Jaehyun Kwak

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.