Author

Sung-Ju Lee

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Preprint Aug 2026

MedMix: Specialization-Consistent Federated Sparse MoEs under Modality Heterogeneity

MedMix is a semantic-alignment framework for federated multimodal sparse MoE architectures that coordinates cross-client routing and expert specialization using modality context, and achieves the best average F1 across diverse modality heterogeneity and modality incompleteness settings.

Adiba Orzikulova, Dong Min Kim, Jaehong Yoon et al. · 0 citations

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 represe...

Adiba Orzikulova, Jaehyun Kwak, Jaemin Shin et al. · 0 citations