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 1026–1050 of 1746 papers

Title	Date	Tasks	Status
Masks and Mimicry: Strategic Obfuscation and Impersonation Attacks on Authorship Verification	Mar 24, 2025	Adversarial RobustnessAuthorship Verification	—Unverified
Universal Adversarial Training with Class-Wise Perturbations	Apr 7, 2021	Adversarial Robustness	—Unverified
Measuring Adversarial Datasets	Nov 6, 2023	Adversarial RobustnessDiversity	—Unverified
Measuring Equality in Machine Learning Security Defenses: A Case Study in Speech Recognition	Feb 17, 2023	Adversarial RobustnessFairness	—Unverified
Measuring the Effect of Causal Disentanglement on the Adversarial Robustness of Neural Network Models	Aug 21, 2023	Adversarial RobustnessBenchmarking	—Unverified
Classifier-independent Lower-Bounds for Adversarial Robustness	Jun 17, 2020	Adversarial AttackAdversarial Robustness	—Unverified
Analyzing Adversarial Robustness of Deep Neural Networks in Pixel Space: a Semantic Perspective	Jun 18, 2021	Adversarial Robustness	—Unverified
Meta Invariance Defense Towards Generalizable Robustness to Unknown Adversarial Attacks	Apr 4, 2024	Adversarial DefenseAdversarial Robustness	—Unverified
Towards Achieving Adversarial Robustness Beyond Perceptual Limits	Sep 29, 2021	Adversarial DefenseAdversarial Robustness	—Unverified
Adversarial Amendment is the Only Force Capable of Transforming an Enemy into a Friend	May 18, 2023	Adversarial AttackAdversarial Defense	—Unverified
Analyzing Adversarial Attacks Against Deep Learning for Intrusion Detection in IoT Networks	May 13, 2019	Adversarial RobustnessIntrusion Detection	—Unverified
Adversarial Alignment for LLMs Requires Simpler, Reproducible, and More Measurable Objectives	Feb 17, 2025	Adversarial Robustness	—Unverified
Mind the box: l_1-APGD for sparse adversarial attacks on image classifiers	Mar 1, 2021	Adversarial Robustness	—Unverified
Min-Max Optimization under Delays	Jul 13, 2023	Adversarial RobustnessStochastic Optimization	—Unverified
MIRST-DM: Multi-Instance RST with Drop-Max Layer for Robust Classification of Breast Cancer	May 2, 2022	Adversarial Robustnessimage-classification	—Unverified
An Adversarial Robustness Benchmark for Enterprise Network Intrusion Detection	Feb 25, 2024	Adversarial RobustnessCyber Attack Detection	—Unverified
Mitigating Closed-model Adversarial Examples with Bayesian Neural Modeling for Enhanced End-to-End Speech Recognition	Feb 17, 2022	Adversarial RobustnessAutomatic Speech Recognition	—Unverified
Towards Adversarially Robust and Domain Generalizable Stereo Matching by Rethinking DNN Feature Backbones	Jul 31, 2021	Adversarial RobustnessStereo Matching	—Unverified
Mitigating Low-Frequency Bias: Feature Recalibration and Frequency Attention Regularization for Adversarial Robustness	Jul 4, 2024	Adversarial RobustnessDisentanglement	—Unverified
A Multiclass Boosting Framework for Achieving Fast and Provable Adversarial Robustness	Mar 1, 2021	Adversarial RobustnessObject Recognition	—Unverified
Towards Adversarially Robust Continual Learning	Mar 31, 2023	Adversarial RobustnessContinual Learning	—Unverified
Mixing Classifiers to Alleviate the Accuracy-Robustness Trade-Off	Nov 26, 2023	Adversarial Robustness	—Unverified
Mixture of Robust Experts (MoRE):A Robust Denoising Method towards multiple perturbations	Apr 21, 2021	Adversarial RobustnessDenoising	—Unverified
Universally Robust Graph Neural Networks by Preserving Neighbor Similarity	Jan 18, 2024	Adversarial Robustness	—Unverified
D4: Detection of Adversarial Diffusion Deepfakes Using Disjoint Ensembles	Feb 11, 2022	Adversarial RobustnessDeepFake Detection	—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