SOTAVerified

Adversarial Robustness

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

Papers

Showing 201250 of 1746 papers

TitleStatusHype
Can Large Language Models Improve the Adversarial Robustness of Graph Neural Networks?Code1
CARBEN: Composite Adversarial Robustness BenchmarkCode1
Adversarial Robustness via Random Projection FiltersCode1
NeRFool: Uncovering the Vulnerability of Generalizable Neural Radiance Fields against Adversarial PerturbationsCode1
CARLA-GeAR: a Dataset Generator for a Systematic Evaluation of Adversarial Robustness of Vision ModelsCode1
The Eigenlearning Framework: A Conservation Law Perspective on Kernel Regression and Wide Neural NetworksCode1
CBA: Contextual Background Attack against Optical Aerial Detection in the Physical WorldCode1
On Evaluating Adversarial RobustnessCode1
Demystifying Causal Features on Adversarial Examples and Causal Inoculation for Robust Network by Adversarial Instrumental Variable RegressionCode1
On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-LearningCode1
Certified Adversarial Robustness via Randomized SmoothingCode1
(Certified!!) Adversarial Robustness for Free!Code1
Certified Training: Small Boxes are All You NeedCode1
On the Duality Between Sharpness-Aware Minimization and Adversarial TrainingCode1
Drawing Robust Scratch Tickets: Subnetworks with Inborn Robustness Are Found within Randomly Initialized NetworksCode1
AdvDrop: Adversarial Attack to DNNs by Dropping InformationCode1
Adversarial Training with Complementary Labels: On the Benefit of Gradually Informative AttacksCode1
Adversarial Vertex Mixup: Toward Better Adversarially Robust GeneralizationCode1
Adversarial Visual Robustness by Causal InterventionCode1
Adversarial vulnerability of powerful near out-of-distribution detectionCode1
Adversarial Vulnerability of Randomized EnsemblesCode1
Adversarial Machine Learning: Bayesian PerspectivesCode1
GenoArmory: A Unified Evaluation Framework for Adversarial Attacks on Genomic Foundation ModelsCode1
PatchGuard: Adversarially Robust Anomaly Detection and Localization through Vision Transformers and Pseudo AnomaliesCode1
Perceptual Adversarial Robustness: Defense Against Unseen Threat ModelsCode1
AdvRush: Searching for Adversarially Robust Neural ArchitecturesCode1
Comparing the Robustness of Modern No-Reference Image- and Video-Quality Metrics to Adversarial AttacksCode1
Practical Evaluation of Adversarial Robustness via Adaptive Auto AttackCode1
Pre-trained Model Guided Fine-Tuning for Zero-Shot Adversarial RobustnessCode1
Composite Adversarial AttacksCode1
Adversarial Attack and Defense in Deep RankingCode1
Consistency Regularization for Adversarial RobustnessCode1
Adversarial Prompt Tuning for Vision-Language ModelsCode1
AGKD-BML: Defense Against Adversarial Attack by Attention Guided Knowledge Distillation and Bi-directional Metric LearningCode1
Enhancing Intrinsic Adversarial Robustness via Feature Pyramid DecoderCode1
Adversarial Attack and Defense Strategies for Deep Speaker Recognition SystemsCode1
GARNET: Reduced-Rank Topology Learning for Robust and Scalable Graph Neural NetworksCode1
Consistency Regularization for Certified Robustness of Smoothed ClassifiersCode1
Adversarial Attack on Deep Learning-Based Splice LocalizationCode1
Rate Coding or Direct Coding: Which One is Better for Accurate, Robust, and Energy-efficient Spiking Neural Networks?Code1
Learning Adversarially Robust Representations via Worst-Case Mutual Information MaximizationCode1
Regularization with Latent Space Virtual Adversarial TrainingCode1
A Light Recipe to Train Robust Vision TransformersCode1
Adversarial Robustification via Text-to-Image Diffusion ModelsCode1
Rethinking and Improving Robustness of Convolutional Neural Networks: a Shapley Value-based Approach in Frequency DomainCode1
Revisiting Adversarial Robustness Distillation: Robust Soft Labels Make Student BetterCode1
Decision-based Black-box Attack Against Vision Transformers via Patch-wise Adversarial RemovalCode1
An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN ArchitecturesCode1
Adversarial Image Color Transformations in Explicit Color Filter SpaceCode1
Robust Deep Reinforcement Learning through Bootstrapped Opportunistic CurriculumCode1
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1DeBERTa (single model)Accuracy0.61Unverified
2ALBERT (single model)Accuracy0.59Unverified
3T5 (single model)Accuracy0.57Unverified
4SMART_RoBERTa (single model)Accuracy0.54Unverified
5FreeLB (single model)Accuracy0.5Unverified
6RoBERTa (single model)Accuracy0.5Unverified
7InfoBERT (single model)Accuracy0.46Unverified
8ELECTRA (single model)Accuracy0.42Unverified
9BERT (single model)Accuracy0.34Unverified
10SMART_BERT (single model)Accuracy0.3Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed classifierAccuracy95.23Unverified
2Stochastic-LWTA/PGD/WideResNet-34-10Accuracy92.26Unverified
3Stochastic-LWTA/PGD/WideResNet-34-5Accuracy91.88Unverified
4GLOT-DRAccuracy84.13Unverified
5TRADES-ANCRA/ResNet18Accuracy81.7Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (SGD, Cosine)Accuracy77.4Unverified
2ResNet-50 (SGD, Step)Accuracy76.9Unverified
3DeiT-S (AdamW, Cosine)Accuracy76.8Unverified
4ResNet-50 (AdamW, Cosine)Accuracy76.4Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy12.2Unverified
2ResNet-50 (SGD, Cosine)Accuracy3.3Unverified
3ResNet-50 (SGD, Step)Accuracy3.2Unverified
4ResNet-50 (AdamW, Cosine)Accuracy3.1Unverified
#ModelMetricClaimedVerifiedStatus
1ResNet-50 (AdamW, Cosine)mean Corruption Error (mCE)59.3Unverified
2ResNet-50 (SGD, Step)mean Corruption Error (mCE)57.9Unverified
3ResNet-50 (SGD, Cosine)mean Corruption Error (mCE)56.9Unverified
4DeiT-S (AdamW, Cosine)mean Corruption Error (mCE)48Unverified
#ModelMetricClaimedVerifiedStatus
1DeiT-S (AdamW, Cosine)Accuracy13Unverified
2ResNet-50 (SGD, Cosine)Accuracy8.4Unverified
3ResNet-50 (SGD, Step)Accuracy8.3Unverified
4ResNet-50 (AdamW, Cosine)Accuracy8.1Unverified
#ModelMetricClaimedVerifiedStatus
1Mixed ClassifierClean Accuracy85.21Unverified
2ResNet18/MART-ANCRAClean Accuracy60.1Unverified