SNIFFER: Multimodal Large Language Model for Explainable Out-of-Context Misinformation Detection

arXiv:2403.03170v1 Announce Type: cross
Abstract: Misinformation is a prevalent societal issue due to its potential high risks. Out-of-context (OOC) misinformation, where authentic images are repurposed with false text, is one of the easiest and most effective ways to mislead audiences. Current methods focus on assessing image-text consistency but lack convincing explanations for their judgments, which is essential for debunking misinformation. While Multimodal Large Language Models (MLLMs) have rich knowledge and innate capability for visual reasoning and explanation generation, they still …

abstract arxiv authentic context cs.ai cs.cl cs.cy cs.mm current detection false focus image images issue language language model large language large language model misinformation multimodal multimodal large language model risks text type