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Adversarial Examples Are Not Bugs, They Are Features
v1v2v3v4 (latest)

Adversarial Examples Are Not Bugs, They Are Features

Neural Information Processing Systems (NeurIPS), 2019
6 May 2019
Andrew Ilyas
Shibani Santurkar
Dimitris Tsipras
Logan Engstrom
Brandon Tran
Aleksander Madry
    SILM
ArXiv (abs)PDFHTML

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

50 / 1,093 papers shown
Assistive AI for Augmenting Human Decision-making
Assistive AI for Augmenting Human Decision-making
Natabara Máté Gyöngyössy
Bernát Török
Csilla Farkas
Laura Lucaj
Attila Menyhárd
Krisztina Menyhárd-Balázs
András Simonyi
Patrick van der Smagt
Zsolt Ződi
András Lőrincz
320
0
0
18 Oct 2024
Attuned to Change: Causal Fine-Tuning under Latent-Confounded Shifts
Attuned to Change: Causal Fine-Tuning under Latent-Confounded Shifts
Jialin Yu
Yuxiang Zhou
Yulan He
Nevin L. Zhang
Ricardo Silva
Philip Torr
Ricardo M. A. Silva
386
0
0
18 Oct 2024
Golyadkin's Torment: Doppelgängers and Adversarial Vulnerability
Golyadkin's Torment: Doppelgängers and Adversarial Vulnerability
George I. Kamberov
AAML
139
0
0
17 Oct 2024
Estimating the Probabilities of Rare Outputs in Language Models
Estimating the Probabilities of Rare Outputs in Language ModelsInternational Conference on Learning Representations (ICLR), 2024
Gabriel Wu
Jacob Hilton
AAMLUQCV
348
3
0
17 Oct 2024
Efficient Optimization Algorithms for Linear Adversarial Training
Efficient Optimization Algorithms for Linear Adversarial TrainingInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2024
Antônio H. Ribeiro
Thomas B. Schon
Dave Zahariah
Francis Bach
AAML
452
3
0
16 Oct 2024
SOE: SO(3)-Equivariant 3D MRI Encoding
SOE: SO(3)-Equivariant 3D MRI Encoding
Shizhe He
Magdalini Paschali
J. Ouyang
Adnan Masood
Akshay S. Chaudhari
Ehsan Adeli
234
1
0
15 Oct 2024
Towards Reliable Verification of Unauthorized Data Usage in Personalized
  Text-to-Image Diffusion Models
Towards Reliable Verification of Unauthorized Data Usage in Personalized Text-to-Image Diffusion ModelsIEEE Symposium on Security and Privacy (S&P), 2024
Boheng Li
Yanhao Wei
Yankai Fu
Ziyi Wang
Yiming Li
Jie Zhang
Run Wang
Minlie Huang
DiffMAAML
208
20
0
14 Oct 2024
Uncovering, Explaining, and Mitigating the Superficial Safety of
  Backdoor Defense
Uncovering, Explaining, and Mitigating the Superficial Safety of Backdoor DefenseNeural Information Processing Systems (NeurIPS), 2024
Rui Min
Zeyu Qin
Nevin L. Zhang
Li Shen
Minhao Cheng
AAML
465
8
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 DataInternational Conference on Learning Representations (ICLR), 2024
Binghui Li
Yuanzhi Li
OOD
348
9
0
11 Oct 2024
Bilinear MLPs enable weight-based mechanistic interpretability
Bilinear MLPs enable weight-based mechanistic interpretabilityInternational Conference on Learning Representations (ICLR), 2024
Michael T. Pearce
Thomas Dooms
Alice Rigg
José Oramas
Lee Sharkey
240
16
0
10 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
922
0
0
03 Oct 2024
Robust Network Learning via Inverse Scale Variational Sparsification
Robust Network Learning via Inverse Scale Variational Sparsification
Zhiling Zhou
Zirui Liu
Chengming Xu
Yanwei Fu
Xinwei Sun
AAML
273
0
0
27 Sep 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
194
1
0
19 Sep 2024
The Fluorescent Veil: A Stealthy and Effective Physical Adversarial Patch Against Traffic Sign Recognition
The Fluorescent Veil: A Stealthy and Effective Physical Adversarial Patch Against Traffic Sign Recognition
Shuai Yuan
Xingshuo Han
Hongwei Li
Guowen Xu
Wenbo Jiang
Tao Ni
Qingchuan Zhao
Yuguang Fang
275
7
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
195
2
0
09 Sep 2024
Dreaming is All You Need
Dreaming is All You Need
Mingze Ni
Wei Liu
131
0
0
03 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
267
1
0
01 Sep 2024
What Machine Learning Tells Us About the Mathematical Structure of
  Concepts
What Machine Learning Tells Us About the Mathematical Structure of Concepts
Jun Otsuka
244
0
0
28 Aug 2024
Certified Causal Defense with Generalizable Robustness
Certified Causal Defense with Generalizable RobustnessAAAI Conference on Artificial Intelligence (AAAI), 2024
Yiran Qiao
Yu Yin
Chen Chen
Jing Ma
AAMLOODCML
486
1
0
28 Aug 2024
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
LLM Defenses Are Not Robust to Multi-Turn Human Jailbreaks Yet
Nathaniel Li
Ziwen Han
Ian Steneker
Willow Primack
Riley Goodside
Hugh Zhang
Zifan Wang
Cristina Menghini
Summer Yue
AAMLMU
291
104
0
27 Aug 2024
Improving Adversarial Robustness in Android Malware Detection by
  Reducing the Impact of Spurious Correlations
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations
Hamid Bostani
Subrat Kishore Dutta
Veelasha Moonsamy
AAML
224
0
0
27 Aug 2024
Approaching Deep Learning through the Spectral Dynamics of Weights
Approaching Deep Learning through the Spectral Dynamics of Weights
David Yunis
Kumar Kshitij Patel
Samuel Wheeler
Pedro H. P. Savarese
Gal Vardi
Karen Livescu
Michael Maire
Matthew R. Walter
327
13
0
21 Aug 2024
Criticality Leveraged Adversarial Training (CLAT) for Boosted
  Performance via Parameter Efficiency
Criticality Leveraged Adversarial Training (CLAT) for Boosted Performance via Parameter Efficiency
Bhavna Gopal
Huanrui Yang
Jingyang Zhang
Mark Horton
Yiran Chen
AAML
204
1
0
19 Aug 2024
Exploring Cross-model Neuronal Correlations in the Context of Predicting
  Model Performance and Generalizability
Exploring Cross-model Neuronal Correlations in the Context of Predicting Model Performance and Generalizability
Haniyeh Ehsani Oskouie
Lionel Levine
Majid Sarrafzadeh
214
2
0
15 Aug 2024
PixelFade: Privacy-preserving Person Re-identification with Noise-guided
  Progressive Replacement
PixelFade: Privacy-preserving Person Re-identification with Noise-guided Progressive ReplacementACM Multimedia (MM), 2024
Delong Zhang
Yi-Xing Peng
Xiao-Ming Wu
Ancong Wu
Wei-Shi Zheng
PICVAAML
350
7
0
10 Aug 2024
Securing the Diagnosis of Medical Imaging: An In-depth Analysis of
  AI-Resistant Attacks
Securing the Diagnosis of Medical Imaging: An In-depth Analysis of AI-Resistant Attacks
A. Biswas
Md Abdullah Al Nasim
Chen Chen
Weiming Zhuang
Abdur Rashid
AAML
196
5
0
01 Aug 2024
Clean-Label Physical Backdoor Attacks with Data Distillation
Clean-Label Physical Backdoor Attacks with Data Distillation
Thinh Dao
Cuong Chi Le
Khoa D. Doan
AAML
485
1
0
27 Jul 2024
Scaling Trends in Language Model Robustness
Scaling Trends in Language Model Robustness
Nikolhaus Howe
Michal Zajac
I. R. McKenzie
Oskar Hollinsworth
Tom Tseng
Aaron David Tucker
Pierre-Luc Bacon
Adam Gleave
647
1
0
25 Jul 2024
Beyond Spatial Explanations: Explainable Face Recognition in the
  Frequency Domain
Beyond Spatial Explanations: Explainable Face Recognition in the Frequency Domain
Marco Huber
Naser Damer
CVBM
288
3
0
16 Jul 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
330
8
0
15 Jul 2024
Evaluating the Adversarial Robustness of Semantic Segmentation: Trying
  Harder Pays Off
Evaluating the Adversarial Robustness of Semantic Segmentation: Trying Harder Pays Off
L. Halmosi
Bálint Mohos
Márk Jelasity
AAML
175
1
0
12 Jul 2024
Deep Learning for Network Anomaly Detection under Data Contamination:
  Evaluating Robustness and Mitigating Performance Degradation
Deep Learning for Network Anomaly Detection under Data Contamination: Evaluating Robustness and Mitigating Performance Degradation
D'Jeff K. Nkashama
Jordan Masakuna Félicien
Arian Soltani
Jean-Charles Verdier
Pierre Martin Tardif
Marc Frappier
F. Kabanza
AAML
240
3
0
11 Jul 2024
Non-Robust Features are Not Always Useful in One-Class Classification
Non-Robust Features are Not Always Useful in One-Class Classification
Matthew Lau
Haoran Wang
Alec Helbling
Matthew Hul
ShengYun Peng
Martin Andreoni
W. T. Lunardi
Wenke Lee
AAML
137
0
0
08 Jul 2024
Regulating Model Reliance on Non-Robust Features by Smoothing Input
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Regulating Model Reliance on Non-Robust Features by Smoothing Input Marginal Density
Peiyu Yang
Naveed Akhtar
Mubarak Shah
Lin Wang
AAML
222
3
0
05 Jul 2024
Feature compression is the root cause of adversarial fragility in neural network classifiers
Feature compression is the root cause of adversarial fragility in neural network classifiers
Jingchao Gao
Ziqing Lu
Xiaodong Wu
Xiaodong Wu
Jirong Yi
Myung Cho
Catherine Xu
Hui Xie
Weiyu Xu
206
2
0
23 Jun 2024
IG2: Integrated Gradient on Iterative Gradient Path for Feature
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IG2: Integrated Gradient on Iterative Gradient Path for Feature Attribution
Yue Zhuo
Zhiqiang Ge
279
17
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16 Jun 2024
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Spuriousness-Aware Meta-Learning for Learning Robust Classifiers
Guangtao Zheng
Wenqian Ye
Aidong Zhang
257
7
0
15 Jun 2024
Watch the Watcher! Backdoor Attacks on Security-Enhancing Diffusion
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Changjiang Li
Ren Pang
Bochuan Cao
Jinghui Chen
Fenglong Ma
Shouling Ji
Ting Wang
DiffM
181
4
0
14 Jun 2024
An Unsupervised Approach to Achieve Supervised-Level Explainability in
  Healthcare Records
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records
Joakim Edin
Maria Maistro
Lars Maaløe
Lasse Borgholt
Jakob Drachmann Havtorn
Tuukka Ruotsalo
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217
14
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ProFeAT: Projected Feature Adversarial Training for Self-Supervised
  Learning of Robust Representations
ProFeAT: Projected Feature Adversarial Training for Self-Supervised Learning of Robust Representations
Sravanti Addepalli
Priyam Dey
R. Venkatesh Babu
262
2
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MeanSparse: Post-Training Robustness Enhancement Through Mean-Centered Feature Sparsification
MeanSparse: Post-Training Robustness Enhancement Through Mean-Centered Feature Sparsification
Sajjad Amini
Mohammadreza Teymoorianfard
Shiqing Ma
Amir Houmansadr
OODAAML
300
19
0
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The Price of Implicit Bias in Adversarially Robust Generalization
The Price of Implicit Bias in Adversarially Robust GeneralizationNeural Information Processing Systems (NeurIPS), 2024
Nikolaos Tsilivis
Natalie Frank
Nathan Srebro
Julia Kempe
319
4
0
07 Jun 2024
Batch-in-Batch: a new adversarial training framework for initial
  perturbation and sample selection
Batch-in-Batch: a new adversarial training framework for initial perturbation and sample selection
Yinting Wu
Pai Peng
Bo Cai
Le Li
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AAML
242
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06 Jun 2024
Memorization in deep learning: A survey
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Jiaheng Wei
Yanjun Zhang
Leo Yu Zhang
Ming Ding
Chao Chen
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303
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FuRL: Visual-Language Models as Fuzzy Rewards for Reinforcement Learning
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Yuwei Fu
Haichao Zhang
Di Wu
Wei Xu
Benoit Boulet
VLM
365
25
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Investigating and unmasking feature-level vulnerabilities of CNNs to
  adversarial perturbations
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Davide Coppola
Hwee Kuan Lee
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183
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Resurrecting Old Classes with New Data for Exemplar-Free Continual
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EntProp: High Entropy Propagation for Improving Accuracy and Robustness
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Cross-Modal Safety Alignment: Is textual unlearning all you need?
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Trishna Chakraborty
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384
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