Label Noise

CLEX: Complementary Label Exchange Learning for Noisy Facial Expression Recognition CVPR 2026 Debiased Sample Selection for Learning with Noisy Labels CVPR 2026 Do We Need to Penalize Variance of Losses for Learning with Label Noise? JMLR 2026 Drainage: A Unifying Framework for Addressing Class Uncertainty CVPR 2026 Graph Attention Prototypical Network for Robust Few-Shot Classification CVPR 2026 Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise COLT 2026 TANGO: Text-Anchored Guided Optimization for Robust Fine-tuning Vision-Language Models under Label Noise CVPR 2026 Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise UAI 2024 Learning with Structural Labels for Learning with Noisy Labels CVPR 2024 Trusted re-weighting for label distribution learning UAI 2024 Understanding and Mitigating the Label Noise in Pre-training on Downstream Tasks ICLR 2024 Adaptive Textual Label Noise Learning based on Pre-trained Models EMNLP 2023 A law of adversarial risk, interpolation, and label noise ICLR 2023 Metadata Archaeology: Unearthing Data Subsets by Leveraging Training Dynamics ICLR 2023 OT-Filter: An Optimal Transport Filter for Learning With Noisy Labels CVPR 2023 Quantifying and Mitigating the Impact of Label Errors on Model Disparity Metrics ICLR 2023 Scale-teaching: Robust Multi-scale Training for Time Series Classification with Noisy Labels NeurIPS 2023 Stochastic Feature Averaging for Learning with Long-Tailed Noisy Labels IJCAI 2023 Learning with Noisy Labels Revisited: A Study Using Real-World Human Annotations ICLR 2022 Noise Is Also Useful: Negative Correlation-Steered Latent Contrastive Learning CVPR 2022 Robustness to Label Noise Depends on the Shape of the Noise Distribution NeurIPS 2022 Uncertainty-Aware Learning against Label Noise on Imbalanced Datasets AAAI 2022 Instance-adaptive training with noise-robust losses against noisy labels EMNLP 2021 Multi-Objective Interpolation Training for Robustness To Label Noise CVPR 2021 Noise against noise: stochastic label noise helps combat inherent label noise ICLR 2021