M\"obius Interaction Filtering: Order-Selective Spectral Regularization for Multimodal Humor Detection

arXiv:2611.12913v1 Announce Type: cross Abstract: Multimodal humor detection requires interpreting language, vocal delivery, and visual behavior jointly. Expressive fusion must also regulate how interactions of different orders enter the final judgment. We propose M\"obius Interaction Filtering (MoIF), which learns a modality-subset prediction function and imposes order-selective spectral regularization through its aggregation structure. Private temporal encoders and balanced reciprocal interaction construct supervised unimodal, bimodal, and trimodal predictors. Their uniform aggregate is exac

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