-Analyses (PRISMA) methodology to investigate recent applications of …
Boosting generalization of fine-tuning BERT for fake news detection
S Qin, M Zhang - Information Processing & Management, 2024 - Elsevier
Using deep neural networks to detect fake news has gradually become an extremely
important field of research. Recent studies, which adopt fine-tuning BERT to detect fake …
important field of research. Recent studies, which adopt fine-tuning BERT to detect fake …
Evaluating generalizability of fine-tuned models for fake news detection
The Covid-19 pandemic has caused a dramatic and parallel rise in dangerous
misinformation, denoted aninfodemic'by the CDC and WHO. Misinformation tied to the Covid …
misinformation, denoted aninfodemic'by the CDC and WHO. Misinformation tied to the Covid …
Report on the 2nd workshop on reducing online misinformation through credible information retrieval (romcir 2022) at ecir 2022
M Petrocchi, M Viviani - ACM SIGIR Forum, 2023 - dl.acm.org
The 2022 Workshop on Reducing Online Misinformation through Credible Information
Retrieval (ROMCIR 2022), at its Second Edition as part of the Satellite Events of the 44th …
Retrieval (ROMCIR 2022), at its Second Edition as part of the Satellite Events of the 44th …
Experiments with truth using Machine Learning: Spectral analysis and explainable classification of synthetic, false, and genuine information
VS Pendyala, M Dutta - arXiv preprint arXiv:2407.05464, 2024 - arxiv.org
Misinformation is still a major societal problem and the arrival of Large Language Models
(LLMs) only added to it. This paper analyzes synthetic, false, and genuine information in the …
(LLMs) only added to it. This paper analyzes synthetic, false, and genuine information in the …
Exploring generalizability of fine-tuned models for fake news detection
The Covid-19 pandemic has caused a dramatic and parallel rise in dangerous
misinformation, denoted an 'infodemic'by the CDC and WHO. Misinformation tied to the …
misinformation, denoted an 'infodemic'by the CDC and WHO. Misinformation tied to the …
Misinformation detection: datasets, models and performance
Purpose This paper aims to understand the characteristics of current misinformation
detection studies, including the datasets used by researchers, the computational models or …
detection studies, including the datasets used by researchers, the computational models or …