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California Polytechnic State University,Computer Engineering Department,San Luis Obispo,United States
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MultiHuSE is introduced, a multi-modal dataset comprising 2,407 high-definition videos of 50 demographically diverse actors performing 1,463 text samples across four psychological humour styles (affiliative, aggressive, self-enhancing, and self-deprecating), as well as neutral content that provides empirical support for psychological theories linking humour and emotion.
Strong-modality collapse can degrade dominant modalities by over 18%, but Inverted Asymmetric Fusion preserves performance while enhancing weaker modalities.