Interpretable Detection of Out-of-Context Misinformation with Neural-Symbolic-Enhanced Large Multimodal Model

arXiv:2304.07633v2 Announce Type: replace-cross
Abstract: Recent years have witnessed the sustained evolution of misinformation that aims at manipulating public opinions. Unlike traditional rumors or fake news editors who mainly rely on generated and/or counterfeited images, text and videos, current misinformation creators now more tend to use out-of-context multimedia contents (e.g. mismatched images and captions) to deceive the public and fake news detection systems. This new type of misinformation increases the difficulty of not only detection but also clarification, because every …

abstract arxiv contents context creators cs.cl cs.lg current detection editors evolution fake fake news generated images misinformation multimedia multimodal multimodal model opinions public rumors text type videos