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Adversarial Examples Are Not Bugs, They Are Features

Adversarial Examples Are Not Bugs, They Are Features

6 May 2019
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
A. Madry
    SILM
ArXivPDFHTML

Papers citing "Adversarial Examples Are Not Bugs, They Are Features"

50 / 372 papers shown
Title
Adversarially Pretrained Transformers may be Universally Robust In-Context Learners
Adversarially Pretrained Transformers may be Universally Robust In-Context Learners
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
11
0
0
20 May 2025
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
X-Transfer Attacks: Towards Super Transferable Adversarial Attacks on CLIP
Hanxun Huang
Sarah Monazam Erfani
Yige Li
Xingjun Ma
James Bailey
AAML
55
0
0
08 May 2025
Reliable Disentanglement Multi-view Learning Against View Adversarial Attacks
Reliable Disentanglement Multi-view Learning Against View Adversarial Attacks
Xuyang Wang
Siyuan Duan
Qizhi Li
Guiduo Duan
Yuan Sun
Dezhong Peng
AAML
EDL
65
0
0
07 May 2025
A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i
A Mathematical Philosophy of Explanations in Mechanistic Interpretability -- The Strange Science Part I.i
Kola Ayonrinde
Louis Jaburi
MILM
90
1
0
01 May 2025
Representation Learning on a Random Lattice
Representation Learning on a Random Lattice
Aryeh Brill
OOD
FAtt
AI4CE
75
0
0
28 Apr 2025
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
A Cryptographic Perspective on Mitigation vs. Detection in Machine Learning
Greg Gluch
Shafi Goldwasser
AAML
42
0
0
28 Apr 2025
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers
Unveiling and Mitigating Adversarial Vulnerabilities in Iterative Optimizers
Elad Sofer
Tomer Shaked
Caroline Chaux
Nir Shlezinger
AAML
47
0
0
26 Apr 2025
Human Aligned Compression for Robust Models
Human Aligned Compression for Robust Models
Samuel Räber
Andreas Plesner
Till Aczél
Roger Wattenhofer
AAML
42
0
0
16 Apr 2025
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Impact of Data Duplication on Deep Neural Network-Based Image Classifiers: Robust vs. Standard Models
Alireza Aghabagherloo
Aydin Abadi
Sumanta Sarkar
Vishnu Asutosh Dasu
Bart Preneel
AAML
65
0
0
01 Apr 2025
Do regularization methods for shortcut mitigation work as intended?
Do regularization methods for shortcut mitigation work as intended?
Haoyang Hong
Ioanna Papanikolaou
Sonali Parbhoo
47
1
0
21 Mar 2025
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data
Weakly Supervised Contrastive Adversarial Training for Learning Robust Features from Semi-supervised Data
Lilin Zhang
Chengpei Wu
Ning Yang
39
0
0
14 Mar 2025
Testing the limits of fine-tuning to improve reasoning in vision language models
Testing the limits of fine-tuning to improve reasoning in vision language models
Luca M. Schulze Buschoff
Konstantinos Voudouris
Elif Akata
Matthias Bethge
Joshua B. Tenenbaum
Eric Schulz
LRM
VLM
Presented at ResearchTrend Connect | VLM on 14 Mar 2025
126
0
1
24 Feb 2025
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Carefully Blending Adversarial Training, Purification, and Aggregation Improves Adversarial Robustness
Emanuele Ballarin
A. Ansuini
Luca Bortolussi
AAML
70
0
0
20 Feb 2025
Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play
Imitation Game for Adversarial Disillusion with Multimodal Generative Chain-of-Thought Role-Play
Ching-Chun Chang
Fan-Yun Chen
Shih-Hong Gu
Kai Gao
Hanrui Wang
Isao Echizen
AAML
243
0
0
31 Jan 2025
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
Graph Neural Backdoor: Fundamentals, Methodologies, Applications, and Future Directions
Xiao Yang
Gaolei Li
Jianhua Li
AAML
AI4CE
56
1
0
08 Jan 2025
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
A High Dimensional Statistical Model for Adversarial Training: Geometry and Trade-Offs
Kasimir Tanner
Matteo Vilucchio
Bruno Loureiro
Florent Krzakala
AAML
63
0
0
31 Dec 2024
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
Defending Multimodal Backdoored Models by Repulsive Visual Prompt Tuning
Zhifang Zhang
Shuo He
Bingquan Shen
Lei Feng
Lei Feng
AAML
57
0
0
29 Dec 2024
Improving Transferable Targeted Attacks with Feature Tuning Mixup
Improving Transferable Targeted Attacks with Feature Tuning Mixup
K. Liang
Xuelong Dai
Yanjie Li
Dong Wang
Bin Xiao
AAML
224
0
0
23 Nov 2024
Robust Feature Learning for Multi-Index Models in High Dimensions
Robust Feature Learning for Multi-Index Models in High Dimensions
Alireza Mousavi-Hosseini
Adel Javanmard
Murat A. Erdogdu
OOD
AAML
48
1
0
21 Oct 2024
Estimating the Probabilities of Rare Outputs in Language Models
Estimating the Probabilities of Rare Outputs in Language Models
Gabriel Wu
Jacob Hilton
AAML
UQCV
53
2
0
17 Oct 2024
Efficient Optimization Algorithms for Linear Adversarial Training
Efficient Optimization Algorithms for Linear Adversarial Training
Antônio H. Ribeiro
Thomas B. Schon
Dave Zahariah
Francis Bach
AAML
55
1
0
16 Oct 2024
Uncovering, Explaining, and Mitigating the Superficial Safety of
  Backdoor Defense
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor Defense
Rui Min
Zeyu Qin
Nevin L. Zhang
Li Shen
Minhao Cheng
AAML
39
4
0
13 Oct 2024
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Adversarial Training Can Provably Improve Robustness: Theoretical Analysis of Feature Learning Process Under Structured Data
Binghui Li
Yuanzhi Li
OOD
41
2
0
11 Oct 2024
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Unveiling AI's Blind Spots: An Oracle for In-Domain, Out-of-Domain, and Adversarial Errors
Shuangpeng Han
Mengmi Zhang
193
0
0
03 Oct 2024
FedAT: Federated Adversarial Training for Distributed Insider Threat
  Detection
FedAT: Federated Adversarial Training for Distributed Insider Threat Detection
R. Gayathri
Atul Sajjanhar
Md Palash Uddin
Yong Xiang
FedML
23
0
0
19 Sep 2024
Seeing Through the Mask: Rethinking Adversarial Examples for CAPTCHAs
Seeing Through the Mask: Rethinking Adversarial Examples for CAPTCHAs
Yahya Jabary
Andreas Plesner
Turlan Kuzhagaliyev
Roger Wattenhofer
AAML
39
0
0
09 Sep 2024
Accurate Forgetting for All-in-One Image Restoration Model
Accurate Forgetting for All-in-One Image Restoration Model
Xin Su
Zhuoran Zheng
CLL
37
1
0
01 Sep 2024
Certified Causal Defense with Generalizable Robustness
Certified Causal Defense with Generalizable Robustness
Yiran Qiao
Yu Yin
Chen Chen
Jing Ma
AAML
OOD
CML
63
0
0
28 Aug 2024
PartImageNet++ Dataset: Scaling up Part-based Models for Robust
  Recognition
PartImageNet++ Dataset: Scaling up Part-based Models for Robust Recognition
Xiao-Li Li
Yining Liu
Na Dong
Sitian Qin
Xiaolin Hu
41
3
0
15 Jul 2024
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Guangtao Zheng
Wenqian Ye
Aidong Zhang
54
1
0
15 Jun 2024
Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory
  Overfitting Challenge in Continual Learning
Adversarially Diversified Rehearsal Memory (ADRM): Mitigating Memory Overfitting Challenge in Continual Learning
Hikmat Khan
Ghulam Rasool
N. Bouaynaya
AAML
28
0
0
20 May 2024
Distilling Diffusion Models into Conditional GANs
Distilling Diffusion Models into Conditional GANs
Minguk Kang
Richard Zhang
Connelly Barnes
Sylvain Paris
Suha Kwak
Jaesik Park
Eli Shechtman
Jun-Yan Zhu
Taesung Park
46
37
0
09 May 2024
Brain-Inspired Continual Learning-Robust Feature Distillation and
  Re-Consolidation for Class Incremental Learning
Brain-Inspired Continual Learning-Robust Feature Distillation and Re-Consolidation for Class Incremental Learning
Hikmat Khan
N. Bouaynaya
Ghulam Rasool
CLL
38
1
0
22 Apr 2024
Towards a Novel Perspective on Adversarial Examples Driven by Frequency
Towards a Novel Perspective on Adversarial Examples Driven by Frequency
Zhun Zhang
Yi Zeng
Qihe Liu
Shijie Zhou
AAML
39
0
0
16 Apr 2024
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset
  Distillation
DD-RobustBench: An Adversarial Robustness Benchmark for Dataset Distillation
Yifan Wu
Jiawei Du
Ping Liu
Yuewei Lin
Wenqing Cheng
Wei-ping Xu
DD
AAML
42
5
0
20 Mar 2024
Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach
  for Relation Classification
Best of Both Worlds: A Pliable and Generalizable Neuro-Symbolic Approach for Relation Classification
Robert Vacareanu
F. Alam
M. Islam
Haris Riaz
Mihai Surdeanu
NAI
35
2
0
05 Mar 2024
On the Challenges and Opportunities in Generative AI
On the Challenges and Opportunities in Generative AI
Laura Manduchi
Kushagra Pandey
Robert Bamler
Ryan Cotterell
Sina Daubener
...
F. Wenzel
Frank Wood
Stephan Mandt
Vincent Fortuin
Vincent Fortuin
56
17
0
28 Feb 2024
Adversarial Math Word Problem Generation
Adversarial Math Word Problem Generation
Roy Xie
Chengxuan Huang
Junlin Wang
Bhuwan Dhingra
AAML
38
1
0
27 Feb 2024
Robustness of Deep Neural Networks for Micro-Doppler Radar
  Classification
Robustness of Deep Neural Networks for Micro-Doppler Radar Classification
Mikolaj Czerkawski
C. Clemente
C. Michie
Christos Tachtatzis
OOD
AAML
24
3
0
21 Feb 2024
Theoretical Understanding of Learning from Adversarial Perturbations
Theoretical Understanding of Learning from Adversarial Perturbations
Soichiro Kumano
Hiroshi Kera
Toshihiko Yamasaki
AAML
46
1
0
16 Feb 2024
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off
  in Adversarial Training
Conserve-Update-Revise to Cure Generalization and Robustness Trade-off in Adversarial Training
Shruthi Gowda
Bahram Zonooz
Elahe Arani
AAML
31
2
0
26 Jan 2024
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive
  Attackers for Security Applications
CARE: Ensemble Adversarial Robustness Evaluation Against Adaptive Attackers for Security Applications
Hangsheng Zhang
Jiqiang Liu
Jinsong Dong
AAML
21
1
0
20 Jan 2024
Mathematical Algorithm Design for Deep Learning under Societal and
  Judicial Constraints: The Algorithmic Transparency Requirement
Mathematical Algorithm Design for Deep Learning under Societal and Judicial Constraints: The Algorithmic Transparency Requirement
Holger Boche
Adalbert Fono
Gitta Kutyniok
FaML
33
4
0
18 Jan 2024
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
MIMIR: Masked Image Modeling for Mutual Information-based Adversarial Robustness
Xiaoyun Xu
Shujian Yu
Jingzheng Wu
S. Picek
AAML
35
0
0
08 Dec 2023
SoK: Unintended Interactions among Machine Learning Defenses and Risks
SoK: Unintended Interactions among Machine Learning Defenses and Risks
Vasisht Duddu
S. Szyller
Nadarajah Asokan
AAML
47
2
0
07 Dec 2023
Scaling Laws for Adversarial Attacks on Language Model Activations
Scaling Laws for Adversarial Attacks on Language Model Activations
Stanislav Fort
26
15
0
05 Dec 2023
Rethinking Adversarial Training with Neural Tangent Kernel
Rethinking Adversarial Training with Neural Tangent Kernel
Guanlin Li
Han Qiu
Shangwei Guo
Jiwei Li
Tianwei Zhang
AAML
29
0
0
04 Dec 2023
Towards Sample-specific Backdoor Attack with Clean Labels via Attribute Trigger
Towards Sample-specific Backdoor Attack with Clean Labels via Attribute Trigger
Yiming Li
Mingyan Zhu
Junfeng Guo
Tao Wei
Shu-Tao Xia
Zhan Qin
AAML
71
1
0
03 Dec 2023
On The Relationship Between Universal Adversarial Attacks And Sparse
  Representations
On The Relationship Between Universal Adversarial Attacks And Sparse Representations
Dana Weitzner
Raja Giryes
AAML
32
0
0
14 Nov 2023
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from
  a Minimax Game Perspective
Balance, Imbalance, and Rebalance: Understanding Robust Overfitting from a Minimax Game Perspective
Yifei Wang
Liangchen Li
Jiansheng Yang
Zhouchen Lin
Yisen Wang
33
11
0
30 Oct 2023
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