Co-occurring keywords · papers mentioning both
Papers
ε-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise
NeurIPS 2024
Can Active Label Correction Improve LLM-based Modular AI Systems?
EMNLP 2024
CoLAL: Co-learning Active Learning for Text Classification
AAAI 2024
Collaborative Refining for Learning from Inaccurate Labels
NeurIPS 2024
Confusing Pair Correction Based on Category Prototype for Domain Adaptation under Noisy Environments
AAAI 2024
DiffusionMTL: Learning Multi-Task Denoising Diffusion Model from Partially Annotated Data
CVPR 2024
Dirichlet-Based Prediction Calibration for Learning with Noisy Labels
AAAI 2024
Don’t Label Twice: Quantity Beats Quality when Comparing Binary Classifiers on a Budget
ICML 2024
Dual-Level Curriculum Meta-Learning for Noisy Few-Shot Learning Tasks
AAAI 2024
Enhancing Contrastive Learning with Noise-Guided Attack: Towards Continual Relation Extraction in the Wild
ACL 2024
Enhancing Multi-Label Text Classification under Label-Dependent Noise: A Label-Specific Denoising Framework
EMNLP 2024
Entity Alignment with Noisy Annotations from Large Language Models
NeurIPS 2024
Estimating Noisy Class Posterior with Part-level Labels for Noisy Label Learning
CVPR 2024
Federated Learning with Extremely Noisy Clients via Negative Distillation
AAAI 2024
FedLTF: Linear Probing Teaches Fine-tuning to Mitigate Noisy Labels in Federated Learning
ACML 2024
Fine-tuning Pre-trained Models for Robustness under Noisy Labels
IJCAI 2024
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLMs-Powered Assistance
ACL 2024
Identifying Label Errors in Object Detection Datasets by Loss Inspection
WACV 2024
Improving Grammatical Error Correction via Contextual Data Augmentation
ACL 2024
Information-theoretic Limits of Online Classification with Noisy Labels
NeurIPS 2024
IOFM: Using the Interpolation Technique on the Over-Fitted Models to Identify Clean-Annotated Samples
AAAI 2024
L2B: Learning to Bootstrap Robust Models for Combating Label Noise
CVPR 2024
Label Consistency-based Worker Filtering for Crowdsourcing
UAI 2024
Learning from Crowds with Dual-View K-Nearest Neighbor
UAI 2024
Learning from Noisy Labels via Conditional Distributionally Robust Optimization
NeurIPS 2024