Social media platforms are hubs for multimodal information exchange, encompassing text,
images, and videos, making it challenging for machines to comprehend the information or …

Large language models (LLMs) are transforming the ways the general public accesses and
consumes information. Their influence is particularly pronounced in pivotal sectors like …

Internet memes, while often humorous in nature, can be used to spread hate speech, toxic
content, and disinformation across the digital information ecosystem. As a result, detecting …

Today, detecting fake news has become challenging as anyone can interact by freely
sending or receiving electronic information. Deep learning processes to detect multimodal …

Large language models (LLMs) are transforming the ways the general public accesses and
consumes information. Their influence is particularly pronounced in pivotal sectors like …

With the COVID-19 outbreak, health-related rumors have attracted significant attention from
governments and global society. These rumors often mislead the public through multimedia …

Due to the explosive rise of multimodal content in online social communities, cross-modal
learning is crucial for accurate fake news detection. However, current multimodal fake news …

Dynamic graph learning is crucial for modeling real-world systems with evolving
relationships and temporal dynamics. However, the lack of a unified benchmark framework …

Globally, the usage of social media has significantly increased and has become the most
common way for people to deplete news. The easy sharing of multimedia content on social …

Large language models (LLMs) are transforming the ways the general public accesses and
consumes information. Their influence is particularly pronounced in pivotal sectors like …