WISTERIA learns robust clinical representations from noisy EHR labels by enforcing consistency across multiple weak supervision views plus ontology regularization.
Generator: a long-context generative genomic foundation model
2 Pith papers cite this work. Polarity classification is still indexing.
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cs.LG 2years
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UNVERDICTED 2representative citing papers
DNA pretraining suffers from inappropriate evaluation datasets, flawed neighbor-masking, and neglected vocabulary design; the authors supply guidelines and a reproducible testbed to fix them.
citing papers explorer
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WISTERIA: Learning Clinical Representations from Noisy Supervision via Multi-View Consistency in Electronic Health Records
WISTERIA learns robust clinical representations from noisy EHR labels by enforcing consistency across multiple weak supervision views plus ontology regularization.
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In Search of Lost DNA Sequence Pretraining
DNA pretraining suffers from inappropriate evaluation datasets, flawed neighbor-masking, and neglected vocabulary design; the authors supply guidelines and a reproducible testbed to fix them.