A curated (most recent) list of resources for Learning with Noisy Labels
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Updated
Oct 18, 2024
A curated (most recent) list of resources for Learning with Noisy Labels
Labelling platform for text using weak supervision.
[NAACL 2021] This is the code for our paper `Fine-Tuning Pre-trained Language Model with Weak Supervision: A Contrastive-Regularized Self-Training Approach'.
Weakly supervised medical named entity classification
PyTorch implementation for Learning with Twin Noisy Labels for Visible-Infrared Person Re-Identification (CVPR 2022).
A pytorch implementation for "Neighborhood Collective Estimation for Noisy Label Identification and Correction", which is accepted by ECCV2022.
Tensorflow 版本的图片鉴黄。not suitable/safe for work (NSFW) images detection using Tensorflow
Uncertainty-aware Fine-tuning of Segmentation Foundation Models (NeurIPS 2024).
Official code of "No Regret Sample Selection with Noisy Labels"
Learning with Noisy Labels for Sentence-level Sentiment Classification
$\epsilon$-Softmax: Approximating One-Hot Vectors for Mitigating Label Noise, NeurIPS 2024
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