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 501–525 of 1746 papers

Title	Date	Tasks	Status
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection	Feb 25, 2024	Adversarial RobustnessCyber Attack Detection	—Unverified
A Comparative Analysis of Adversarial Robustness for Quantum and Classical Machine Learning Models	Apr 24, 2024	Adversarial RobustnessQuantum Machine 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
Adversarial Robustness through Dynamic Ensemble Learning	Dec 20, 2024	Adversarial AttackAdversarial Robustness	—Unverified
A Domain-Based Taxonomy of Jailbreak Vulnerabilities in Large Language Models	Apr 7, 2025	Adversarial Robustness	—Unverified
Evaluating Adversarial Robustness on Document Image Classification	Apr 24, 2023	Adversarial AttackAdversarial Robustness	—Unverified
Evaluating the Adversarial Robustness of Detection Transformers	Dec 25, 2024	Adversarial RobustnessAutonomous Driving	—Unverified
DecodingTrust: A Comprehensive Assessment of Trustworthiness in GPT Models	Jun 20, 2023	Adversarial RobustnessEthics	—Unverified
Exploiting Excessive Invariance caused by Norm-Bounded Adversarial Robustness	Mar 25, 2019	Adversarial Robustness	—Unverified
Exploring the Hyperparameter Landscape of Adversarial Robustness	May 9, 2019	Adversarial RobustnessHyperparameter Optimization	—Unverified
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks	May 1, 2020	Adversarial RobustnessGeneral Classification	—Unverified
Adversarial Robustness Through Artifact Design	Feb 7, 2024	Adversarial RobustnessTraffic Sign Recognition	—Unverified
Accelerating Adversarial Perturbation by 50% with Semi-backward Propagation	Nov 9, 2022	Adversarial Robustness	—Unverified
Binarized ResNet: Enabling Robust Automatic Modulation Classification at the resource-constrained Edge	Oct 27, 2021	Adversarial RobustnessBinarization	—Unverified
Bi-fidelity Evolutionary Multiobjective Search for Adversarially Robust Deep Neural Architectures	Jul 12, 2022	Adversarial RobustnessMultiobjective Optimization	—Unverified
Towards Bridging the gap between Empirical and Certified Robustness against Adversarial Examples	Feb 9, 2021	Adversarial Robustness	—Unverified
Ensemble Adversarial Defense via Integration of Multiple Dispersed Low Curvature Models	Mar 25, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
Biased Multi-Domain Adversarial Training	Sep 29, 2021	Adversarial Robustness	—Unverified
Beyond Worst-Case Online Classification: VC-Based Regret Bounds for Relaxed Benchmarks	Apr 14, 2025	Adversarial RobustnessBinary Classification	—Unverified
Adversarial Robustness: Softmax versus Openmax	Aug 5, 2017	Adversarial RobustnessOpen Set Learning	—Unverified
Beyond Pruning Criteria: The Dominant Role of Fine-Tuning and Adaptive Ratios in Neural Network Robustness	Oct 19, 2024	Adversarial RobustnessSensitivity	—Unverified
Adversarial Robustness Overestimation and Instability in TRADES	Oct 10, 2024	Adversarial Robustness	—Unverified
Adversarially Robust and Explainable Model Compression with On-Device Personalization for Text Classification	Jan 10, 2021	Adversarial RobustnessGeneral Classification	—Unverified
Improving Transformation-based Defenses against Adversarial Examples with First-order Perturbations	Mar 8, 2021	Adversarial 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