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To address the limitations of labeled data in vision tasks, semi-supervised learning, which utilizes readily accessible unlabeled data, can boost performance significantly. This approach can be heuristically applied to alleviate issues in few-shot learning, particularly in its semi-supervised form (Semi-FSCIL). The present body of work focusing on the Semi-FSCIL task is qui