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 …

Anomalies are rare observations (eg, data records or events) that deviate significantly from
the others in the sample. Over the past few decades, research on anomaly mining has …

The wide spread of fake news is increasingly threatening both individuals and society. Great
efforts have been made for automatic fake news detection on a single domain (eg, politics) …

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 wide dissemination of fake news is increasingly threatening both individuals and
society. Fake news detection aims to train a model on the past news and detect fake news of …

Misinformation is becoming increasingly prevalent on social media and in news articles. It
has become so widespread that we require algorithmic assistance utilising machine …

The wide spread of fake news has caused serious societal issues. We propose a subgraph
reasoning paradigm for fake news detection, which provides a crystal type of explainability …

Recent efforts in fake news detection have witnessed a surge of interest in using graph
neural networks (GNNs) to exploit rich social context. Existing studies generally leverage …

The wide spread of fake news and its negative impacts on society has attracted a lot of
attention to fake news detection. In existing fake news detection methods, particular attention …

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 …