Label Smoothing and Adversarial Robustness

Label Smoothing and Adversarial Robustness

17 September 2020

Weijia Jia

Papers citing "Label Smoothing and Adversarial Robustness"

10 / 10 papers shown

Title
AutoAdvExBench: Benchmarking autonomous exploitation of adversarial example defenses Nicholas Carlini Javier Rando Edoardo Debenedetti Milad Nasr F. Tramèr AAML ELM 47 2 0 03 Mar 2025
Impact of Regularization on Calibration and Robustness: from the Representation Space Perspective Jonghyun Park Juyeop Kim Jong-Seok Lee 32 1 0 05 Oct 2024
Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection Yinting Wu Pai Peng Bo Cai Le Li . AAML 39 0 0 06 Jun 2024
Guidance Through Surrogate: Towards a Generic Diagnostic Attack Muzammal Naseer Salman Khan Fatih Porikli Fahad Shahbaz Khan AAML 28 1 0 30 Dec 2022
In and Out-of-Domain Text Adversarial Robustness via Label Smoothing Yahan Yang Soham Dan Dan Roth Insup Lee 6 5 0 20 Dec 2022
Masked Spatial-Spectral Autoencoders Are Excellent Hyperspectral Defenders Jiahao Qi Z. Gong Xingyue Liu Kangcheng Bin Chen Chen Yongqiang Li Wei Xue Yu Zhang P. Zhong AAML 42 6 0 16 Jul 2022
Adversarial Ensemble Training by Jointly Learning Label Dependencies and Member Models Lele Wang B. Liu UQCV 23 4 0 29 Jun 2022
RobustART: Benchmarking Robustness on Architecture Design and Training Techniques Shiyu Tang Ruihao Gong Yan Wang Aishan Liu Jiakai Wang ... Xianglong Liu D. Song Alan Yuille Philip Torr Dacheng Tao VLM AAML 26 107 0 11 Sep 2021
Real World Robustness from Systematic Noise Yan Wang Yuhang Li Ruihao Gong 30 7 0 02 Sep 2021
Understanding the Logit Distributions of Adversarially-Trained Deep Neural Networks Landan Seguin A. Ndirango Neeli Mishra SueYeon Chung Tyler Lee OOD 25 2 0 26 Aug 2021