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 826–850 of 1746 papers

Title	Date	Tasks	Status
How Robust are Randomized Smoothing based Defenses to Data Poisoning?	Dec 2, 2020	Adversarial RobustnessBilevel Optimization	—Unverified
Adversarial Robustness in Deep Learning: Attacks on Fragile Neurons	Jan 31, 2022	Adversarial AttackAdversarial Robustness	—Unverified
Efficient Certification for Probabilistic Robustness	Sep 29, 2021	Adversarial Robustness	—Unverified
How to beat a Bayesian adversary	Jul 11, 2024	Adversarial Robustness	—Unverified
How to Enhance Downstream Adversarial Robustness (almost) without Touching the Pre-Trained Foundation Model?	Apr 15, 2025	Adversarial RobustnessContrastive Learning	—Unverified
A3T: Adversarially Augmented Adversarial Training	Jan 12, 2018	Adversarial RobustnessBIG-bench Machine Learning	—Unverified
Improving Robust Generalization by Direct PAC-Bayesian Bound Minimization	Nov 22, 2022	Adversarial Robustness	—Unverified
Improving Robustness of Deep Convolutional Neural Networks via Multiresolution Learning	Sep 24, 2023	Adversarial Robustness	—Unverified
Improving White-box Robustness of Pre-processing Defenses via Joint Adversarial Training	Jun 10, 2021	Adversarial DefenseAdversarial Robustness	—Unverified
Intrinsic Biologically Plausible Adversarial Robustness	Sep 29, 2023	Adversarial Robustness	—Unverified
Efficiency-driven Hardware Optimization for Adversarially Robust Neural Networks	May 9, 2021	Adversarial Robustness	—Unverified
Hybrid Deep Learning Model using SPCAGAN Augmentation for Insider Threat Analysis	Mar 6, 2022	Adversarial RobustnessAnomaly Detection	—Unverified
Hydra: An Agentic Reasoning Approach for Enhancing Adversarial Robustness and Mitigating Hallucinations in Vision-Language Models	Apr 19, 2025	Adversarial AttackAdversarial Defense	—Unverified
Improving the Adversarial Robustness for Speaker Verification by Self-Supervised Learning	Jun 1, 2021	Adversarial DefenseAdversarial Robustness	—Unverified
Effects of Loss Functions And Target Representations on Adversarial Robustness	Dec 1, 2018	Adversarial Robustness	—Unverified
Adversarially Robust Spiking Neural Networks with Sparse Connectivity	May 16, 2025	Adversarial Robustness	—Unverified
Effective, Efficient and Robust Neural Architecture Search	Nov 19, 2020	Adversarial RobustnessNeural Architecture Search	—Unverified
Improving Hyperspectral Adversarial Robustness Under Multiple Attacks	Oct 28, 2022	Adversarial RobustnessSemantic Segmentation	—Unverified
Adversarial Robustness Guarantees for Quantum Classifiers	May 16, 2024	Adversarial RobustnessQuantum Machine Learning	—Unverified
I Can Find You in Seconds! Leveraging Large Language Models for Code Authorship Attribution	Jan 14, 2025	Adversarial RobustnessAttribute	—Unverified
IDEA: Invariant Defense for Graph Adversarial Robustness	May 25, 2023	Adversarial Robustness	—Unverified
Edge-Only Universal Adversarial Attacks in Distributed Learning	Nov 15, 2024	Adversarial Robustness	—Unverified
Improving Graph Neural Networks via Adversarial Robustness Evaluation	Dec 14, 2024	Adversarial Robustness	—Unverified
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning	Aug 1, 2023	Adversarial Robustness	—Unverified
Are classical deep neural networks weakly adversarially robust?	May 28, 2025	Adversarial DefenseAdversarial 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