Learning Emergent Modular Representations in Multi-modality Medical Vision Foundation Models
Multi-modality medical vision (MV) foundation models (FM) are fundamentally challenged by pronounced Non-IID feature statistics across heterogeneous imaging modalities. Monolithic self-supervised optimization on such data induces conflicting gradients, driving representations to collapse toward modality-dominant shortcuts. This work reframes this failure as an imbalance between specialization and coordination in emergent modularity, and proposes Director-Experts (DEX), a modular network that explicitly regulates these dynamics in stacked modules. Each DEX module comprises a pool of experts, dynamically adapted by our image-wise activation strategy, autonomously specializing in modality-do...
| Authors | Yuting He, Chenyu You, Shuo Li |
|---|---|
| Primary category | cs.CV |
| Published | 21 May 2026 |
| Last updated at source | 21 May 2026 |
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