When Does Label Smoothing Help?

6 June 2019

Papers citing "When Does Label Smoothing Help?"

50 / 352 papers shown

Title
Diversified in-domain synthesis with efficient fine-tuning for few-shot classification Victor G. Turrisi da Costa Nicola Dall’Asen Yiming Wang N. Sebe Elisa Ricci 46 3 0 05 Dec 2023
Source-Free Domain Adaptation with Frozen Multimodal Foundation Model Song Tang Wenxin Su Mao Ye Xiatian Zhu VLM 33 21 0 27 Nov 2023
Tailoring Mixup to Data for Calibration Quentin Bouniot Pavlo Mozharovskyi Florence dÁlché-Buc 61 1 0 02 Nov 2023
Towards Fair and Calibrated Models Anand Brahmbhatt Vipul Rathore Mausam Parag Singla FaML 21 2 0 16 Oct 2023
Enhancing Cross-Dataset Performance of Distracted Driving Detection With Score Softmax Classifier And Dynamic Gaussian Smoothing Supervision Cong Duan Zixuan Liu Jiahao Xia Minghai Zhang Jiacai Liao Libo Cao 34 3 0 08 Oct 2023
On Calibration of Modern Quantized Efficient Neural Networks Joe-Hwa Kuang Alexander Wong UQCV MQ 27 1 0 25 Sep 2023
Improving Machine Learning Robustness via Adversarial Training Long Dang T. Hapuarachchi Kaiqi Xiong Jing Lin OOD AAML 38 2 0 22 Sep 2023
Semantic-embedded Similarity Prototype for Scene Recognition Chuanxin Song Hanbo Wu X. Ma Yibin Li 32 3 0 11 Aug 2023
M2Former: Multi-Scale Patch Selection for Fine-Grained Visual Recognition Ji-Hee Moon Junseok K. Lee Yu-Ling Lee Seongsik Park 35 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 23 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 25 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 47 5 0 25 Jul 2023
Towards Generalizable Deepfake Detection by Primary Region Regularization Harry Cheng Yangyang Guo Tianyi Wang Liqiang Nie Mohan S. Kankanhalli 50 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 23 15 0 24 Jul 2023
Boundary-weighted logit consistency improves calibration of segmentation networks Neerav Karani Neel Dey Polina Golland 25 3 0 16 Jul 2023
Omnipotent Adversarial Training in the Wild Guanlin Li Kangjie Chen Yuan Xu Han Qiu Tianwei Zhang 26 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 39 1 0 07 Jul 2023
Set Learning for Accurate and Calibrated Models Lukas Muttenthaler Robert A. Vandermeulen Qiuyi Zhang Thomas Unterthiner Klaus-Robert Muller 34 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 32 0 0 21 Jun 2023
Scaling of Class-wise Training Losses for Post-hoc Calibration Seungjin Jung Seung-Woo Seo Yonghyun Jeong Jongwon Choi 46 3 0 19 Jun 2023
Deep Model Compression Also Helps Models Capture Ambiguity Hancheol Park Jong C. Park 30 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 19 0 06 Jun 2023
Unraveling Projection Heads in Contrastive Learning: Insights from Expansion and Shrinkage Yu Gui Cong Ma Yiqiao Zhong 25 7 0 06 Jun 2023
On the Limitations of Temperature Scaling for Distributions with Overlaps Muthuraman Chidambaram Rong Ge UQCV 37 4 0 01 Jun 2023
Context-aware attention layers coupled with optimal transport domain adaptation and multimodal fusion methods for recognizing dementia from spontaneous speech Loukas Ilias D. Askounis 34 9 0 25 May 2023
Density Ratio Estimation-based Bayesian Optimization with Semi-Supervised Learning Jungtaek Kim 36 1 0 24 May 2023
Dual Focal Loss for Calibration Linwei Tao Minjing Dong Chang Xu UQCV 47 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 20 3 0 18 May 2023
Instance Smoothed Contrastive Learning for Unsupervised Sentence Embedding Hongliang He Junlei Zhang Zhenzhong Lan Yue Zhang 35 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 48 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 41 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 24 2 0 29 Apr 2023
Neural Keyphrase Generation: Analysis and Evaluation Tuhin Kundu Jishnu Ray Chowdhury Cornelia Caragea 31 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 32 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 30 41 0 07 Apr 2023
Intersection over Union with smoothing for bounding box regression Petra Stevuliáková P. Hurtík 37 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 28 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 29 73 0 23 Mar 2023
Randomized Adversarial Training via Taylor Expansion Gao Jin Xinping Yi Dengyu Wu Ronghui Mu Xiaowei Huang AAML 44 34 0 19 Mar 2023
AdaptGuard: Defending Against Universal Attacks for Model Adaptation Lijun Sheng Jian Liang Ran He Zilei Wang Tien-Ping Tan AAML 51 5 0 19 Mar 2023
Collision Cross-entropy for Soft Class Labels and Deep Clustering Z. Zhang Yuri Boykov 23 0 0 13 Mar 2023
Smooth and Stepwise Self-Distillation for Object Detection Jieren Deng Xiaoxia Zhou Hao Tian Zhihong Pan Derek Aguiar ObjD 28 0 0 09 Mar 2023
Rethinking Confidence Calibration for Failure Prediction Fei Zhu Zhen Cheng Xu-Yao Zhang Cheng-Lin Liu UQCV 22 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 33 1 0 04 Mar 2023
Soft labelling for semantic segmentation: Bringing coherence to label down-sampling Roberto Alcover-Couso Marcos Escudero-Viñolo Juan C. Sanmiguel Jose M. Martínez 32 7 0 27 Feb 2023
VE-KWS: Visual Modality Enhanced End-to-End Keyword Spotting Aoting Zhang He Wang Pengcheng Guo Yihui Fu Linfu Xie Yingying Gao Shilei Zhang Junlan Feng 13 4 0 27 Feb 2023
Distilling Calibrated Student from an Uncalibrated Teacher Ishan Mishra Sethu Vamsi Krishna Deepak Mishra FedML 40 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 18 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 14 5 0 13 Feb 2023
Jaccard Metric Losses: Optimizing the Jaccard Index with Soft Labels Zifu Wang Xuefei Ning Matthew B. Blaschko VLM 32 12 0 11 Feb 2023