When Does Label Smoothing Help?

6 June 2019

Papers citing "When Does Label Smoothing Help?"

50 / 282 papers shown

Title
M2Former: Multi-Scale Patch Selection for Fine-Grained Visual Recognition Ji-Hee Moon Junseok K. Lee Yu-Ling Lee Seongsik Park 22 4 0 04 Aug 2023
Get the Best of Both Worlds: Improving Accuracy and Transferability by Grassmann Class Representation Haoqi Wang Zhizhong Li Wayne Zhang 15 2 0 03 Aug 2023
A vision transformer-based framework for knowledge transfer from multi-modal to mono-modal lymphoma subtyping models Bilel Guetarni Féryal Windal H. Benhabiles Marianne Petit Romain Dubois Emmanuelle Leteurtre Dominique Collard DiffM 15 2 0 02 Aug 2023
Model Calibration in Dense Classification with Adaptive Label Perturbation Jiawei Liu Changkun Ye Shanpeng Wang Rui-Qing Cui Jing Zhang Kai Zhang Nick Barnes 39 5 0 25 Jul 2023
Towards Generalizable Deepfake Detection by Primary Region Regularization Harry Cheng Yangyang Guo Tianyi Wang Liqiang Nie Mohan S. Kankanhalli 36 0 0 24 Jul 2023
Rethinking Data Distillation: Do Not Overlook Calibration Dongyao Zhu Bowen Lei Jie M. Zhang Yanbo Fang Ruqi Zhang Yiqun Xie Dongkuan Xu DD FedML 15 15 0 24 Jul 2023
Boundary-weighted logit consistency improves calibration of segmentation networks Neerav Karani Neel Dey Polina Golland 17 3 0 16 Jul 2023
Omnipotent Adversarial Training in the Wild Guanlin Li Kangjie Chen Yuan Xu Han Qiu Tianwei Zhang 16 0 0 14 Jul 2023
Universal Semi-supervised Model Adaptation via Collaborative Consistency Training Zizheng Yan Yushuang Wu Yipeng Qin Xiaoguang Han Shuguang Cui Guanbin Li 30 1 0 07 Jul 2023
Set Learning for Accurate and Calibrated Models Lukas Muttenthaler Robert A. Vandermeulen Qiuyi Zhang Thomas Unterthiner Klaus-Robert Muller 26 2 0 05 Jul 2023
Geometric Pooling: maintaining more useful information Hao Xu Jia Liu Yang Shen Kenan Lou Yanxia Bao Ruihua Zhang Shuyue Zhou Hongsen Zhao Shuai Wang 27 0 0 21 Jun 2023
Scaling of Class-wise Training Losses for Post-hoc Calibration Seungjin Jung Seung-Woo Seo Yonghyun Jeong Jongwon Choi 29 3 0 19 Jun 2023
Deep Model Compression Also Helps Models Capture Ambiguity Hancheol Park Jong C. Park 25 1 0 12 Jun 2023
Performance-optimized deep neural networks are evolving into worse models of inferotemporal visual cortex Drew Linsley I. F. Rodriguez Thomas Fel Michael Arcaro Saloni Sharma Margaret Livingstone Thomas Serre 35 18 0 06 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage Yu Gui Cong Ma Yiqiao Zhong 22 6 0 06 Jun 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 34 4 0 01 Jun 2023
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning Jungtaek Kim 32 1 0 24 May 2023
Dual Focal Loss for Calibration Linwei Tao Minjing Dong Chang Xu UQCV 37 26 0 23 May 2023
Measuring and Mitigating Local Instability in Deep Neural Networks Arghya Datta Subhrangshu Nandi Jingcheng Xu Greg Ver Steeg He Xie Anoop Kumar Aram Galstyan 15 3 0 18 May 2023
Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding Hongliang He Junlei Zhang Zhenzhong Lan Yue Zhang 33 5 0 12 May 2023
Do Not Blindly Imitate the Teacher: Using Perturbed Loss for Knowledge Distillation Rongzhi Zhang Jiaming Shen Tianqi Liu Jia-Ling Liu Michael Bendersky Marc Najork Chao Zhang 42 18 0 08 May 2023
A Systematic Study of Knowledge Distillation for Natural Language Generation with Pseudo-Target Training Nitay Calderon Subhabrata Mukherjee Roi Reichart Amir Kantor 31 17 0 03 May 2023
Fusion for Visual-Infrared Person ReID in Real-World Surveillance Using Corrupted Multimodal Data Arthur Josi Mahdi Alehdaghi Rafael M. O. Cruz Eric Granger 16 2 0 29 Apr 2023
Neural Keyphrase Generation: Analysis and Evaluation Tuhin Kundu Jishnu Ray Chowdhury Cornelia Caragea 25 0 0 27 Apr 2023
Approaching Test Time Augmentation in the Context of Uncertainty Calibration for Deep Neural Networks Pedro Conde T. Barros Rui L. Lopes C. Premebida U. J. Nunes UQCV 17 7 0 11 Apr 2023
On Efficient Training of Large-Scale Deep Learning Models: A Literature Review Li Shen Yan Sun Zhiyuan Yu Liang Ding Xinmei Tian Dacheng Tao VLM 28 40 0 07 Apr 2023
Intersection over Union with smoothing for bounding box regression Petra Stevuliáková P. Hurtík 35 4 0 27 Mar 2023
Exploiting Unlabelled Photos for Stronger Fine-Grained SBIR Aneeshan Sain A. Bhunia Subhadeep Koley Pinaki Nath Chowdhury Soumitri Chattopadhyay Tao Xiang Yi-Zhe Song 20 18 0 24 Mar 2023
From Knowledge Distillation to Self-Knowledge Distillation: A Unified Approach with Normalized Loss and Customized Soft Labels Zhendong Yang Ailing Zeng Zhe Li Tianke Zhang Chun Yuan Yu Li 21 72 0 23 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 36 34 0 19 Mar 2023
AdaptGuard: Defending Against Universal Attacks for Model Adaptation Lijun Sheng Jian Liang R. He Zilei Wang Tien-Ping Tan AAML 40 5 0 19 Mar 2023
Collision Cross-entropy for Soft Class Labels and Deep Clustering Z. Zhang Yuri Boykov 18 0 0 13 Mar 2023
Smooth and Stepwise Self-Distillation for Object Detection Jieren Deng Xiaoxia Zhou Hao Tian Zhihong Pan Derek Aguiar ObjD 23 0 0 09 Mar 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 14 39 0 06 Mar 2023
DiTTO: A Feature Representation Imitation Approach for Improving Cross-Lingual Transfer Shanu Kumar Abbaraju Soujanya Sandipan Dandapat Sunayana Sitaram Monojit Choudhury VLM 25 1 0 04 Mar 2023
Distilling Calibrated Student from an Uncalibrated Teacher Ishan Mishra Sethu Vamsi Krishna Deepak Mishra FedML 32 2 0 22 Feb 2023
mSAM: Micro-Batch-Averaged Sharpness-Aware Minimization Kayhan Behdin Qingquan Song Aman Gupta S. Keerthi Ayan Acharya Borja Ocejo Gregory Dexter Rajiv Khanna D. Durfee Rahul Mazumder AAML 13 7 0 19 Feb 2023
Calibrating a Deep Neural Network with Its Predecessors Linwei Tao Minjing Dong Daochang Liu Changming Sun Chang Xu BDL UQCV 6 5 0 13 Feb 2023
Better Diffusion Models Further Improve Adversarial Training Zekai Wang Tianyu Pang Chao Du Min-Bin Lin Weiwei Liu Shuicheng Yan DiffM 16 207 0 09 Feb 2023
Cut your Losses with Squentropy Like Hui M. Belkin S. Wright UQCV 13 8 0 08 Feb 2023
When the Ground Truth is not True: Modelling Human Biases in Temporal Annotations Taku Yamagata E. Tonkin Benjamin Arana Sanchez I. Craddock Miquel Perelló Nieto Raúl Santos-Rodríguez Weisong Yang Peter A. Flach 14 1 0 06 Feb 2023
Pathologies of Predictive Diversity in Deep Ensembles Taiga Abe E. Kelly Buchanan Geoff Pleiss John P. Cunningham UQCV 38 13 0 01 Feb 2023
Knowledge Distillation on Graphs: A Survey Yijun Tian Shichao Pei Xiangliang Zhang Chuxu Zhang Nitesh V. Chawla 13 28 0 01 Feb 2023
Rethinking Soft Label in Label Distribution Learning Perspective Seungbum Hong Jihun Yoon Bogyu Park Min-Kook Choi 31 0 0 31 Jan 2023
Skeleton-based Human Action Recognition via Convolutional Neural Networks (CNN) Ayman Ali Ekkasit Pinyoanuntapong Pu Wang Mohsen Dorodchi 3DH 20 10 0 31 Jan 2023
Confidence-Aware Calibration and Scoring Functions for Curriculum Learning Shuang Ao Stefan Rueger Advaith Siddharthan UQCV 24 0 0 29 Jan 2023
Controlling Steering with Energy-Based Models Mykyta Baliesnyi Ardi Tampuu Tambet Matiisen LLMSV 25 2 0 28 Jan 2023
Uncertainty Estimation based on Geometric Separation Gabriella Chouraqui L. Cohen Gil Einziger Liel Leman 19 0 0 11 Jan 2023
Transferring Pre-trained Multimodal Representations with Cross-modal Similarity Matching Byoungjip Kim Sun Choi Dasol Hwang Moontae Lee Honglak Lee 25 10 0 07 Jan 2023
Annealing Double-Head: An Architecture for Online Calibration of Deep Neural Networks Erdong Guo D. Draper Maria de Iorio 32 0 0 27 Dec 2022