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Semi-Supervised Learning via Weight-aware Distillation under Class Distribution Mismatch
Specifically, WAD captures adaptive weights and high-quality pseudo labels to target instances by exploring point mutual information (PMI) in representation space to maximize the role of unlabeled data and filter unknown categories.
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