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cs.CV2026
Leveraging Dissimilarity Invariance as a Robust Anchor for Learning with Noisy Labels
Wenxiao Fan, Kan Li
Deep learning models excel in visual recognition but suffer severe performance drops when training labels are corrupted by noise. Under label noise prior work cannot learn accurate…
cs.CV2025
Combating Semantic Contamination in Learning with Label Noise
Wenxiao Fan, Kan Li
Noisy labels can negatively impact the performance of deep neural networks. One common solution is label refurbishment, which involves reconstructing noisy labels through predictio…