SOTAVerified

Adversarial Attack

An Adversarial Attack is a technique to find a perturbation that changes the prediction of a machine learning model. The perturbation can be very small and imperceptible to human eyes.

Source: Recurrent Attention Model with Log-Polar Mapping is Robust against Adversarial Attacks

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 21–30 of 1808 papers

TitleStatusHype
CAPAA: Classifier-Agnostic Projector-Based Adversarial AttackCode0
Adversarial Threat Vectors and Risk Mitigation for Retrieval-Augmented Generation Systems—0
3D Gaussian Splat VulnerabilitiesCode1
Learning Safety Constraints for Large Language ModelsCode1
SafeScientist: Toward Risk-Aware Scientific Discoveries by LLM AgentsCode1
Adversarial Semantic and Label Perturbation Attack for Pedestrian Attribute RecognitionCode0
Seeing the Threat: Vulnerabilities in Vision-Language Models to Adversarial Attack—0
Adversarial Attacks against Closed-Source MLLMs via Feature Optimal AlignmentCode2
TabAttackBench: A Benchmark for Adversarial Attacks on Tabular DataCode0
A Framework for Adversarial Analysis of Decision Support Systems Prior to Deployment—0
Show:102550
← PrevPage 3 of 181Next →
All datasetsCIFAR-10CIFAR-100

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1Xu et al.Attack: PGD2078.68—Unverified
23-ensemble of multi-resolution self-ensemblesAttack: AutoAttack78.13—Unverified
3TRADES-ANCRA/ResNet18Attack: AutoAttack59.7—Unverified
4AdvTraining [madry2018]Attack: PGD2048.44—Unverified
5TRADES [zhang2019b]Attack: PGD2045.9—Unverified
6XU-NetRobust Accuracy1—Unverified
#ModelMetricClaimedVerifiedStatus
13-ensemble of multi-resolution self-ensemblesAttack: AutoAttack51.28—Unverified
2multi-resolution self-ensemblesAttack: AutoAttack47.85—Unverified