Misinformation Detection

Misinformation detection research aims to automatically identify false or misleading information, primarily focusing on text and image-text combinations, to mitigate its societal harm. Current efforts leverage large language models (LLMs) and vision-language models (VLMs), often incorporating techniques like semi-supervised learning, knowledge distillation, and retrieval-augmented generation, to improve accuracy and explainability. This field is crucial for combating the spread of misinformation across various platforms, with ongoing research exploring diverse approaches to enhance detection capabilities and address challenges like domain adaptation and cross-modal inconsistencies.