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Adversarial Robustness

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하위 태스크: 0
평가표: 7
보존된 평가 기록: 33

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

코드

관련 논문과 평가 결과에 연결된 구현입니다. 출처에서 확인된 저자 구현에는 공식 코드 표시가 있습니다.

https://github.com/lebronx/neuro-symbolic-verification

공식 코드

Neuro-Symbolic Verification of Deep Neural Networks

https://github.com/leegerpeng/autoae

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Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles

https://github.com/leonackermann/robust-neurons

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On the Relationship between Skill Neurons and Robustness in Prompt Tuning

https://github.com/leoranlmia/CAR-DQN

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Towards Optimal Adversarial Robust Q-learning with Bellman Infinity-error

https://github.com/lethaiq/shield-defend-adversarial-texts

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SHIELD: Defending Textual Neural Networks against Multiple Black-Box Adversarial Attacks with Stochastic Multi-Expert Patcher

https://github.com/liamdugan/raid

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RAID: A Shared Benchmark for Robust Evaluation of Machine-Generated Text Detectors

https://github.com/lightonai/adversarial-robustness-by-design

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Adversarial Robustness by Design through Analog Computing and Synthetic Gradients

https://github.com/lijiefan/advcl

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When Does Contrastive Learning Preserve Adversarial Robustness from Pretraining to Finetuning?

https://github.com/lintotao/out-of-bbox-attack

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Out-of-Bounding-Box Triggers: A Stealthy Approach to Cheat Object Detectors

https://github.com/lionel-w2/fap

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Few-Shot Adversarial Prompt Learning on Vision-Language Models

https://github.com/lisaoakley/dtmc_attack_synthesis

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Adversarial Robustness Verification and Attack Synthesis in Stochastic Systems

https://github.com/liuxingbin/cat

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CAT:Collaborative Adversarial Training

https://github.com/liuxingbin/lfrc

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Latent Feature Relation Consistency for Adversarial Robustness

https://github.com/liuye6666/adaptive_auto_attack

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Practical Evaluation of Adversarial Robustness via Adaptive Auto Attack

https://github.com/lixiaothu/laat

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Language-Driven Anchors for Zero-Shot Adversarial Robustness

https://github.com/lixiaothu/privacy_and_aug

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On the Privacy Effect of Data Enhancement via the Lens of Memorization

https://github.com/lmb-freiburg/understanding_flow_robustness

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Towards Understanding Adversarial Robustness of Optical Flow Networks

https://github.com/locuslab/orthogonal-convolutions

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Orthogonalizing Convolutional Layers with the Cayley Transform

https://github.com/locuslab/projected_sinkhorn

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Wasserstein Adversarial Examples via Projected Sinkhorn Iterations

https://github.com/locuslab/robust_union

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Adversarial Robustness Against the Union of Multiple Perturbation Models

https://github.com/locuslab/smoothing

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Certified Adversarial Robustness via Randomized Smoothing

https://github.com/locuslab/smoothinv

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Single Image Backdoor Inversion via Robust Smoothed Classifiers

https://github.com/maayango285/Adversaries-With-Incentives

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Adversaries With Incentives: A Strategic Alternative to Adversarial Robustness

https://github.com/mackelab/rabi

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Adversarial robustness of amortized Bayesian inference

https://github.com/mamerzouk/adversarial-purification

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Diffusion-based Adversarial Purification for Intrusion Detection

https://github.com/marcosaelzer/nn2nfa

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Verifying And Interpreting Neural Networks using Finite Automata

https://github.com/mariusarvinte/robust-face-verification

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Robust Face Verification via Disentangled Representations

https://github.com/matthewwicker/CertifiableBayesianInference

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Bayesian Inference with Certifiable Adversarial Robustness

https://github.com/matthewwicker/GradientFreeAttacksBNNs

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Gradient-Free Adversarial Attacks for Bayesian Neural Networks

https://github.com/matthewwicker/adversarialrobustnesscertificationforbnns

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Adversarial Robustness Certification for Bayesian Neural Networks

https://github.com/max-andr/provably-robust-boosting

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Provably Robust Boosted Decision Stumps and Trees against Adversarial Attacks

https://github.com/max-andr/square-attack

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Reliable evaluation of adversarial robustness with an ensemble of diverse parameter-free attacks

https://github.com/mazurowski-lab/intrinsic-properties

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The Effect of Intrinsic Dataset Properties on Generalization: Unraveling Learning Differences Between Natural and Medical Images

https://github.com/mdasifkhan/robustnessvae

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Adversarial robustness of VAEs through the lens of local geometry

https://github.com/meet-cjli/ctrl

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An Embarrassingly Simple Backdoor Attack on Self-supervised Learning

https://github.com/metaphors/TSAttack

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TSCheater: Generating High-Quality Tibetan Adversarial Texts via Visual Similarity

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