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 …

With the advent of social media, an increasing number of netizens are sharing and reading
posts and news online. However, the huge volumes of misinformation (eg, fake news and …

The spread of rumors along with breaking events seriously hinders the truth in the era of
social media. Previous studies reveal that due to the lack of annotated resources, rumors …

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 …

While large pre-trained language models (LLMs) have shown their impressive capabilities in
various NLP tasks, they are still under-explored in the misinformation domain. In this paper …

The prevalence and perniciousness of fake news have been a critical issue on the Internet,
which stimulates the development of automatic fake news detection in turn. In this paper, we …

With the popularization of digital technology, the problem of information pollution caused by
fake news has become more common. Malicious dissemination of harmful, offensive or …

The escalating prevalence of disinformation, or “fake news,” on social media platforms
represents a growing societal concern with far-reaching implications. Its ubiquitous …

Automatic fact-checking plays a crucial role in combating the spread of misinformation.
Large Language Models (LLMs) and Instruction-Following variants, such as InstructGPT and …

The psychological factors influence the frequency and intensity of the lie's audio. In addition,
the changes could be associated with each word in a segment of the liar's output. We …