However, the issue of adversarial robustness of models for code has gone largely unnoticed. In this work, we explore this issue by: (i) instantiating adversarial attacks for code (a domain with discrete and highly structured inputs), (ii) showing that, similar to other domains, neural models...
On the Adversarial Robustness of Instruction-Tuned LargeLanguage Models for CodeMd Imran HossenUniversity of Louisiana at LafayetteLafayette, Louisiana, USAmd-imran.hossen1@louisiana.eduXiali HeiUniversity of Louisiana at LafayetteLafayette, Louisiana, USAxiali.hei@louisiana.eduAbstractThe advent of instruct...
Code Issues Pull requests Discussions Adversarial Robustness Toolbox (ART) - Python Library for Machine Learning Security - Evasion, Poisoning, Extraction, Inference - Red and Blue Teams python machine-learning privacy ai attack extraction inference artificial-intelligence evasion red-team poisoning adver...
This is the repo for Adversarial Robustness via Runtime Masking and Cleansing, Yi-Hsuan Wu, Chia-Hung Yuan, and Shan-Hung Wu, In Proceedings of ICML 2020. Our code is implemented in TensorFlow 2.0 using all the best practices. We devise a new defense method, called runtime masking and cl...
To sum up, we have two options of pretrained models to use for transfer learning. We can either use standard models that have high accuracy but little robustness on the source task; or we can use adversarially robust models, which are worse in terms of ImageNet accuracy but are robust and...
Self-supervised Adversarial Robustness for the Low-label, High-data Regime Understanding Catastrophic Overfitting in Single-step Adversarial Training Adversarial Training Can Hurt Generalization Understanding and Mitigating the Tradeoff Between Robustness and Accuracy ...
Trusted-AI/adversarial-robustness-toolboxPublic NotificationsYou must be signed in to change notification settings Fork1.2k Star5k main BranchesTags Code Folders and files Name Last commit message Last commit date Latest commit beat-buesser Merge pull request#2571from Trusted-AI/dependabot/pip/ruff-...
Instead, we argue that one can estimate robustness accurately mostly without adaptive attacks but for this one has to introduce some restrictions on the considered models. However, we do welcome adaptive evaluations and we are always interested in showing the best known robust accuracy....
(Wildfire Adversarial Robustness Procedure), the first model-agnostic framework for evaluating the adversarial robustness of DNN-based wildfire detection models. WARP addresses limitations in smoke image diversity using global and local adversarial attack methods. The global attack method uses image-...
Double Visual Defense: Adversarial Pre-training and Instruction Tuning for Improving Vision-Language Model Robustness no code yet •16 Jan 2025 For example, the adversarial robustness ofΔCLIP surpasses that of the previous best models on ImageNet-1k by ~20%. ...