Debiased Multimodal Personality Understanding through Dual Causal Intervention

ArXi:2605.06371v1 Announce Type: new Multimodalpersonalityunderstandingplaysacriticalroleinhuman centered artificial intelligence. Previous work mainly focus on learn-ing rich multimodal representations for video personality under standing. However, they often suffer from potential harm caused by subject bias (e.g., observable age and unobservable mental states), as subjects originate from diverse graphic backgrounds. Learn ing such spurious associations between multimodal features and traits may lead to unfair personality understanding.