ConfSMoE adds expert-opinion imputation and detaches softmax routing scores to ground-truth task confidence to relieve expert collapse in SMoE without extra load-balance losses, evaluated on four real-world datasets.
Multimodal learning with transformers: A survey
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FLAME is an MoE architecture using modality-specific routers and low-rank compression of expert knowledge to support efficient continual multimodal multi-task learning while reducing catastrophic forgetting.
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Rethinking Gating Mechanism in Sparse MoE: Handling Arbitrary Modality Inputs with Confidence-Guided Gate
ConfSMoE adds expert-opinion imputation and detaches softmax routing scores to ground-truth task confidence to relieve expert collapse in SMoE without extra load-balance losses, evaluated on four real-world datasets.