SECOS enables direct semantic label prediction in open-world semi-supervised learning by aligning representations with external knowledge for novel classes, outperforming prior methods by up to 5.4% even without post-hoc matching.
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SECOS: Semantic Capture for Rigorous Classification in Open-World Semi-Supervised Learning
SECOS enables direct semantic label prediction in open-world semi-supervised learning by aligning representations with external knowledge for novel classes, outperforming prior methods by up to 5.4% even without post-hoc matching.