Multimodal Misinformation

Multimodal misinformation, the spread of false information across multiple media formats (text, image, video, audio), is a growing concern demanding robust detection methods. Current research focuses on developing automated fact-checking systems using large vision-language models (LVLMs) and large language models (LLMs), often incorporating techniques like contrastive learning, knowledge distillation, and external knowledge augmentation to improve accuracy and interpretability. These advancements aim to address the challenges posed by increasingly sophisticated misinformation campaigns and contribute to the development of more resilient and trustworthy information ecosystems.