A Comprehensive Survey on Self-Interpretable Neural Networks
Neural networks have achieved remarkable success across various fields. However, the
lack of interpretability limits their practical use, particularly in critical decision-making …
lack of interpretability limits their practical use, particularly in critical decision-making …
A review of web infodemic analysis and detection trends across multi-modalities using deep neural network
The proliferation of disinformation and misinformation across diverse digital platforms poses
a significant societal challenge. Previous work in this area adequately addresses the false …
a significant societal challenge. Previous work in this area adequately addresses the false …
Class-aware graph Siamese representation learning
C Xu, T Wang, M Chen, J Chen, Z Pan - Neurocomputing, 2025 - Elsevier
Currently, two issues exist in the field of graph Siamese representation learning. First, the
strategies for positive sample selection often impose strict constraints on the candidate set …
strategies for positive sample selection often impose strict constraints on the candidate set …
Label-aware learning to enhance unsupervised cross-domain rumor detection
H Ran, X Li, Z Zhang - Journal of Network and Computer Applications, 2025 - Elsevier
Recently, massive research has achieved significant development in improving the
performance of rumor detection. However, identifying rumors in an invisible domain is still an …
performance of rumor detection. However, identifying rumors in an invisible domain is still an …
Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection
The rapid proliferation of fake news on social media threatens social stability, creating an
urgent demand for more effective detection methods. While many promising approaches …
urgent demand for more effective detection methods. While many promising approaches …
Learning Complex Heterogeneous Multimodal Fake News via Social Latent Network Inference
M Li, Y Zhang, H Xu, X Li, C Gao, Z Wang - arxiv preprint arxiv …, 2025 - arxiv.org
With the diversification of online social platforms, news dissemination has become
increasingly complex, heterogeneous, and multimodal, making the fake news detection task …
increasingly complex, heterogeneous, and multimodal, making the fake news detection task …
Graph with Sequence: Broad-Range Semantic Modeling for Fake News Detection
The rapid proliferation of fake news on social media threatens social stability, creating an
urgent demand for more effective detection methods. While many promising approaches …
urgent demand for more effective detection methods. While many promising approaches …