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 …

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 …

Rumor spreaders are increasingly taking advantage of multimedia content to attract and
mislead news consumers on social media. Although recent multimedia rumor detection …

Rumor spreaders are increasingly utilizing multimedia content to attract the attention and
trust of news consumers. Though quite a few rumor detection models have exploited the …

False news that spreads on social media has proliferated over the past years and has led to
multi-aspect threats in the real world. While there are studies of false news on specific …

In recent years, quantum neural network (QNN) based on quantum computing has attracted
attention due to its potential for computation-acceleration and parallelism. However, the …

Stance detection improves fake information recognition in social media. This task
encourages interpreting and explaining the misinformation identification, thus aligning with …

U-Net has become baseline standard in the medical image segmentation tasks, but it has
limitations in explicitly modeling long-term dependencies. Transformer has the ability to …

With more and more messages in the form of text and image being spread on the Internet,
multi-modal rumor detection has become the focus of recent research. However, most of the …

The emerging graph Transformers have achieved impressive performance for graph
representation learning over graph neural networks (GNNs). In this work, we regard the self …