Adversarial Robustness

Adversarial Robustness evaluates the vulnerabilities of machine learning models under various types of adversarial attacks.

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 426–450 of 1746 papers

Title	Date	Tasks	Status	Score
Improved Robustness Against Adaptive Attacks With Ensembles and Error-Correcting Output Codes	Mar 4, 2023	Adversarial RobustnessDiversity	CodeCode Available	5
Generating Adversarial Examples with Adversarial Networks	Jan 8, 2018	Adversarial Robustness	CodeCode Available	5
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models	Apr 19, 2023	Adversarial Robustness	CodeCode Available	5
Improving Model Robustness with Latent Distribution Locally and Globally	Jul 8, 2021	Adversarial Robustness	CodeCode Available	5
Improving Adversarial Robustness in Android Malware Detection by Reducing the Impact of Spurious Correlations	Aug 27, 2024	Adversarial RobustnessAndroid Malware Detection	CodeCode Available	5
Latent Feature Relation Consistency for Adversarial Robustness	Mar 29, 2023	Adversarial RobustnessRelation	CodeCode Available	5
Biologically Inspired Mechanisms for Adversarial Robustness	Jun 29, 2020	Adversarial Robustness	CodeCode Available	5
Finding Biological Plausibility for Adversarially Robust Features via Metameric Tasks	Feb 2, 2022	Adversarial RobustnessTexture Synthesis	CodeCode Available	5
Center Smoothing: Certified Robustness for Networks with Structured Outputs	Feb 19, 2021	Adversarial RobustnessDimensionality Reduction	CodeCode Available	5
Adversarial Robustness Study of Convolutional Neural Network for Lumbar Disk Shape Reconstruction from MR images	Feb 4, 2021	Adversarial RobustnessData Augmentation	CodeCode Available	5
FI-ODE: Certifiably Robust Forward Invariance in Neural ODEs	Oct 30, 2022	Adversarial Robustnesscontinuous-control	CodeCode Available	5
Feature Denoising for Improving Adversarial Robustness	Dec 9, 2018	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
A Deep Dive into Adversarial Robustness in Zero-Shot Learning	Aug 17, 2020	Adversarial RobustnessBIG-bench Machine Learning	CodeCode Available	5
Beyond Pretrained Features: Noisy Image Modeling Provides Adversarial Defense	Feb 2, 2023	Adversarial DefenseAdversarial Robustness	CodeCode Available	5
Feature Statistics with Uncertainty Help Adversarial Robustness	Mar 26, 2025	Adversarial Robustness	CodeCode Available	5
Beyond One-Hot-Encoding: Injecting Semantics to Drive Image Classifiers	Aug 1, 2023	Adversarial Robustnessimage-classification	CodeCode Available	5
Beyond Model Interpretability: On the Faithfulness and Adversarial Robustness of Contrastive Textual Explanations	Oct 17, 2022	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Fast Adversarial Robustness Certification of Nearest Prototype Classifiers for Arbitrary Seminorms	Dec 1, 2020	Adversarial RobustnessQuantization	CodeCode Available	5
Certified Adversarial Robustness Within Multiple Perturbation Bounds	Apr 20, 2023	Adversarial Robustness	CodeCode Available	5
Fake It Until You Break It: On the Adversarial Robustness of AI-generated Image Detectors	Oct 2, 2024	Adversarial RobustnessMisinformation	CodeCode Available	5
Fast Adversarial Training with Smooth Convergence	Aug 24, 2023	Adversarial Robustness	CodeCode Available	5
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness	Aug 16, 2023	Adversarial RobustnessSubgraph Counting	CodeCode Available	5
Adversarial Robustness of VAEs across Intersectional Subgroups	Jul 4, 2024	Adversarial RobustnessDimensionality Reduction	CodeCode Available	5
FairDeFace: Evaluating the Fairness and Adversarial Robustness of Face Obfuscation Methods	Mar 11, 2025	Adversarial RobustnessFace Detection	CodeCode Available	5
Adversarial Attack Generation Empowered by Min-Max Optimization	Jun 9, 2019	Adversarial AttackAdversarial Robustness	CodeCode Available	5

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All datasets AdvGLUE CIFAR-10 ImageNet ImageNet-A ImageNet-C Stylized ImageNet CIFAR-100

Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	DeBERTa (single model)	Accuracy	0.61	—	Unverified
2	ALBERT (single model)	Accuracy	0.59	—	Unverified
3	T5 (single model)	Accuracy	0.57	—	Unverified
4	SMART_RoBERTa (single model)	Accuracy	0.54	—	Unverified
5	FreeLB (single model)	Accuracy	0.5	—	Unverified
6	RoBERTa (single model)	Accuracy	0.5	—	Unverified
7	InfoBERT (single model)	Accuracy	0.46	—	Unverified
8	ELECTRA (single model)	Accuracy	0.42	—	Unverified
9	BERT (single model)	Accuracy	0.34	—	Unverified
10	SMART_BERT (single model)	Accuracy	0.3	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed classifier	Accuracy	95.23	—	Unverified
2	Stochastic-LWTA/PGD/WideResNet-34-10	Accuracy	92.26	—	Unverified
3	Stochastic-LWTA/PGD/WideResNet-34-5	Accuracy	91.88	—	Unverified
4	GLOT-DR	Accuracy	84.13	—	Unverified
5	TRADES-ANCRA/ResNet18	Accuracy	81.7	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (SGD, Cosine)	Accuracy	77.4	—	Unverified
2	ResNet-50 (SGD, Step)	Accuracy	76.9	—	Unverified
3	DeiT-S (AdamW, Cosine)	Accuracy	76.8	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	76.4	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	12.2	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	3.3	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	3.2	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	3.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	ResNet-50 (AdamW, Cosine)	mean Corruption Error (mCE)	59.3	—	Unverified
2	ResNet-50 (SGD, Step)	mean Corruption Error (mCE)	57.9	—	Unverified
3	ResNet-50 (SGD, Cosine)	mean Corruption Error (mCE)	56.9	—	Unverified
4	DeiT-S (AdamW, Cosine)	mean Corruption Error (mCE)	48	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	DeiT-S (AdamW, Cosine)	Accuracy	13	—	Unverified
2	ResNet-50 (SGD, Cosine)	Accuracy	8.4	—	Unverified
3	ResNet-50 (SGD, Step)	Accuracy	8.3	—	Unverified
4	ResNet-50 (AdamW, Cosine)	Accuracy	8.1	—	Unverified

#	Model	Metric	Claimed	Verified	Status
1	Mixed Classifier	Clean Accuracy	85.21	—	Unverified
2	ResNet18/MART-ANCRA	Clean Accuracy	60.1	—	Unverified