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통찰 - COCA Method for SF-UniDA
COCA: Classifier-Oriented Calibration for Source-Free Universal Domain Adaptation
COCA introduces a novel approach using textual prototypes to enhance few-shot learners in the SF-UniDA scenario.
COCA: Classifier-Oriented Calibration via Textual Prototype for Source-Free Universal Domain Adaptation
COCA method utilizes textual prototypes for few-shot learners in SF-UniDA, outperforming existing models.
