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2012.13628
Cited By
A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning
25 December 2020
Ahmadreza Jeddi
M. Shafiee
A. Wong
AAML
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Papers citing
"A Simple Fine-tuning Is All You Need: Towards Robust Deep Learning Via Adversarial Fine-tuning"
27 / 27 papers shown
A Guide to Robust Generalization: The Impact of Architecture, Pre-training, and Optimization Strategy
M. Heuillet
Rishika Bhagwatkar
Jonas Ngnawé
Y. Pequignot
Alexandre Larouche
Christian Gagné
Irina Rish
Ola Ahmad
Audrey Durand
OOD
AAML
VLM
207
2
0
12 Aug 2025
Adversarially Pretrained Transformers May Be Universally Robust In-Context Learners
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
627
1
0
20 May 2025
On the Robustness Tradeoff in Fine-Tuning
Kunyang Li
Jean-Charles Noirot Ferrand
Ryan Sheatsley
Blaine Hoak
Yohan Beugin
Eric Pauley
Patrick McDaniel
336
2
0
19 Mar 2025
Model X-Ray: Detection of Hidden Malware in AI Model Weights using Few Shot Learning
Daniel Gilkarov
Ran Dubin
262
1
0
28 Sep 2024
Current state of LLM Risks and AI Guardrails
Suriya Ganesh Ayyamperumal
Limin Ge
379
66
0
16 Jun 2024
ASAM: Boosting Segment Anything Model with Adversarial Tuning
Bo Li
Haoke Xiao
Lv Tang
331
24
0
01 May 2024
Adversarial Fine-tuning of Compressed Neural Networks for Joint Improvement of Robustness and Efficiency
Hallgrimur Thorsteinsson
Valdemar J Henriksen
Tong Chen
Raghavendra Selvan
AAML
261
2
0
14 Mar 2024
Mitigating Feature Gap for Adversarial Robustness by Feature Disentanglement
Nuoyan Zhou
Dawei Zhou
Decheng Liu
Xinbo Gao
Nannan Wang
AAML
245
0
0
26 Jan 2024
Adversarial Finetuning with Latent Representation Constraint to Mitigate Accuracy-Robustness Tradeoff
IEEE International Conference on Computer Vision (ICCV), 2023
Satoshi Suzuki
Shin'ya Yamaguchi
Shoichiro Takeda
Sekitoshi Kanai
Naoki Makishima
Atsushi Ando
Ryo Masumura
AAML
303
7
0
31 Aug 2023
A Holistic Assessment of the Reliability of Machine Learning Systems
Anthony Corso
David Karamadian
Romeo Valentin
Mary Cooper
Mykel J. Kochenderfer
416
10
0
20 Jul 2023
TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and Generalization
Computer Vision and Pattern Recognition (CVPR), 2023
Ziquan Liu
Yi Tian Xu
Xiangyang Ji
Antoni B. Chan
AAML
242
26
0
20 Mar 2023
Revisiting Adversarial Training for ImageNet: Architectures, Training and Generalization across Threat Models
Neural Information Processing Systems (NeurIPS), 2023
Naman D. Singh
Francesco Croce
Matthias Hein
OOD
440
100
0
03 Mar 2023
Robust Trajectory Prediction against Adversarial Attacks
Conference on Robot Learning (CoRL), 2022
Yulong Cao
Danfei Xu
Xinshuo Weng
Zhuoqing Mao
Anima Anandkumar
Chaowei Xiao
Marco Pavone
AAML
226
43
0
29 Jul 2022
Guiding the retraining of convolutional neural networks against adversarial inputs
PeerJ Computer Science (PeerJ CS), 2022
Francisco Durán
Luís Cruz
Michael Felderer
Xavier Franch
AAML
335
1
0
08 Jul 2022
Turning a Curse into a Blessing: Enabling In-Distribution-Data-Free Backdoor Removal via Stabilized Model Inversion
Si-An Chen
Yi Zeng
J. T.Wang
Won Park
Xun Chen
Lingjuan Lyu
Zhuoqing Mao
R. Jia
218
3
0
14 Jun 2022
Hierarchical Distribution-Aware Testing of Deep Learning
ACM Transactions on Software Engineering and Methodology (TOSEM), 2022
Wei Huang
Xingyu Zhao
Alec Banks
V. Cox
Xiaowei Huang
OOD
AAML
304
14
0
17 May 2022
Adversarial Fine-tune with Dynamically Regulated Adversary
IEEE International Joint Conference on Neural Network (IJCNN), 2022
Peng-Fei Hou
Ming Zhou
Jie Han
Petr Musílek
Xingyu Li
AAML
151
3
0
28 Apr 2022
Joint rotational invariance and adversarial training of a dual-stream Transformer yields state of the art Brain-Score for Area V4
William Berrios
Arturo Deza
MedIm
ViT
327
13
0
08 Mar 2022
On The Empirical Effectiveness of Unrealistic Adversarial Hardening Against Realistic Adversarial Attacks
IEEE Symposium on Security and Privacy (IEEE S&P), 2022
Salijona Dyrmishi
Salah Ghamizi
Thibault Simonetto
Yves Le Traon
Maxime Cordy
AAML
242
23
0
07 Feb 2022
Improving Robustness by Enhancing Weak Subnets
European Conference on Computer Vision (ECCV), 2022
Yong Guo
David Stutz
Bernt Schiele
AAML
376
17
0
30 Jan 2022
Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness
International Conference on Learning Representations (ICLR), 2021
Simon Geisler
Johanna Sommer
Jan Schuchardt
Aleksandar Bojchevski
Stephan Günnemann
AAML
179
49
0
21 Oct 2021
Can the Transformer Be Used as a Drop-in Replacement for RNNs in Text-Generating GANs?
Recent Advances in Natural Language Processing (RANLP), 2021
Kevin Blin
Andrei Kucharavy
272
2
0
26 Aug 2021
Identifying Layers Susceptible to Adversarial Attacks
Shoaib Ahmed Siddiqui
Thomas Breuel
AAML
284
3
0
10 Jul 2021
ROPUST: Improving Robustness through Fine-tuning with Photonic Processors and Synthetic Gradients
Alessandro Cappelli
Julien Launay
Laurent Meunier
Ruben Ohana
Iacopo Poli
AAML
174
4
0
06 Jul 2021
Adversarial Robustness against Multiple and Single
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-Threat Models via Quick Fine-Tuning of Robust Classifiers
International Conference on Machine Learning (ICML), 2021
Francesco Croce
Matthias Hein
OOD
AAML
293
26
0
26 May 2021
Adversarial Perturbations Are Not So Weird: Entanglement of Robust and Non-Robust Features in Neural Network Classifiers
Jacob Mitchell Springer
Melanie Mitchell
Garrett Kenyon
AAML
218
15
0
09 Feb 2021
Adversarially Robust Learning via Entropic Regularization
Frontiers in Artificial Intelligence (FAI), 2020
Gauri Jagatap
Ameya Joshi
A. B. Chowdhury
S. Garg
Chinmay Hegde
OOD
352
13
0
27 Aug 2020
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