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	Boshen Zhang: Learning from Noisy Labels with Coarse-to-Fine Sample Credibility Modeling (Learning with Limited and Imperfect Data) View
	PNP: Robust Learning From Noisy Labels by Probabilistic Noise Prediction \| CVPR 2022 (Artificial Intelligence ) View
	SemiNLL: A Framework of Noisy-Label Learning by Semi-Supervised Learning (SemiNLL [TMLR]) View
	Label distribution for learning with Noisy labels (Sam M) View
	Video for CVPR 2023 paper (Qi Wei) View
	WSDM-23 Workshops: To Aggregate or Not Learning with Separate Noisy Labels (Association for Computing Machinery (ACM)) View
	Contrast to Divide: Self-Supervised Pre-Training for Learning with Noisy Labels (ComputerVisionFoundation Videos) View
	[CVPR 2023] Gaussian Label Distribution Learning for Spherical Image Object Detection (Philip) View
	Rabab Abdelfattah: PLMCL: Partial-Label Momentum Curriculum Learning for Multi-label Classification (Learning with Limited and Imperfect Data) View
	2.3 Knowledge Distillation \| Geoffery Hinton \| Soft Labels \| Softmax with Temperature (AI_Snippets) View