label noise

Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss IJCAI 2024 Learning from Noisy Labels via Conditional Distributionally Robust Optimization NeurIPS 2024 Learning the Latent Causal Structure for Modeling Label Noise NeurIPS 2024 Learning with Structural Labels for Learning with Noisy Labels CVPR 2024 Limited-Supervised Multi-Label Learning with Dependency Noise AAAI 2024 Local Graph Clustering with Noisy Labels ICLR 2024 Make a Strong Teacher with Label Assistance: A Novel Knowledge Distillation Approach for Semantic Segmentation ECCV 2024 Mitigating Label Noise on Graphs via Topological Sample Selection ICML 2024 Mitigating Label Noise through Data Ambiguation AAAI 2024 Multi-Instance Partial-Label Learning with Margin Adjustment NeurIPS 2024 NoiseBench: Benchmarking the Impact of Real Label Noise on Named Entity Recognition EMNLP 2024 Noise Correction on Subjective Datasets ACL 2024 NoisyGL: A Comprehensive Benchmark for Graph Neural Networks under Label Noise NeurIPS 2024 On-the-fly Denoising for Data Augmentation in Natural Language Understanding EACL 2024 On the Noise Robustness of In-Context Learning for Text Generation NeurIPS 2024 On Truthing Issues in Supervised Classification JMLR 2024 Pi-DUAL: Using privileged information to distinguish clean from noisy labels ICML 2024 ProcSim: Proxy-Based Confidence for Robust Similarity Learning WACV 2024 Regroup Median Loss for Combating Label Noise AAAI 2024 Robust Heterophilic Graph Learning against Label Noise for Anomaly Detection IJCAI 2024 Robust Loss Functions for Training Decision Trees with Noisy Labels AAAI 2024 Robust Multi-Task Learning with Excess Risks ICML 2024 Robust Node Classification on Graph Data with Graph and Label Noise AAAI 2024 Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement CVPR 2024 Some Fundamental Aspects about Lipschitz Continuity of Neural Networks ICLR 2024