Papers citing 'Exploring the Vulnerability of Deep Neural Networks: A Study of Parameter Corruption'

Title
Adaptively Sampling-Reusing-Mixing Decomposed Gradients to Speed Up Sharpness Aware Minimization Jiaxin Deng Junbiao Pang 104 0 0 04 Oct 2025
Not All Samples Are Equal: Quantifying Instance-level Difficulty in Targeted Data Poisoning William Xu Yiwei Lu Yihan Wang Matthew Y.R. Yang Zuoqiu Liu Gautam Kamath Yaoliang Yu 120 0 0 08 Sep 2025
Machine Unlearning Fails to Remove Data Poisoning Attacks Martin Pawelczyk Jimmy Z. Di Yiwei Lu Gautam Kamath Ayush Sekhari Seth Neel AAML MU 466 25 0 25 Jun 2024
Hard Work Does Not Always Pay Off: Poisoning Attacks on Neural Architecture Search Zachary Coalson Huazheng Wang Qingyun Wu Sanghyun Hong AAML OOD 222 0 0 09 May 2024
PVF (Parameter Vulnerability Factor): A Scalable Metric for Understanding AI Vulnerability Against SDCs in Model Parameters Xun Jiao Fred Lin H. Dixit Joel Coburn Abhinav Pandey ... Venkat Ramesh Jianyu Huang Wang Xu Daniel Moore Sriram Sankar 123 1 0 02 May 2024
Effective Gradient Sample Size via Variation Estimation for Accelerating Sharpness aware Minimization Jiaxin Deng Junbiao Pang Baochang Zhang Tian Wang 157 1 0 24 Feb 2024
Indiscriminate Data Poisoning Attacks on Pre-trained Feature Extractors Yiwei Lu Matthew Y.R. Yang Gautam Kamath Yaoliang Yu AAML SILM 283 10 0 20 Feb 2024
FAM: Relative Flatness Aware Minimization Linara Adilova Amr Abourayya Jianning Li Amin Dada Henning Petzka Jan Egger Jens Kleesiek Michael Kamp ODL 134 2 0 05 Jul 2023
Adversarial Training Should Be Cast as a Non-Zero-Sum GameInternational Conference on Learning Representations (ICLR), 2023 Avi Schwarzschild Fabian Latorre George J. Pappas Hamed Hassani Volkan Cevher AAML 256 14 0 19 Jun 2023
Loss-Curvature Matching for Dataset Selection and CondensationInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2023 Seung-Jae Shin Heesun Bae DongHyeok Shin Weonyoung Joo Il-Chul Moon DD 171 32 0 08 Mar 2023
Exploring the Limits of Model-Targeted Indiscriminate Data Poisoning AttacksInternational Conference on Machine Learning (ICML), 2023 Yiwei Lu Gautam Kamath Yaoliang Yu AAML 187 23 0 07 Mar 2023
SAMSON: Sharpness-Aware Minimization Scaled by Outlier Normalization for Improving DNN Generalization and Robustness Gonçalo Mordido Sébastien Henwood Sarath Chandar Franccois Leduc-Primeau AAML 137 1 0 18 Nov 2022
Fine-mixing: Mitigating Backdoors in Fine-tuned Language ModelsConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 Zhiyuan Zhang Lingjuan Lyu Jiabo He Chenguang Wang Xu Sun AAML 140 56 0 18 Oct 2022
GA-SAM: Gradient-Strength based Adaptive Sharpness-Aware Minimization for Improved GeneralizationConference on Empirical Methods in Natural Language Processing (EMNLP), 2022 Zhiyuan Zhang Ruixuan Luo Qi Su Xueting Sun 180 17 0 13 Oct 2022
Versatile Weight Attack via Flipping Limited BitsIEEE Transactions on Pattern Analysis and Machine Intelligence (TPAMI), 2022 Jiawang Bai Baoyuan Wu Zhifeng Li Shutao Xia AAML 162 26 0 25 Jul 2022
Fisher SAM: Information Geometry and Sharpness Aware MinimisationInternational Conference on Machine Learning (ICML), 2022 Minyoung Kim Da Li S. Hu Timothy M. Hospedales AAML 235 84 0 10 Jun 2022
Beyond accuracy: generalization properties of bio-plausible temporal credit assignment rulesNeural Information Processing Systems (NeurIPS), 2022 Yuhan Helena Liu Arna Ghosh Blake A. Richards E. Shea-Brown Guillaume Lajoie 368 10 0 02 Jun 2022
Adversarial Parameter Attack on Deep Neural NetworksInternational Conference on Machine Learning (ICML), 2022 Lijia Yu Yihan Wang Xiao-Shan Gao AAML 156 9 0 20 Mar 2022
Raise a Child in Large Language Model: Towards Effective and Generalizable Fine-tuning Runxin Xu Fuli Luo Zhiyuan Zhang Chuanqi Tan Baobao Chang Songfang Huang Fei Huang LRM 283 212 0 13 Sep 2021
Adversarial Parameter Defense by Multi-Step Risk MinimizationNeural Networks (NN), 2021 Zhiyuan Zhang Ruixuan Luo Xuancheng Ren Qi Su Liangyou Li Xu Sun AAML 106 7 0 07 Sep 2021
How to Inject Backdoors with Better Consistency: Logit Anchoring on Clean Data Zhiyuan Zhang Lingjuan Lyu Weiqiang Wang Lichao Sun Xu Sun 164 39 0 03 Sep 2021
Where do Models go Wrong? Parameter-Space Saliency Maps for Explainability Roman Levin Manli Shu Eitan Borgnia Furong Huang Micah Goldblum Tom Goldstein FAtt AAML 87 12 0 03 Aug 2021
Minimum sharpness: Scale-invariant parameter-robustness of neural networks Hikaru Ibayashi Takuo Hamaguchi Masaaki Imaizumi 108 5 0 23 Jun 2021
ASAM: Adaptive Sharpness-Aware Minimization for Scale-Invariant Learning of Deep Neural NetworksInternational Conference on Machine Learning (ICML), 2021 Jungmin Kwon Jeongseop Kim Hyunseong Park I. Choi 308 348 0 23 Feb 2021
Sharpness-Aware Minimization for Efficiently Improving GeneralizationInternational Conference on Learning Representations (ICLR), 2020 Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 618 1,625 0 03 Oct 2020
Relative Flatness and GeneralizationNeural Information Processing Systems (NeurIPS), 2020 Henning Petzka Michael Kamp Linara Adilova C. Sminchisescu Mario Boley 286 89 0 03 Jan 2020