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 451–475 of 1746 papers

Title	Date	Tasks	Status
Adversarial Masked Autoencoder Purifier with Defense Transferability	Jan 28, 2025	Adversarial DefenseAdversarial Robustness	—Unverified
Boosting Certified Robustness for Time Series Classification with Efficient Self-Ensemble	Sep 4, 2024	Adversarial RobustnessTime Series	—Unverified
Adversarially Robust Few-shot Learning via Parameter Co-distillation of Similarity and Class Concept Learners	Jan 1, 2024	Adversarial RobustnessFew-Shot Learning	—Unverified
Chaos Theory and Adversarial Robustness	Oct 20, 2022	Adversarial Robustness	—Unverified
Characterizing the adversarial vulnerability of speech self-supervised learning	Nov 8, 2021	Adversarial RobustnessBenchmarking	—Unverified
A Survey and Evaluation of Adversarial Attacks for Object Detection	Aug 4, 2024	Adversarial RobustnessAutonomous Vehicles	—Unverified
Effects of Loss Functions And Target Representations on Adversarial Robustness	Dec 1, 2018	Adversarial Robustness	—Unverified
Class-Aware Domain Adaptation for Improving Adversarial Robustness	May 10, 2020	Adversarial AttackAdversarial Defense	—Unverified
Class-Aware Robust Adversarial Training for Object Detection	Mar 30, 2021	Adversarial RobustnessObject	—Unverified
Classifier Guidance Enhances Diffusion-based Adversarial Purification by Preserving Predictive Information	Aug 12, 2024	Adversarial PurificationAdversarial Robustness	—Unverified
A Framework for Verification of Wasserstein Adversarial Robustness	Oct 13, 2021	Adversarial AttackAdversarial Robustness	—Unverified
Boosting Barely Robust Learners: A New Perspective on Adversarial Robustness	Feb 11, 2022	Adversarial Robustness	—Unverified
Dynamical Low-Rank Compression of Neural Networks with Robustness under Adversarial Attacks	May 12, 2025	Adversarial RobustnessLow-rank compression	—Unverified
SOAR: Second-Order Adversarial Regularization	Apr 4, 2020	Adversarial Robustness	—Unverified
A Fundamental Accuracy--Robustness Trade-off in Regression and Classification	Nov 6, 2024	Adversarial Robustnessregression	—Unverified
Adversarial Prompt Distillation for Vision-Language Models	Nov 22, 2024	Adversarial RobustnessAutonomous Driving	—Unverified
Boosting Adversarial Robustness From The Perspective of Effective Margin Regularization	Oct 11, 2022	Adversarial DefenseAdversarial Robustness	—Unverified
Collective Robustness Certificates: Exploiting Interdependence in Graph Neural Networks	Feb 6, 2023	Adversarial RobustnessImage Segmentation	—Unverified
Adversarially Robust Estimate and Risk Analysis in Linear Regression	Dec 18, 2020	Adversarial Robustnessregression	—Unverified
Dynamic Defense Approach for Adversarial Robustness in Deep Neural Networks via Stochastic Ensemble Smoothed Model	May 6, 2021	Adversarial RobustnessAttribute	—Unverified
Boosting Adversarial Robustness and Generalization with Structural Prior	Feb 2, 2025	Adversarial RobustnessDeep Learning	—Unverified
Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation	Jan 1, 2023	Adversarial RobustnessKnowledge Distillation	—Unverified
Adversarial Robustness through Local Linearization	Jul 4, 2019	Adversarial DefenseAdversarial Robustness	—Unverified
A Closer Look at the Adversarial Robustness of Information Bottleneck Models	Jul 12, 2021	Adversarial Robustness	—Unverified
Adversarial Robustness through Dynamic Ensemble Learning	Dec 20, 2024	Adversarial AttackAdversarial Robustness	—Unverified

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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