Decoding Multimodal Cues: Unveiling the Implicit Meaning Behind Hateful Videos
Researchers have developed a new framework called IARE to improve the explainability of AI models detecting hateful videos. This framework aims to provide contextual rationales and logical reasoning alongside detection decisions, moving beyond simple binary classification. IARE utilizes multimodal chain-of-thought and Direct Preference Optimization to enhance the integration of harmful elements and the coherence of justifications. Experiments on two new datasets, Ex-HateMM and Ex-ImpliHateVid, show that IARE achieves state-of-the-art performance in both detection accuracy and rationale generation. AI
IMPACT Improves AI's ability to explain decisions in content moderation, potentially leading to more trustworthy and transparent systems.