Combating misinformation in the age of llms: Opportunities and challenges
Misinformation such as fake news and rumors is a serious threat for information ecosystems
and public trust. The emergence of large language models (LLMs) has great potential to …
and public trust. The emergence of large language models (LLMs) has great potential to …
Adversarial attacks and defenses in deep learning: From a perspective of cybersecurity
The outstanding performance of deep neural networks has promoted deep learning
applications in a broad set of domains. However, the potential risks caused by adversarial …
applications in a broad set of domains. However, the potential risks caused by adversarial …
A survey on automated fact-checking
Fact-checking has become increasingly important due to the speed with which both
information and misinformation can spread in the modern media ecosystem. Therefore …
information and misinformation can spread in the modern media ecosystem. Therefore …
Enhancing graph neural network-based fraud detectors against camouflaged fraudsters
Graph Neural Networks (GNNs) have been widely applied to fraud detection problems in
recent years, revealing the suspiciousness of nodes by aggregating their neighborhood …
recent years, revealing the suspiciousness of nodes by aggregating their neighborhood …
Cross-modal ambiguity learning for multimodal fake news detection
Cross-modal learning is essential to enable accurate fake news detection due to the fast-
growing multimodal contents in online social communities. A fundamental challenge of …
growing multimodal contents in online social communities. A fundamental challenge of …
Temporally evolving graph neural network for fake news detection
The proliferation of fake news on social media has the probability to bring an unfavorable
impact on public opinion and social development. Many efforts have been paid to develop …
impact on public opinion and social development. Many efforts have been paid to develop …
[HTML][HTML] Deep learning for fake news detection: A comprehensive survey
The information age enables people to obtain news online through various channels, yet in
the meanwhile making false news spread at unprecedented speed. Fake news exerts …
the meanwhile making false news spread at unprecedented speed. Fake news exerts …
Rumor detection on social media with graph adversarial contrastive learning
Rumors spread through the Internet, especially on Twitter, have harmed social stability and
residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor …
residents' daily lives. Recently, in addition to utilizing the text features of posts for rumor …
Ddgcn: Dual dynamic graph convolutional networks for rumor detection on social media
Detecting rumors on social media has become particular important due to the rapid
dissemination and adverse impacts on our lives. Though a set of rumor detection models …
dissemination and adverse impacts on our lives. Though a set of rumor detection models …
Gccad: Graph contrastive coding for anomaly detection
Graph-based anomaly detection has been widely used for detecting malicious activities in
real-world applications. Existing attempts to address this problem have thus far focused on …
real-world applications. Existing attempts to address this problem have thus far focused on …