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Incompletely labeled PROTAC databases can still yield powerful predictors for protein degradation, achieving state-of-the-art performance without extensive experimental labels.
Separating long-term preferences from short-term intentions via self-supervision boosts session-based recommendation, outperforming standard fusion methods.
