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 …

Fake news possesses a destructive and negative impact on our lives. With the rapid growth
of multimodal content in social media communities, multimodal fake news detection has …

Multimodal fake news detection, which aims to detect fake news across vast amounts of
multimodal data in social networks, greatly contributes to identifying potential risks on the …

As social media platforms are evolving from text-based forums into multi-modal
environments, the nature of misinformation in social media is also transforming accordingly …

Misinformation is often conveyed in multiple modalities, eg a miscaptioned image.
Multimodal misinformation is perceived as more credible by humans, and spreads faster …

Multimodal content, such as mixing text with images, presents significant challenges to
rumor detection in social media. Existing multimodal rumor detection has focused on mixing …

The popularity of online social networks has enabled rapid dissemination of information.
People now can share and consume information much more rapidly than ever before …

The creation and propagation of disinformation on social media is a growing concern. The
widespread dissemination of disinformation can have destructive effects on people's …

The explosion of multimodal fake news content on social media has sparked widespread
concern. Existing multimodal fake news detection methods have made significant …

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 …