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Adversarial Robustness

Adversarial Robustness evaluates the vulnerabilities of machine learning models under various types of adversarial attacks.

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 1501–1550 of 1746 papers

TitleStatusHype
From Sound Representation to Model Robustness—0
Robust Collective Classification against Structural Attacks—0
Hierarchical Verification for Adversarial Robustness—0
On Adversarial Robustness: A Neural Architecture Search perspectiveCode0
Failure Modes of Variational Autoencoders and Their Effects on Downstream Tasks—0
Adversarial robustness via robust low rank representationsCode0
How benign is benign overfitting?—0
On Connections between Regularizations for Improving DNN Robustness—0
Trace-Norm Adversarial Examples—0
Opportunities and Challenges in Deep Learning Adversarial Robustness: A Survey—0
Biologically Inspired Mechanisms for Adversarial RobustnessCode0
Sharp Statistical Guarantees for Adversarially Robust Gaussian Classification—0
Improving Calibration through the Relationship with Adversarial Robustness—0
Adversarial Robustness of Deep Sensor Fusion Models—0
How do SGD hyperparameters in natural training affect adversarial robustness?—0
Local Convolutions Cause an Implicit Bias towards High Frequency Adversarial Examples—0
Local Competition and Uncertainty for Adversarial Robustness in Deep Learning—0
The Dilemma Between Data Transformations and Adversarial Robustness for Time Series Application Systems—0
Using Wavelets and Spectral Methods to Study Patterns in Image-Classification DatasetsCode0
Classifier-independent Lower-Bounds for Adversarial Robustness—0
SPLASH: Learnable Activation Functions for Improving Accuracy and Adversarial Robustness—0
On sparse connectivity, adversarial robustness, and a novel model of the artificial neuron—0
Debona: Decoupled Boundary Network Analysis for Tighter Bounds and Faster Adversarial Robustness ProofsCode0
Improving Adversarial Robustness via Unlabeled Out-of-Domain Data—0
On Saliency Maps and Adversarial Robustness—0
Deterministic Gaussian Averaged Neural NetworksCode0
The Lipschitz Constant of Self-Attention—0
Adversarial Feature DesensitizationCode0
UFO-BLO: Unbiased First-Order Bilevel Optimization—0
Robust Face Verification via Disentangled RepresentationsCode0
Rethinking Empirical Evaluation of Adversarial Robustness Using First-Order Attack MethodsCode0
Investigating Vulnerability to Adversarial Examples on Multimodal Data Fusion in Deep Learning—0
Robust Ensemble Model Training via Random Layer Sampling Against Adversarial Attack—0
Revisiting Role of Autoencoders in Adversarial Settings—0
Increasing-Margin Adversarial (IMA) Training to Improve Adversarial Robustness of Neural NetworksCode0
Toward Adversarial Robustness by Diversity in an Ensemble of Specialized Deep Neural Networks—0
Towards Assessment of Randomized Smoothing Mechanisms for Certifying Adversarial Robustness—0
Class-Aware Domain Adaptation for Improving Adversarial Robustness—0
Measuring Adversarial Robustness using a Voronoi-Epsilon AdversaryCode0
Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware?—0
Biologically inspired sleep algorithm for increased generalization and adversarial robustness in deep neural networks—0
Adversarial Learning Guarantees for Linear Hypotheses and Neural Networks—0
Improving the Interpretability of fMRI Decoding using Deep Neural Networks and Adversarial RobustnessCode0
How to compare adversarial robustness of classifiers from a global perspectiveCode0
QUANOS- Adversarial Noise Sensitivity Driven Hybrid Quantization of Neural Networks—0
Certifying Joint Adversarial Robustness for Model EnsemblesCode0
Adversarially Robust Streaming Algorithms via Differential Privacy—0
Adversarial Robustness Guarantees for Random Deep Neural NetworksCode0
Certifiable Robustness to Adversarial State Uncertainty in Deep Reinforcement Learning—0
Approximate Manifold Defense Against Multiple Adversarial PerturbationsCode0
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All datasetsAdvGLUECIFAR-10ImageNetImageNet-AImageNet-CStylized ImageNetCIFAR-100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeBERTa (single model)Accuracy0.61—Unverified
2ALBERT (single model)Accuracy0.59—Unverified
3T5 (single model)Accuracy0.57—Unverified
4SMART_RoBERTa (single model)Accuracy0.54—Unverified
5FreeLB (single model)Accuracy0.5—Unverified
6RoBERTa (single model)Accuracy0.5—Unverified
7InfoBERT (single model)Accuracy0.46—Unverified
8ELECTRA (single model)Accuracy0.42—Unverified
9BERT (single model)Accuracy0.34—Unverified
10SMART_BERT (single model)Accuracy0.3—Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed classifierAccuracy95.23—Unverified
2Stochastic-LWTA/PGD/WideResNet-34-10Accuracy92.26—Unverified
3Stochastic-LWTA/PGD/WideResNet-34-5Accuracy91.88—Unverified
4GLOT-DRAccuracy84.13—Unverified
5TRADES-ANCRA/ResNet18Accuracy81.7—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (SGD, Cosine)Accuracy77.4—Unverified
2ResNet-50 (SGD, Step)Accuracy76.9—Unverified
3DeiT-S (AdamW, Cosine)Accuracy76.8—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy76.4—Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy12.2—Unverified
2ResNet-50 (SGD, Cosine)Accuracy3.3—Unverified
3ResNet-50 (SGD, Step)Accuracy3.2—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy3.1—Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (AdamW, Cosine)mean Corruption Error (mCE)59.3—Unverified
2ResNet-50 (SGD, Step)mean Corruption Error (mCE)57.9—Unverified
3ResNet-50 (SGD, Cosine)mean Corruption Error (mCE)56.9—Unverified
4DeiT-S (AdamW, Cosine)mean Corruption Error (mCE)48—Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy13—Unverified
2ResNet-50 (SGD, Cosine)Accuracy8.4—Unverified
3ResNet-50 (SGD, Step)Accuracy8.3—Unverified
4ResNet-50 (AdamW, Cosine)Accuracy8.1—Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed ClassifierClean Accuracy85.21—Unverified
2ResNet18/MART-ANCRAClean Accuracy60.1—Unverified