DART is a cross-modal foundation model that delivers rope damage classification, severity regression, and few-shot recognition from a single frozen representation trained on 4270 images across 14 damage classes.
M3-jepa: Multimodal alignment via multi-gate moe based on the joint-embedding predictive architecture
3 Pith papers cite this work. Polarity classification is still indexing.
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BrainFIBRE presents a foundation model for brain microstructure that applies self-supervised partial information decomposition on NODDI maps to disentangle unique, synergistic, and redundant information and reports state-of-the-art results on multiple prediction tasks.
A literature survey that categorizes how Mixture-of-Experts architectures address multimodal learning challenges and identifies open research gaps.
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Tackling Multimodal Learning Challenges with Mixture-of-Expert: A Survey
A literature survey that categorizes how Mixture-of-Experts architectures address multimodal learning challenges and identifies open research gaps.