noisy label

Debiased Sample Selection for Learning with Noisy Labels CVPR 2026 Deconstructing the Failure of Ideal Noise Correction: A Three-Pillar Diagnosis CVPR 2026 Drainage: A Unifying Framework for Addressing Class Uncertainty CVPR 2026 FedEFC: Federated Learning Using Enhanced Forward Correction Against Noisy Labels WACV 2026 FedRG: Unleashing the Representation Geometry for Federated Learning with Noisy Clients CVPR 2026 Jump-teaching: Combating Sample Selection Bias via Temporal Disagreement AAAI 2026 Meta-Guided Sample Reweighting for Robust Cross-Modal Hashing Retrieval with Noisy Labels AAAI 2026 Nested Graph Pseudo-Label Refinement for Noisy Label Domain Adaptation Learning AAAI 2026 Noise-Aware Few-Shot Learning through Bi-directional Multi-View Prompt Alignment CVPR 2026 Prototype-Guided Supervision for Graph Learning with Noisy and Sparse Labels AAAI 2026 RetFormer: Multimodal Retrieval for Enhancing Image Recognition CVPR 2026 Semantic-Consistent Bidirectional Contrastive Hashing for Noisy Multi-Label Cross-Modal Retrieval AAAI 2026 Variation-Bounded Loss for Noise-Tolerant Learning AAAI 2026 A CLIP-Powered Framework for Robust and Generalizable Data Selection ICLR 2025 A Self-Denoising Model for Robust Few-Shot Relation Extraction ACL 2025 CA2C: A Prior-Knowledge-Free Approach for Robust Label Noise Learning via Asymmetric Co-learning and Co-training ICCV 2025 D2SP: Dynamic Dual-Stage Purification Framework for Dual Noise Mitigation in Vision-based Affective Recognition. CVPR 2025 DiN: Diffusion Model for Robust Medical VQA with Semantic Noisy Labels CVPR 2025 Distribution-Consistency-Guided Multi-modal Hashing AAAI 2025 Domain-Informed Label Fusion Surpasses LLMs in Free-Living Activity Classification (Student Abstract) AAAI 2025 Energy vs. Noise: Towards Robust Temporal Action Localization in Open-World AAAI 2025 Enhanced Sample Selection with Confidence Tracking: Identifying Correctly Labeled Yet Hard-to-Learn Samples in Noisy Data AAAI 2025 Enhancing Noise-Robust Losses for Large-Scale Noisy Data Learning AAAI 2025 Enhancing Rating-Based Reinforcement Learning to Effectively Leverage Feedback from Large Vision-Language Models ICML 2025 Guiding Noisy Label Conditional Diffusion Models with Score-based Discriminator Correction ICCV 2025