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Pohang University of Science and Technology
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Achieve ensemble-level sequential recommendation performance with a single network at inference time by distilling diversity from a modular ensemble during training.
Transformer-based models trained directly on high-resolution 7T MRI data can spot MS lesions that classical methods miss, but not without introducing new challenges in boundary variability and artifact-related false positives.
