noisy label

Label Calibration in Source Free Domain Adaptation WACV 2025 Label Distribution Learning with Biased Annotations Assisted by Multi-Label Learning IJCAI 2025 Learning from Noisy Labels via Self-Taught On-the-Fly Meta Loss Rescaling AAAI 2025 Learning to Generate Diverse Pedestrian Movements from Web Videos with Noisy Labels ICLR 2025 Learning under Noisy Labels Spurious Points and Diverse Structures: TS40K a 3D Point Cloud Dataset of Rural Terrain and Electrical Transmission Systems WACV 2025 Learning under Temporal Label Noise ICLR 2025 Meta Label Correction with Generalization Regularizer IJCAI 2025 Meta-Learning Dynamic Center Distance: Hard Sample Mining for Learning with Noisy Labels ICCV 2025 Minding Fuzzy Regions: A Data-driven Alternating Learning Paradigm for Stable Lesion Segmentation CVPR 2025 Mixture of Experts Based Multi-Task Supervise Learning from Crowds AAAI 2025 NLPrompt: Noise-Label Prompt Learning for Vision-Language Models CVPR 2025 Noisy Label Calibration for Multi-View Classification AAAI 2025 Noisy Node Classification by Bi-level Optimization Based Multi-Teacher Distillation AAAI 2025 NUTMEG: Separating Signal From Noise in Annotator Disagreement EMNLP 2025 Optimized Gradient Clipping for Noisy Label Learning AAAI 2025 PLReMix: Combating Noisy Labels with Pseudo-Label Relaxed Contrastive Representation Learning WACV 2025 Retraining with Predicted Hard Labels Provably Increases Model Accuracy ICML 2025 Revisiting Interpolation for Noisy Label Correction AAAI 2025 Revisiting Weak-to-Strong Generalization in Theory and Practice: Reverse KL vs. Forward KL ACL 2025 Robust Self-Paced Hashing for Cross-Modal Retrieval with Noisy Labels AAAI 2025 Role-Guided Annotation and Prototype-Aligned Representation Learning for Historical Literature Sentiment Classification EMNLP 2025 S²DN: Learning to Denoise Unconvincing Knowledge for Inductive Knowledge Graph Completion AAAI 2025 Screening, Rectifying, and Re-Screening: A Unified Framework for Tuning Vision-Language Models with Noisy Labels IJCAI 2025 Theory-Inspired Deep Multi-View Multi-Label Learning with Incomplete Views and Noisy Labels CVPR 2025 Towards Real Unsupervised Anomaly Detection Via Confident Meta-Learning ICCV 2025