Preprint
Aug 2026
Multimodal Federated Learning under Dual-Axis Modality Missingness
Flux is proposed, a multimodal federated learning framework built around two complementary components, modality-aware confidence tempering and gradient-decoupled private adaptation, that enables sample-specific, client-local confidence adaptation without allowing confidence-dependent gradients to perturb shared representation learning.
Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin et al.
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