Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels

13 May 2019

Papers citing "Understanding and Utilizing Deep Neural Networks Trained with Noisy Labels"

50 / 74 papers shown

Title
Dynamical Label Augmentation and Calibration for Noisy Electronic Health Records Yuhao Li Ling Luo Uwe Aickelin 34 0 0 12 May 2025
Efficient Vocabulary-Free Fine-Grained Visual Recognition in the Age of Multimodal LLMs Hari Chandana Kuchibhotla Sai Srinivas Kancheti Abbavaram Gowtham Reddy Vineeth N. Balasubramanian 45 0 0 02 May 2025
Hide and Seek in Noise Labels: Noise-Robust Collaborative Active Learning with LLM-Powered Assistance Bo Yuan Yulin Chen Yin Zhang Wei Jiang NoLa 40 6 0 03 Apr 2025
Enhancing Vision-Language Compositional Understanding with Multimodal Synthetic Data Haoxin Li Boyang Li CoGe 73 0 0 03 Mar 2025
Paint Outside the Box: Synthesizing and Selecting Training Data for Visual Grounding Zilin Du Haoxin Li Jianfei Yu Boyang Li 182 0 0 01 Dec 2024
Conformal-in-the-Loop for Learning with Imbalanced Noisy Data J. B. Graham-Knight Jamil Fayyad Nourhan Bayasi Patricia Lasserre H. Najjaran 37 0 0 04 Nov 2024
RC-Mixup: A Data Augmentation Strategy against Noisy Data for Regression Tasks Seonghyeon Hwang Minsu Kim Steven Euijong Whang NoLa 35 2 0 28 May 2024
Why is SAM Robust to Label Noise? Christina Baek Zico Kolter Aditi Raghunathan NoLa AAML 43 9 0 06 May 2024
How does self-supervised pretraining improve robustness against noisy labels across various medical image classification datasets? Bidur Khanal Binod Bhattarai Bishesh Khanal Cristian A. Linte NoLa 21 0 0 15 Jan 2024
Learning with Noisy Labels: Interconnection of Two Expectation-Maximizations Heewon Kim Hyun Sung Chang Kiho Cho Jaeyun Lee Bohyung Han NoLa 26 2 0 09 Jan 2024
Training on Synthetic Data Beats Real Data in Multimodal Relation Extraction Zilin Du Haoxin Li Xu Guo Boyang Li 35 1 0 05 Dec 2023
Investigating the Learning Behaviour of In-context Learning: A Comparison with Supervised Learning Xindi Wang Yufei Wang Can Xu Xiubo Geng Bowen Zhang Chongyang Tao Frank Rudzicz Robert E. Mercer Daxin Jiang 33 11 0 28 Jul 2023
Robust Feature Learning Against Noisy Labels Tsung-Ming Tai Yun-Jie Jhang Wen-Jyi Hwang NoLa 23 1 0 10 Jul 2023
MILD: Modeling the Instance Learning Dynamics for Learning with Noisy Labels Chuanyan Hu Shipeng Yan Zhitong Gao Xuming He NoLa 24 4 0 20 Jun 2023
BadLabel: A Robust Perspective on Evaluating and Enhancing Label-noise Learning Jingfeng Zhang Bo Song Haohan Wang Bo Han Tongliang Liu Lei Liu Masashi Sugiyama AAML NoLa 32 14 0 28 May 2023
DAC-MR: Data Augmentation Consistency Based Meta-Regularization for Meta-Learning Jun Shu Xiang Yuan Deyu Meng Zongben Xu 28 4 0 13 May 2023
DiffuMask: Synthesizing Images with Pixel-level Annotations for Semantic Segmentation Using Diffusion Models Weijia Wu Yuzhong Zhao Mike Zheng Shou Hong Zhou Chunhua Shen 45 140 0 21 Mar 2023
Unsupervised classification to improve the quality of a bird song recording dataset Félix Michaud J. Sueur Maxime LE Cesne S. Haupert 27 28 0 15 Feb 2023
Learning from Noisy Labels with Decoupled Meta Label Purifier Yuanpeng Tu Boshen Zhang Yuxi Li Liang Liu Jian Li Yabiao Wang Chengjie Wang C. Zhao NoLa 49 27 0 14 Feb 2023
Knockoffs-SPR: Clean Sample Selection in Learning with Noisy Labels Yikai Wang Yanwei Fu Xinwei Sun NoLa 55 8 0 02 Jan 2023
Learning from Training Dynamics: Identifying Mislabeled Data Beyond Manually Designed Features Qingrui Jia Xuhong Li Lei Yu Jiang Bian Penghao Zhao Shupeng Li Haoyi Xiong Dejing Dou NoLa 35 5 0 19 Dec 2022
Leveraging Unlabeled Data to Track Memorization Mahsa Forouzesh Hanie Sedghi Patrick Thiran NoLa TDI 34 4 0 08 Dec 2022
Sources of Noise in Dialogue and How to Deal with Them Derek Chen Zhou Yu 24 2 0 06 Dec 2022
CrossSplit: Mitigating Label Noise Memorization through Data Splitting Jihye Kim A. Baratin Yan Zhang Simon Lacoste-Julien NoLa 18 7 0 03 Dec 2022
Hyperbolic Contrastive Learning for Visual Representations beyond Objects Songwei Ge Shlok Kumar Mishra Simon Kornblith Chun-Liang Li David Jacobs OCL SSL 21 51 0 01 Dec 2022
Combating noisy labels in object detection datasets K. Chachula Jakub Lyskawa Bartlomiej Olber Piotr Fratczak A. Popowicz Krystian Radlak NoLa 26 4 0 25 Nov 2022
When Noisy Labels Meet Long Tail Dilemmas: A Representation Calibration Method Manyi Zhang Xuyang Zhao Jun Yao Chun Yuan Weiran Huang 44 20 0 20 Nov 2022
Learning from Long-Tailed Noisy Data with Sample Selection and Balanced Loss Lefan Zhang Zhang-Hao Tian Wujun Zhou Wei Wang NoLa 24 2 0 20 Nov 2022
Improving Data Quality with Training Dynamics of Gradient Boosting Decision Trees M. Ponti L. Oliveira Mathias Esteban Valentina Garcia J. Román Luis Argerich TDI 30 4 0 20 Oct 2022
Tackling Instance-Dependent Label Noise with Dynamic Distribution Calibration Manyi Zhang Yuxin Ren Zihao Wang C. Yuan 24 3 0 11 Oct 2022
Detecting Label Errors in Token Classification Data Wei-Chen Wang Jonas W. Mueller 19 13 0 08 Oct 2022
The Dynamic of Consensus in Deep Networks and the Identification of Noisy Labels Daniel Shwartz Uri Stern D. Weinshall NoLa 36 2 0 02 Oct 2022
Maximising the Utility of Validation Sets for Imbalanced Noisy-label Meta-learning D. Hoang Cuong C. Nguyen Cuong Nguyen anh Belagiannis Vasileios G. Carneiro 28 2 0 17 Aug 2022
Centrality and Consistency: Two-Stage Clean Samples Identification for Learning with Instance-Dependent Noisy Labels Ganlong Zhao Guanbin Li Yipeng Qin Feng Liu Yizhou Yu NoLa 33 22 0 29 Jul 2022
Towards Harnessing Feature Embedding for Robust Learning with Noisy Labels Chuang Zhang Li Shen Jian Yang Chen Gong NoLa 27 5 0 27 Jun 2022
Prioritized Training on Points that are Learnable, Worth Learning, and Not Yet Learnt Sören Mindermann J. Brauner Muhammed Razzak Mrinank Sharma Andreas Kirsch ... Benedikt Höltgen Aidan Gomez Adrien Morisot Sebastian Farquhar Y. Gal 62 149 0 14 Jun 2022
Robustness to Label Noise Depends on the Shape of the Noise Distribution in Feature Space Diane Oyen Michal Kucer N. Hengartner H. Singh NoLa OOD 36 13 0 02 Jun 2022
Effect of Batch Normalization on Noise Resistant Property of Deep Learning Models Omobayode Fagbohungbe Lijun Qian 24 10 0 15 May 2022
FedRN: Exploiting k-Reliable Neighbors Towards Robust Federated Learning Sangmook Kim Wonyoung Shin Soohyuk Jang Hwanjun Song Se-Young Yun 37 2 0 03 May 2022
SELC: Self-Ensemble Label Correction Improves Learning with Noisy Labels Yangdi Lu Wenbo He NoLa 40 39 0 02 May 2022
Selective-Supervised Contrastive Learning with Noisy Labels Shikun Li Xiaobo Xia Shiming Ge Tongliang Liu NoLa 27 172 0 08 Mar 2022
L2B: Learning to Bootstrap Robust Models for Combating Label Noise Yuyin Zhou Xianhang Li Fengze Liu Qingyue Wei Xuxi Chen Lequan Yu Cihang Xie M. Lungren Lei Xing NoLa 47 3 0 09 Feb 2022
Learning with Label Noise for Image Retrieval by Selecting Interactions Sarah Ibrahimi Arnaud Sors Rafael Sampaio de Rezende S. Clinchant NoLa VLM 27 16 0 20 Dec 2021
ALP: Data Augmentation using Lexicalized PCFGs for Few-Shot Text Classification Hazel Kim Daecheol Woo Seong Joon Oh Jeong-Won Cha Yo-Sub Han 323 33 0 16 Dec 2021
Hard Sample Aware Noise Robust Learning for Histopathology Image Classification Chuang Zhu Wenkai Chen T. Peng Ying Wang M. Jin NoLa 34 72 0 05 Dec 2021
Sample Selection for Fair and Robust Training Yuji Roh Kangwook Lee Steven Euijong Whang Changho Suh 21 61 0 27 Oct 2021
PropMix: Hard Sample Filtering and Proportional MixUp for Learning with Noisy Labels F. Cordeiro Vasileios Belagiannis Ian Reid G. Carneiro NoLa 30 18 0 22 Oct 2021
Continual Learning on Noisy Data Streams via Self-Purified Replay C. Kim Jinseo Jeong Sang-chul Moon Gunhee Kim CLL 40 39 0 14 Oct 2021
Assessing the Quality of the Datasets by Identifying Mislabeled Samples Vaibhav Pulastya Gaurav Nuti Yash Kumar Atri Tanmoy Chakraborty NoLa 35 5 0 10 Sep 2021
Robust Long-Tailed Learning under Label Noise Tong Wei Jiang-Xin Shi Wei-Wei Tu Yu-Feng Li NoLa 25 50 0 26 Aug 2021