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 551–575 of 1746 papers

Title	Date	Tasks	Status	Hype
Robust Mixture-of-Expert Training for Convolutional Neural Networks	Aug 19, 2023	Adversarial Robustness	CodeCode Available	1
Causal Adversarial Perturbations for Individual Fairness and Robustness in Heterogeneous Data Spaces	Aug 17, 2023	Adversarial RobustnessFairness	—Unverified	0
Benchmarking Adversarial Robustness of Compressed Deep Learning Models	Aug 16, 2023	Adversarial RobustnessBenchmarking	—Unverified	0
Expressivity of Graph Neural Networks Through the Lens of Adversarial Robustness	Aug 16, 2023	Adversarial RobustnessSubgraph Counting	CodeCode Available	0
Enhancing the Antidote: Improved Pointwise Certifications against Poisoning Attacks	Aug 15, 2023	Adversarial Robustness	—Unverified	0
A Survey on Deep Neural Network Pruning-Taxonomy, Comparison, Analysis, and Recommendations	Aug 13, 2023	Adversarial RobustnessNetwork Pruning	CodeCode Available	2
On the Interplay of Convolutional Padding and Adversarial Robustness	Aug 12, 2023	Adversarial Robustness	CodeCode Available	0
Large Language Models to Identify Social Determinants of Health in Electronic Health Records	Aug 11, 2023	Adversarial RobustnessEthics	CodeCode Available	1
TrajPAC: Towards Robustness Verification of Pedestrian Trajectory Prediction Models	Aug 11, 2023	Adversarial RobustnessAutonomous Vehicles	CodeCode Available	1
ModSec-AdvLearn: Countering Adversarial SQL Injections with Robust Machine Learning	Aug 9, 2023	Adversarial Robustness	CodeCode Available	0
Improving Performance of Semi-Supervised Learning by Adversarial Attacks	Aug 8, 2023	Adversarial Robustnessimage-classification	—Unverified	0
Enhancing Adversarial Robustness in Low-Label Regime via Adaptively Weighted Regularization and Knowledge Distillation	Aug 8, 2023	Adversarial RobustnessKnowledge Distillation	CodeCode Available	0
Fixed Inter-Neuron Covariability Induces Adversarial Robustness	Aug 7, 2023	Adversarial Robustness	—Unverified	0
Unsupervised Adversarial Detection without Extra Model: Training Loss Should Change	Aug 7, 2023	Adversarial Robustness	CodeCode Available	0
Exploring the Physical World Adversarial Robustness of Vehicle Detection	Aug 7, 2023	Adversarial AttackAdversarial Robustness	—Unverified	0
RobustMQ: Benchmarking Robustness of Quantized Models	Aug 4, 2023	Adversarial RobustnessBenchmarking	—Unverified	0
Improving Generalization of Adversarial Training via Robust Critical Fine-Tuning	Aug 1, 2023	Adversarial Robustness	—Unverified	0
Robust Linear Regression: Phase-Transitions and Precise Tradeoffs for General Norms	Aug 1, 2023	Adversarial Robustnessregression	—Unverified	0
Beyond One-Hot-Encoding: Injecting Semantics to Drive Image Classifiers	Aug 1, 2023	Adversarial Robustnessimage-classification	CodeCode Available	0
Dynamic ensemble selection based on Deep Neural Network Uncertainty Estimation for Adversarial Robustness	Aug 1, 2023	Adversarial AttackAdversarial Robustness	—Unverified	0
Towards Trustworthy and Aligned Machine Learning: A Data-centric Survey with Causality Perspectives	Jul 31, 2023	Adversarial RobustnessFairness	—Unverified	0
Benchmarking and Analyzing Robust Point Cloud Recognition: Bag of Tricks for Defending Adversarial Examples	Jul 31, 2023	Adversarial RobustnessBenchmarking	CodeCode Available	1
Characterizing Data Point Vulnerability via Average-Case Robustness	Jul 26, 2023	Adversarial RobustnessMulti-class Classification	CodeCode Available	0
Exploring the Sharpened Cosine Similarity	Jul 25, 2023	Adversarial Robustnessimage-classification	—Unverified	0
On the unreasonable vulnerability of transformers for image restoration -- and an easy fix	Jul 25, 2023	Adversarial AttackAdversarial Robustness	—Unverified	0

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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