C-Score: robust assessment for semi-supervised learning under open-world unlabeled contamination
Read the original at arxiv.org→arXiv:2608.20667v1 Announce Type: new Abstract: Pseudo-label-based semi-supervised learning has achieved strong performance due to its simplicity and scalability. However, it is typically developed under a...
Original headline: "C-Score: Beyond Accuracy for Robustness Assessment in Semi-Supervised Learning under Open-World Unlabeled Contamination"
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- Aug 24, 04:00 UTC arXiv cs.LG lead source C-Score: Beyond Accuracy for Robustness Assessment in Semi-Supervised Learning under Open-World Unlabeled Contamination