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 1–25 of 1746 papers

Title	Date	Tasks	Status	Hype
AugLy: Data Augmentations for Robustness	Jan 17, 2022	Adversarial RobustnessData Augmentation	CodeCode Available	5
LORE: Lagrangian-Optimized Robust Embeddings for Visual Encoders	May 24, 2025	Adversarial RobustnessOut-of-Distribution Generalization	CodeCode Available	4
Adversarial Robustness Toolbox v1.0.0	Jul 3, 2018	Adversarial RobustnessBIG-bench Machine Learning	CodeCode Available	3
Improving Alignment and Robustness with Circuit Breakers	Jun 6, 2024	Adversarial Robustness	CodeCode Available	3
Indicators of Attack Failure: Debugging and Improving Optimization of Adversarial Examples	Jun 18, 2021	Adversarial Robustness	CodeCode Available	3
Quantifying the robustness of deep multispectral segmentation models against natural perturbations and data poisoning	May 18, 2023	Adversarial RobustnessData Poisoning	CodeCode Available	3
Fast Minimum-norm Adversarial Attacks through Adaptive Norm Constraints	Feb 25, 2021	Adversarial AttackAdversarial Robustness	CodeCode Available	2
RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors	May 13, 2024	Adversarial RobustnessText Detection	CodeCode Available	2
On Evaluating Adversarial Robustness of Large Vision-Language Models	May 26, 2023	Adversarial Robustnessmultimodal generation	CodeCode Available	2
Dissecting Adversarial Robustness of Multimodal LM Agents	Jun 18, 2024	Adversarial RobustnessAdversarial Text	CodeCode Available	2
CLAIMED, a visual and scalable component library for Trusted AI	Mar 4, 2021	Adversarial RobustnessFairness	CodeCode Available	2
MIBench: A Comprehensive Framework for Benchmarking Model Inversion Attack and Defense	Oct 7, 2024	Adversarial RobustnessBenchmarking	CodeCode Available	2
Artificial Kuramoto Oscillatory Neurons	Oct 17, 2024	Adversarial RobustnessObject Discovery	CodeCode Available	2
ALERT: A Comprehensive Benchmark for Assessing Large Language Models' Safety through Red Teaming	Apr 6, 2024	Adversarial RobustnessDialogue Safety Prediction	CodeCode Available	2
An Unsupervised Approach to Achieve Supervised-Level Explainability in Healthcare Records	Jun 13, 2024	Adversarial RobustnessExplainable Artificial Intelligence (XAI)	CodeCode Available	2
Authorship Obfuscation in Multilingual Machine-Generated Text Detection	Jan 15, 2024	Adversarial RobustnessBenchmarking	CodeCode Available	2
One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models	Mar 4, 2024	Adversarial AttackAdversarial Robustness	CodeCode Available	2
A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations	Aug 13, 2023	Adversarial RobustnessNetwork Pruning	CodeCode Available	2
Adversarial Robustification via Text-to-Image Diffusion Models	Jul 26, 2024	Adversarial Robustnesszero-shot-classification	CodeCode Available	1
GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation Models	May 16, 2025	Adversarial AttackAdversarial Defense	CodeCode Available	1
Adversarial Image Color Transformations in Explicit Color Filter Space	Nov 12, 2020	Adversarial Robustness	CodeCode Available	1
Adversarial Pruning: A Survey and Benchmark of Pruning Methods for Adversarial Robustness	Sep 2, 2024	Adversarial RobustnessNetwork Pruning	CodeCode Available	1
Adversarial Machine Learning: Bayesian Perspectives	Mar 7, 2020	Adversarial RobustnessBIG-bench Machine Learning	CodeCode Available	1
Adversarially Robust Distillation	May 23, 2019	Adversarial RobustnessKnowledge Distillation	CodeCode Available	1
Adversarial Prompt Tuning for Vision-Language Models	Nov 19, 2023	Adversarial Robustness	CodeCode Available	1

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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