label noise

Active Inference for Micro-Gesture Recognition: EFE-Guided Temporal Sampling and Adaptive Learning CVPR 2026 Better Generalizing to Unseen Concepts: An Evaluation Framework and An LLM-Based Auto-Labeled Pipeline for Biomedical Concept Recognition EACL 2026 Beyond Top Activations: Efficient and Reliable Crowdsourced Evaluation of Automated Interpretability CVPR 2026 Breaking Spurious Correlations: Uncertainty-Driven Causal Transformers for AU Detection CVPR 2026 CLEX: Complementary Label Exchange Learning for Noisy Facial Expression Recognition CVPR 2026 Client-level Active Error Correction in Distributed Learning AAAI 2026 CogniTrust: Cognitive Memory-Driven Verifiable Supervision for Robust Hashing AAAI 2026 Contrastive Cross-Bag Augmentation for Multiple Instance Learning-based Whole Slide Image Classification CVPR 2026 D^3FER: Dual Channel and Dual Branch Network for Robust Facial Expression Recognition under Dual Challenges CVPR 2026 Denoising Mixup for Regression AAAI 2026 Do We Need to Penalize Variance of Losses for Learning with Label Noise? JMLR 2026 FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels WACV 2026 FedRNC: Addressing Spatio-Temporal Label Misalignment in Federated Noisy Class-Incremental Learning AAAI 2026 Generalizing Abstention for Noise-Robust Learning in Medical Image Segmentation MIDL 2026 Graph Attention Prototypical Network for Robust Few-Shot Classification CVPR 2026 Graph-based Label-Efficient Learning: When Graph-Structured Data Meets Limited Labels AAAI 2026 High-Dimensional Analysis of Gradient Flow for Extensive-Width Quadratic Neural Networks JMLR 2026 Human-Corrected Labels Learning: Enhancing Labels Quality via Human Correction of VLMs Discrepancies AAAI 2026 Is Multi-Distribution Learning as Easy as PAC Learning: Sharp Rates with Bounded Label Noise COLT 2026 Is the Information Bottleneck Robust Enough? Towards Label-Noise Resistant Information Bottleneck Learning AAAI 2026 KaLOS finds Consensus: A Meta-Algorithm for Evaluating Inter-Annotator Agreement in Complex Vision Tasks CVPR 2026 Learning from Noisy Supervision: A Denoising-Debiasing Framework for Weakly Supervised Video Anomaly Detection CVPR 2026 Mitigating Endogenous Confirmation Bias in Noisy Label Learning for Vision-Language Models AAAI 2026 Multimodal Learning on Low-Quality Data with Conformal Predictive Self-Calibration CVPR 2026 Neighbor-aware Label Refinement: Enhancing Unreliable Instance-Dependent Partial Labels AAAI 2026