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 651–675 of 1746 papers

Title	Date	Tasks	Status	Score
Approximate Manifold Defense Against Multiple Adversarial Perturbations	Apr 5, 2020	Adversarial Robustnessimage-classification	CodeCode Available	5
Evaluation of Hate Speech Detection Using Large Language Models and Geographical Contextualization	Feb 26, 2025	Adversarial RobustnessBinary Classification	CodeCode Available	5
Adversarial Examples for k-Nearest Neighbor Classifiers Based on Higher-Order Voronoi Diagrams	Nov 19, 2020	Adversarial Robustness	CodeCode Available	5
Evolution-based Region Adversarial Prompt Learning for Robustness Enhancement in Vision-Language Models	Mar 17, 2025	Adversarial RobustnessPrompt Learning	CodeCode Available	5
Adversarial Concurrent Training: Optimizing Robustness and Accuracy Trade-off of Deep Neural Networks	Aug 16, 2020	Adversarial Robustness	CodeCode Available	5
Disentangling Adversarial Robustness in Directions of the Data Manifold	Jan 1, 2021	Adversarial Robustness	CodeCode Available	5
Hardening DNNs against Transfer Attacks during Network Compression using Greedy Adversarial Pruning	Jun 15, 2022	Adversarial RobustnessQuantization	CodeCode Available	5
Expanding Scope: Adapting English Adversarial Attacks to Chinese	Jun 8, 2023	Adversarial AttackAdversarial Robustness	CodeCode Available	5
Disentangling Adversarial Robustness and Generalization	Dec 3, 2018	Adversarial Robustness	CodeCode Available	5
A PAC-Bayes Analysis of Adversarial Robustness	Feb 19, 2021	Adversarial RobustnessGeneralization Bounds	CodeCode Available	5
GREAT Score: Global Robustness Evaluation of Adversarial Perturbation using Generative Models	Apr 19, 2023	Adversarial Robustness	CodeCode Available	5
Understanding the Robustness of Graph Neural Networks against Adversarial Attacks	Jun 20, 2024	Adversarial Robustness	CodeCode Available	5
Global-Local Regularization Via Distributional Robustness	Mar 1, 2022	Adversarial RobustnessDomain Adaptation	CodeCode Available	5
Explaining Adversarial Vulnerability with a Data Sparsity Hypothesis	Mar 1, 2021	Adversarial Robustness	CodeCode Available	5
Gradient-Free Adversarial Attacks for Bayesian Neural Networks	Dec 23, 2020	Adversarial RobustnessBayesian Inference	CodeCode Available	5
Mixup Model Merge: Enhancing Model Merging Performance through Randomized Linear Interpolation	Feb 21, 2025	Adversarial RobustnessData Augmentation	CodeCode Available	5
The interplay of robustness and generalization in quantum machine learning	Jun 10, 2025	Adversarial RobustnessQuantum Machine Learning	CodeCode Available	5
Diffusion Denoised Smoothing for Certified and Adversarial Robust Out-Of-Distribution Detection	Mar 27, 2023	Adversarial RobustnessOut-of-Distribution Detection	CodeCode Available	5
Give me a hint: Can LLMs take a hint to solve math problems?	Oct 8, 2024	Adversarial RobustnessMath	CodeCode Available	5
Exploring Adversarial Attacks and Defenses in Vision Transformers trained with DINO	Jun 14, 2022	Adversarial Robustness	CodeCode Available	5
Hierarchical Distribution-Aware Testing of Deep Learning	May 17, 2022	Adversarial RobustnessData Compression	CodeCode Available	5
Diffusion-based Adversarial Purification for Intrusion Detection	Jun 25, 2024	Adversarial PurificationAdversarial Robustness	CodeCode Available	5
Generating Adversarial Examples with Adversarial Networks	Jan 8, 2018	Adversarial Robustness	CodeCode Available	5
Generating Adversarial Samples in Mini-Batches May Be Detrimental To Adversarial Robustness	Mar 30, 2023	Adversarial Robustness	CodeCode Available	5
DiffPAD: Denoising Diffusion-based Adversarial Patch Decontamination	Oct 31, 2024	Adversarial RobustnessBinarization	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