Co-occurring keywords · papers mentioning both
Papers
Collaborative Multi-view Learning from Crowds
UAI 2026
How to Learn in a Noisy World? Self-Correcting the Real-World Data Noise in Machine Translation
NAACL 2025
Label Noise Correction via Fuzzy Learning Machine
AAAI 2025
Rethinking Pseudo-Label Guided Learning for Weakly Supervised Temporal Action Localization from the Perspective of Noise Correction
AAAI 2025
Connectivity-Driven Pseudo-Labeling Makes Stronger Cross-Domain Segmenters
NeurIPS 2024
IWBVT: Instance Weighting-based Bias-Variance Trade-off for Crowdsourcing
NeurIPS 2024
Which Is More Effective in Label Noise Cleaning, Correction or Filtering?
AAAI 2024
Adaptive Textual Label Noise Learning based on Pre-trained Models
EMNLP 2023
Fine-Grained Classification With Noisy Labels
CVPR 2023
Learning to Correct Noisy Labels for Fine-Grained Entity Typing via Co-Prediction Prompt Tuning
EMNLP 2023
NewsPanda: Media Monitoring for Timely Conservation Action
AAAI 2023
Noisy Pair Corrector for Dense Retrieval
EMNLP 2023
Noise-Robust Learning from Multiple Unsupervised Sources of Inferred Labels
AAAI 2022
Learning from Noisy Labels with No Change to the Training Process
ICML 2021
Label Noise in Context
ACL 2020
Learning Domain Terms - Empirical Methods to Enhance Enterprise Text Analytics Performance
COLING 2020
Using Trusted Data to Train Deep Networks on Labels Corrupted by Severe Noise
NeurIPS 2018