PC-MNet uses polarity-modulated attention, scalar congruity routing, and inconsistency-aware contrastive learning to achieve new state-of-the-art multimodal sarcasm detection with a 3.14% Macro-F1 gain on MUStARD.
Enhancing social media sarcasm detection using chicken swarm optimization and graph neural networks
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PC-MNet: Dual-Level Congruity Modeling for Multimodal Sarcasm Detection via Polarity-Modulated Attention
PC-MNet uses polarity-modulated attention, scalar congruity routing, and inconsistency-aware contrastive learning to achieve new state-of-the-art multimodal sarcasm detection with a 3.14% Macro-F1 gain on MUStARD.