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Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization

5 March 2025

Shunxin Wang

Raymond N. J. Veldhuis

N. Strisciuglio

VLM

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Papers citing "Do ImageNet-trained models learn shortcuts? The impact of frequency shortcuts on generalization"

21 / 21 papers shown

Title
Neural Redshift: Random Networks are not Random Functions Damien Teney A. Nicolicioiu Valentin Hartmann Ehsan Abbasnejad 149 25 0 04 Mar 2024
DFM-X: Augmentation by Leveraging Prior Knowledge of Shortcut Learning Shunxin Wang C. Brune Raymond N. J. Veldhuis N. Strisciuglio AAML 49 4 0 12 Aug 2023
Can contrastive learning avoid shortcut solutions? Joshua Robinson Li Sun Ke Yu Kayhan Batmanghelich Stefanie Jegelka S. Sra SSL 74 145 0 21 Jun 2021
Escaping the Big Data Paradigm with Compact Transformers Ali Hassani Steven Walton Nikhil Shah Abulikemu Abuduweili Jiachen Li Humphrey Shi 120 462 0 12 Apr 2021
A Comprehensive Evaluation Framework for Deep Model Robustness Jun Guo Wei Bao Jiakai Wang Yuqing Ma Xing Gao Gang Xiao Aishan Liu Zehao Zhao Xianglong Liu Wenjun Wu AAML ELM 62 60 0 24 Jan 2021
Unlearnable Examples: Making Personal Data Unexploitable Hanxun Huang Xingjun Ma S. Erfani James Bailey Yisen Wang MIACV 234 194 0 13 Jan 2021
Gradient Starvation: A Learning Proclivity in Neural Networks Mohammad Pezeshki Sekouba Kaba Yoshua Bengio Aaron Courville Doina Precup Guillaume Lajoie MLT 131 268 0 18 Nov 2020
RobustBench: a standardized adversarial robustness benchmark Francesco Croce Maksym Andriushchenko Vikash Sehwag Edoardo Debenedetti Nicolas Flammarion M. Chiang Prateek Mittal Matthias Hein VLM 322 703 0 19 Oct 2020
The Many Faces of Robustness: A Critical Analysis of Out-of-Distribution Generalization Dan Hendrycks Steven Basart Norman Mu Saurav Kadavath Frank Wang ... Samyak Parajuli Mike Guo Basel Alomair Jacob Steinhardt Justin Gilmer OOD 347 1,751 0 29 Jun 2020
The Pitfalls of Simplicity Bias in Neural Networks Harshay Shah Kaustav Tamuly Aditi Raghunathan Prateek Jain Praneeth Netrapalli AAML 69 361 0 13 Jun 2020
Shortcut Learning in Deep Neural Networks Robert Geirhos J. Jacobsen Claudio Michaelis R. Zemel Wieland Brendel Matthias Bethge Felix Wichmann 214 2,056 0 16 Apr 2020
Towards Understanding the Spectral Bias of Deep Learning Yuan Cao Zhiying Fang Yue Wu Ding-Xuan Zhou Quanquan Gu 101 219 0 03 Dec 2019
Learning De-biased Representations with Biased Representations Hyojin Bahng Sanghyuk Chun Sangdoo Yun Jaegul Choo Seong Joon Oh OOD 382 281 0 07 Oct 2019
Learning Robust Global Representations by Penalizing Local Predictive Power Haohan Wang Songwei Ge Eric Xing Zachary Chase Lipton OOD 122 962 0 29 May 2019
Benchmarking Neural Network Robustness to Common Corruptions and Perturbations Dan Hendrycks Thomas G. Dietterich OOD VLM 191 3,445 0 28 Mar 2019
Unmasking Clever Hans Predictors and Assessing What Machines Really Learn Sebastian Lapuschkin S. Wäldchen Alexander Binder G. Montavon Wojciech Samek K. Müller 102 1,017 0 26 Feb 2019
Frequency Principle: Fourier Analysis Sheds Light on Deep Neural Networks Zhi-Qin John Xu Yaoyu Zhang Yaoyu Zhang Yan Xiao Zheng Ma 124 519 0 19 Jan 2019
Certified Robustness to Adversarial Examples with Differential Privacy Mathias Lécuyer Vaggelis Atlidakis Roxana Geambasu Daniel J. Hsu Suman Jana SILM AAML 96 939 0 09 Feb 2018
Grad-CAM: Visual Explanations from Deep Networks via Gradient-based Localization Ramprasaath R. Selvaraju Michael Cogswell Abhishek Das Ramakrishna Vedantam Devi Parikh Dhruv Batra FAtt 321 20,070 0 07 Oct 2016
Why is Posterior Sampling Better than Optimism for Reinforcement Learning? Ian Osband Benjamin Van Roy BDL 83 261 0 01 Jul 2016
Deep Residual Learning for Image Recognition Kaiming He Xinming Zhang Shaoqing Ren Jian Sun MedIm 2.2K 194,322 0 10 Dec 2015