label noise

USDNL: Uncertainty-Based Single Dropout in Noisy Label Learning AAAI 2023 Weaker Than You Think: A Critical Look at Weakly Supervised Learning ACL 2023 When does Privileged information Explain Away Label Noise? ICML 2023 When Source-Free Domain Adaptation Meets Learning with Noisy Labels ICLR 2023 Which Examples Should be Multiply Annotated? Active Learning When Annotators May Disagree ACL 2023 Which is Better for Learning with Noisy Labels: The Semi-supervised Method or Modeling Label Noise? ICML 2023 Why Does Sharpness-Aware Minimization Generalize Better Than SGD? NeurIPS 2023 You Are What You Annotate: Towards Better Models through Annotator Representations EMNLP 2023 Addressing Out-of-Distribution Label Noise in Webly-Labelled Data WACV 2022 An Improved Baseline for Sentence-level Relation Extraction AACL 2022 An Information Fusion Approach to Learning with Instance-Dependent Label Noise ICLR 2022 A Spectral Perspective of DNN Robustness to Label Noise AISTATS 2022 ASSIST: Towards Label Noise-Robust Dialogue State Tracking ACL 2022 Beyond Images: Label Noise Transition Matrix Estimation for Tasks with Lower-Quality Features ICML 2022 Class-Dependent Label-Noise Learning with Cycle-Consistency Regularization NeurIPS 2022 CML: A Contrastive Meta Learning Method to Estimate Human Label Confidence Scores and Reduce Data Collection Cost ACL 2022 Confidence-based Reliable Learning under Dual Noises NeurIPS 2022 Estimating Instance-dependent Bayes-label Transition Matrix using a Deep Neural Network ICML 2022 Fair Classification with Instance-dependent Label Noise CLeaR 2022 Fairness with Adaptive Weights ICML 2022 FedCorr: Multi-Stage Federated Learning for Label Noise Correction CVPR 2022 Few-Shot Learning With Noisy Labels CVPR 2022 Finding Influential Instances for Distantly Supervised Relation Extraction COLING 2022 From Noisy Prediction to True Label: Noisy Prediction Calibration via Generative Model ICML 2022 GearNet: Stepwise Dual Learning for Weakly Supervised Domain Adaptation AAAI 2022