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label noise

569 papers

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Co-occurring keywords · papers mentioning both

noisy label (112) noisy label learning (69) deep neural network (49) semi-supervised learning (42) weakly supervised learning (41) text classification (29) image classification (27) data augmentation (24) representation learning (23) active learning (21)

Papers

Don’t Blame the Data, Blame the Model: Understanding Noise and Bias When Learning from Subjective Annotations EACL 2024 Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks AAAI 2024 Early Stopping Against Label Noise Without Validation Data ICLR 2024 Enhancing Distantly Supervised Named Entity Recognition with Strong Label Guided Lottery Training COLING 2024 Enhancing Multi-Label Text Classification under Label-Dependent Noise: A Label-Specific Denoising Framework EMNLP 2024 Enhancing Robustness of Last Layer Two-Stage Fair Model Corrections NeurIPS 2024 FedDiv: Collaborative Noise Filtering for Federated Learning with Noisy Labels AAAI 2024 Federated Label-Noise Learning with Local Diversity Product Regularization AAAI 2024 Federated Learning with Extremely Noisy Clients via Negative Distillation AAAI 2024 FedES: Federated Early-Stopping for Hindering Memorizing Heterogeneous Label Noise IJCAI 2024 Fine-tuning Pre-trained Models for Robustness under Noisy Labels IJCAI 2024 Generalization Bounds for Label Noise Stochastic Gradient Descent AISTATS 2024 Hypothesis Testing for Class-Conditional Noise Using Local Maximum Likelihood AAAI 2024 Imprecise Label Learning: A Unified Framework for Learning with Various Imprecise Label Configurations NeurIPS 2024 Improving the Robustness of Distantly-Supervised Named Entity Recognition via Uncertainty-Aware Teacher Learning and Student-Student Collaborative Learning ACL 2024 IntraMix: Intra-Class Mixup Generation for Accurate Labels and Neighbors NeurIPS 2024 Investigating the Impact of Model Width and Density on Generalization in Presence of Label Noise UAI 2024 IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples AAAI 2024 IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing NeurIPS 2024 JoAPR: Cleaning the Lens of Prompt Learning for Vision-Language Models CVPR 2024 KFNN: K-Free Nearest Neighbor For Crowdsourcing NeurIPS 2024 L2B: Learning to Bootstrap Robust Models for Combating Label Noise CVPR 2024 Label Noise: Ignorance Is Bliss NeurIPS 2024 Label-Noise Robust Diffusion Models ICLR 2024 Label Noise Robustness of Conformal Prediction JMLR 2024