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 …

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 …

Abstract Video-Text Retrieval has been a hot research topic with the growth of multimedia
data on the internet. Transformer for video-text learning has attracted increasing attention …

Due to the rapid upgrade of social platforms, most of today's fake news is published and
spread in a multi-modal form. Most existing multi-modal fake news detection methods …

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 …

The proliferation of social networks has presented a significant challenge in combating the
pervasive issue of fake news within modern societies. Due to the large amount of …

Social media is flooded with rumors, which make fake news detection a pressing problem.
Many black-box approaches have been proposed to automatically predict the veracity of …

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

Stance detection aims to identify the stance of the text towards a target. Different from
conventional stance detection, Zero-Shot Stance Detection (ZSSD) needs to predict the …

Fake news being spread on social media platforms has a disruptive and damaging impact
on our lives. Multimedia content improves the visibility of posts more than text data but is …