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https://deepai.org/publication/adversarial-robustness-with-non-uniform-perturbations Adversarial Robustness with Non-uniform Perturbations | DeepAI Feb 24, 2021 - 02/24/21 - Robustness of machine learning models is critical for security related applications, where real-world adversaries are uniquely foc... adversarial robustness non uniform perturbations deepai https://openreview.net/forum?id=leFBpvYaPx Adversarial Robustness of Graph Transformers | OpenReview Existing studies have shown that Message-Passing Graph Neural Networks (MPNNs) are highly susceptible to adversarial attacks. In contrast, despite the... adversarial robustness graph transformers openreview https://openreview.net/forum?id=U6o1lPe_wdB&referrer=%5Bthe%20profile%20of%20Junhao%20Dong%5D(%2Fprofile%3Fid%3D~Junhao_Dong1) Toward Intrinsic Adversarial Robustness Through Probabilistic Training | OpenReview Modern deep neural networks have made numerous breakthroughs in real-world applications, yet they remain vulnerable to some imperceptible adversarial... adversarial robustness toward intrinsic probabilistic training https://openreview.net/forum?id=5BHnwahrv78&referrer=%5Bthe%20profile%20of%20Alessandro%20De%20Palma%5D(%2Fprofile%3Fid%3D~Alessandro_De_Palma1) IBP Regularization for Verified Adversarial Robustness via Branch-and-Bound | OpenReview Recent works have tried to increase the verifiability of adversarially trained networks by running the attacks over domains larger than the original... branch and bound adversarial robustness ibp regularization verified https://openreview.net/forum?id=rklOg6EFwS Improving Adversarial Robustness Requires Revisiting Misclassified Examples | OpenReview By differentiating misclassified and correctly classified data, we propose a new misclassification aware defense that improves the state-of-the-art adversarial... adversarial robustness improving requires revisiting misclassified https://deepai.org/publication/how-and-when-adversarial-robustness-transfers-in-knowledge-distillation How and When Adversarial Robustness Transfers in Knowledge Distillation? | DeepAI Oct 22, 2021 - 10/22/21 - Knowledge distillation (KD) has been widely used in teacher-student training, with applications to model compression in resource-c... adversarial robustness transfers in knowledge distillation deepai https://openreview.net/forum?id=mLe63bAYc7 Provable Adversarial Robustness for Group Equivariant Tasks: Graphs, Point Clouds, Molecules, and... A machine learning model is traditionally considered robust if its prediction remains (almost) constant under input perturbations with small norm. However,... adversarial robustness for group https://www.frontiersin.org/journals/artificial-intelligence/articles/10.3389/frai.2021.752831/full Frontiers | Improving Adversarial Robustness via Attention and Adversarial Logit Pairing Though deep neural networks have achieved the state of the art performance in visual classification, recent studies have shown that they are all vulnerable t... adversarial robustness frontiers improving via attention https://jmlr.org/papers/v23/21-0382.html Adversarial Robustness Guarantees for Gaussian Processes adversarial robustness guarantees gaussian processes https://deepai.org/publication/adversarial-robustness-for-code Adversarial Robustness for Code | DeepAI Feb 11, 2020 - 02/11/20 - We propose a novel technique which addresses the challenge of learning accurate and robust models of code in a principled way. Our... adversarial robustness code deepai https://openreview.net/forum?id=MN4nt01TeO Adaptive Randomized Smoothing: Certified Adversarial Robustness for Multi-Step Defences | OpenReview We propose Adaptive Randomized Smoothing (ARS) to certify the predictions of our test-time adaptive models against adversarial examples. ARS extends the... adversarial robustness multi step adaptive randomized smoothing https://deepai.org/publication/on-the-adversarial-robustness-of-visual-transformers On the Adversarial Robustness of Visual Transformers | DeepAI Mar 29, 2021 - 03/29/21 - Following the success in advancing natural language processing and understanding, transformers are expected to bring revolutionary... on the adversarial robustness visual transformers deepai https://openreview.net/forum?id=tqi_45ApQzF Shift Invariance Can Reduce Adversarial Robustness | OpenReview We provide theoretical and empirical evidence that the property of shift invariance in convolutional neural networks can decrease adversarial robustness. shift invariance can reduce adversarial robustness openreview https://openreview.net/forum?id=4xK0vjxTWL Adversarial Robustness of Graph Transformers | OpenReview Existing studies have shown that Message-Passing Graph Neural Networks (MPNNs) are highly susceptible to adversarial attacks. In contrast, despite the... adversarial robustness graph transformers openreview https://aclanthology.org/2024.findings-acl.596/ SpeechGuard: Exploring the Adversarial Robustness of Multi-modal Large Language Models - ACL... Raghuveer Peri, Sai Muralidhar Jayanthi, Srikanth Ronanki, Anshu Bhatia, Karel Mundnich, Saket Dingliwal, Nilaksh Das, Zejiang Hou, Goeric Huybrechts, Srikanth... large language models adversarial robustness https://openreview.net/forum?id=KvPwXVcslY Spatial-frequency channels, shape bias, and adversarial robustness | OpenReview What spatial frequency information do humans and neural networks use to recognize objects? In neuroscience, critical band masking is an established tool that... spatial frequency adversarial robustness channels shape bias https://openreview.net/forum?id=YauQYh2k1g&referrer=%5Bthe%20profile%20of%20Daniel%20Fried%5D(%2Fprofile%3Fid%3D~Daniel_Fried1) Dissecting Adversarial Robustness of Multimodal LM Agents | OpenReview As language models (LMs) are used to build autonomous agents in real environments, ensuring their adversarial robustness becomes a critical challenge. Unlike... adversarial robustness dissecting multimodal lm agents https://openreview.net/forum?id=I1W3fGOC36&referrer=%5Bthe%20profile%20of%20Omer%20Hofman%5D(%2Fprofile%3Fid%3D~Omer_Hofman1) KDAT: Inherent Adversarial Robustness via Knowledge Distillation with Adversarial Tuning for Object... Adversarial patches pose a significant threat to computer vision models' integrity, decreasing the accuracy of various tasks, including object detection (OD).... adversarial robustness knowledge distillation kdat inherent via https://www.mathworks.com/help/deeplearning/ref/verifynetworkrobustness.html verifyNetworkRobustness - Verify adversarial robustness of MATLAB, ONNX, and PyTorch networks -... This MATLAB function verifies whether the network net is adversarially robust with respect to the class label when the input is between XLower and XUpper. adversarial robustness verify matlab onnx pytorch https://deepai.org/publication/an-adaptive-view-of-adversarial-robustness-from-test-time-smoothing-defense An Adaptive View of Adversarial Robustness from Test-time Smoothing Defense | DeepAI Nov 26, 2019 - 11/26/19 - The safety and robustness of learning-based decision-making systems are under threats from adversarial examples, as imperceptible ... adversarial robustness https://openreview.net/forum?id=NO_cSsVghGb Neural Architecture Dilation for Adversarial Robustness | OpenReview With the tremendous advances in the architecture and scale of convolutional neural networks (CNNs) over the past few decades, they can easily reach or even... adversarial robustness neural architecture dilation openreview https://openreview.net/forum?id=HQtTg1try7 Adversarial Robustness Limits via Scaling-Law and Human-Alignment Studies | OpenReview This paper revisits the simple, long-studied, yet still unsolved problem of making image classifiers robust to imperceptible perturbations. Taking CIFAR10 as... adversarial robustness scaling law limits via https://openreview.net/forum?id=LjVIGva5Ct Dissecting Adversarial Robustness of Multimodal LM Agents | OpenReview As language models (LMs) are used to build autonomous agents in real environments, ensuring their adversarial robustness becomes a critical challenge. Unlike... adversarial robustness dissecting multimodal lm agents https://www.kth.se/eecs/kalender/on-the-adversarial-robustness-of-graph-neural-networks-1.1466748?date=2026-04-23&orgdate=2026-04-22&length=1&orglength=0 On the Adversarial Robustness of Graph Neural Networks | KTH graph neural networks on the adversarial robustness kth https://openreview.net/forum?id=5bNYf0CqxY Certified Adversarial Robustness for Rate Encoded Spiking Neural Networks | OpenReview The spiking neural networks are inspired by the biological neurons that employ binary spikes to propagate information in the neural network. It has garnered... spiking neural networks adversarial robustness certified rate encoded https://openreview.net/forum?id=iy4xRjfdid Scoring Black-Box Models for Adversarial Robustness | OpenReview Deep neural networks are susceptible to adversarial inputs and various methods have been proposed to defend these models against adversarial attacks under... black box models adversarial robustness scoring openreview https://arxiv.org/abs/2405.00392 [2405.00392] Certified Adversarial Robustness of Machine Learning-based Malware Detectors via... Abstract page for arXiv paper 2405.00392: Certified Adversarial Robustness of Machine Learning-based Malware Detectors via (De)Randomized Smoothing adversarial robustness https://openreview.net/forum?id=o81ZyBCojoA On Fast Adversarial Robustness Adaptation in Model-Agnostic Meta-Learning | OpenReview Model-agnostic meta-learning (MAML) has emerged as one of the most successful meta-learning techniques in few-shot learning. It enables us to learn a... adversarial robustness meta learning fast adaptation https://openreview.net/forum?id=snLBop22lS&referrer=%5Bthe%20profile%20of%20Zhiyuan%20Ma%5D(%2Fprofile%3Fid%3D~Zhiyuan_Ma1) Exploring Adversarial Robustness of Deep State Space Models | OpenReview Deep State Space Models (SSMs) have proven effective in numerous task scenarios but face significant security challenges due to Adversarial Perturbations (APs)... state space models adversarial robustness exploring deep openreview https://adversarial-robustness-toolbox.org/ Adversarial Robustness Toolbox adversarial robustness toolbox https://adversarial-ml-tutorial.org/ Adversarial Robustness - Theory and Practice This web page contains materials to accompany the NeurIPS 2018 tutorial, "Adversarial Robustness: Theory and Practice", by Zico Kolter and Aleksander Madry.... adversarial robustness theory practice https://openreview.net/forum?id=FObkvLwNSo Projected Randomized Smoothing for Certified Adversarial Robustness | OpenReview Randomized smoothing is the current state-of-the-art method for producing provably robust classifiers. While randomized smoothing typically yields robust... adversarial robustness projected randomized smoothing certified https://easychair.org/publications/preprint/9r2v Adversarial Robustness in Optimized LLMs: Defending Against Attacks adversarial robustness optimized llms defending attacks https://openreview.net/forum?id=EtGd7pF237i An Adversarial Robustness Perspective on the Topology of Neural Networks | OpenReview In this paper, we investigate the impact of NNs topology on adversarial robustness. Specifically, we study the graph produced when an input traverses all the... adversarial robustness on the neural networks perspective https://openreview.net/forum?id=XNFo3dQiCJ Generalizability of Adversarial Robustness Under Distribution Shifts | OpenReview Recent progress in empirical and certified robustness promises to deliver reliable and deployable Deep Neural Networks (DNNs). Despite that success, most... adversarial robustness distribution shifts generalizability openreview https://arxiv.org/abs/2602.06395v1 [2602.06395v1] Empirical Analysis of Adversarial Robustness and Explainability Drift in... Abstract page for arXiv paper 2602.06395v1: Empirical Analysis of Adversarial Robustness and Explainability Drift in Cybersecurity Classifiers empirical analysis adversarial robustness https://www.a-star.edu.sg/cfar/events/improving-and-evaluating-adversarial-robustness Improving and Evaluating Adversarial Robustness improving evaluating adversarial robustness https://arxiv.org/abs/2007.07209 [2007.07209] Fragility and Robustness in Mean-Payoff Adversarial Stackelberg Games Abstract page for arXiv paper 2007.07209: Fragility and Robustness in Mean-Payoff Adversarial Stackelberg Games 2007 fragility robustness https://deepai.org/publication/do-gradient-based-explanations-tell-anything-about-adversarial-robustness-to-android-malware Do Gradient-based Explanations Tell Anything About Adversarial Robustness to Android Malware? |... May 4, 2020 - 05/04/20 - Machine-learning algorithms trained on features extracted from static code analysis can successfully detect Android malware. Howev... https://openreview.net/forum?id=pl2WX3riyiq How Should Pre-Trained Language Models Be Fine-Tuned Towards Adversarial Robustness? | OpenReview The fine-tuning of pre-trained language models has a great success in many NLP fields. Yet, it is strikingly vulnerable to adversarial examples, e.g., word... https://openreview.net/forum?id=HJxdTxHYvB BREAKING CERTIFIED DEFENSES: SEMANTIC ADVERSARIAL EXAMPLES WITH SPOOFED ROBUSTNESS CERTIFICATES |... Defenses against adversarial attacks can be classified into certified and non-certified. Certifiable defenses make networks robust within a certain... adversarial examples breaking certified defenses semantic https://www.digitalocean.com/community/tutorials/enhancing-nlp-models-against-adversarial-attacks Enhancing NLP Models for Robustness Against Adversarial Attacks: Techniques and Applications |... Learn about a variety of techniques used to keep deep learning NLP models secure. nlp models adversarial attacks enhancing robustness https://openreview.net/forum?id=BkeWw6VFwr Certified Robustness for Top-k Predictions against Adversarial Perturbations via Randomized... We study the certified robustness for top-k predictions via randomized smoothing under Gaussian noise and derive a tight robustness bound in L_2 norm. certified robustness top k https://openreview.net/forum?id=vJZ7dPIjip3 Generalization of Neural Combinatorial Solvers Through the Lens of Adversarial Robustness |... End-to-end (geometric) deep learning has seen first successes in approximating the solution of combinatorial optimization problems. However, generating data in... through the lens generalization neural combinatorial solvers https://www.easychair.org/publications/preprint/W6Hh Towards Robustness of Convolutional Neural Network against Adversarial Examples convolutional neural network towards robustness adversarial examples https://openreview.net/forum?id=AN0LfgNH40&referrer=%5Bthe%20profile%20of%20Dung%20D.%20Le%5D(%2Fprofile%3Fid%3D~Dung_D._Le2) A Curious Case of Searching for the Correlation between Training Data and Adversarial Robustness of... Existing works have shown that fine-tuned textual transformer models achieve state-of-the-art prediction performances but are also vulnerable to adversarial... https://arxiv.org/abs/2404.13631 [2404.13631] Fermi-Bose Machine achieves both generalization and adversarial robustness Abstract page for arXiv paper 2404.13631: Fermi-Bose Machine achieves both generalization and adversarial robustness 2404 fermi bose machine https://openreview.net/forum?id=E3gF8L-mmS3&referrer=%5Bthe%20profile%20of%20Hwee%20Kuan%20Lee%5D(%2Fprofile%3Fid%3D~Hwee_Kuan_Lee1) Use of small auxiliary networks and scarce data to improve the adversarial robustness of deep... Deep Learning models for image classification are known to be vulnerable to adversarial examples. Adversarial training is one of the most effective ways to... https://deepai.org/publication/twins-a-fine-tuning-framework-for-improved-transferability-of-adversarial-robustness-and-generalization TWINS: A Fine-Tuning Framework for Improved Transferability of Adversarial Robustness and... Mar 20, 2023 - 03/20/23 - Recent years have seen the ever-increasing importance of pre-trained models and their downstream training in deep learning researc... fine tuning https://openreview.net/forum?id=ZUiWjEouSf RT2I-Bench: Evaluating Robustness of Text-to-Image Systems Against Adversarial Attacks | OpenReview Text-to-Image (T2I) systems have demonstrated impressive abilities in the generation of images from text descriptions. However, these systems remain... text to image https://deepai.org/publication/ensemble-in-one-learning-ensemble-within-random-gated-networks-for-enhanced-adversarial-robustness Ensemble-in-One: Learning Ensemble within Random Gated Networks for Enhanced Adversarial Robustness... Mar 27, 2021 - 03/27/21 - Adversarial attacks have rendered high security risks on modern deep learning systems. Adversarial training can significantly enha... in one https://deepai.org/publication/pointca-evaluating-the-robustness-of-3d-point-cloud-completion-models-against-adversarial-examples PointCA: Evaluating the Robustness of 3D Point Cloud Completion Models Against Adversarial Examples... Nov 22, 2022 - 11/22/22 - Point cloud completion, as the upstream procedure of 3D recognition and segmentation, has become an essential part of many tasks s... https://jmlr.org/papers/v26/22-1428.html Regularizing Hard Examples Improves Adversarial Robustness hard examples improves adversarial robustness https://arxiv.org/abs/1902.00577 [1902.00577] Robustness of Generalized Learning Vector Quantization Models against Adversarial... Abstract page for arXiv paper 1902.00577: Robustness of Generalized Learning Vector Quantization Models against Adversarial Attacks learning vector quantization 1902 robustness generalized https://arxiv.org/abs/2407.15549 [2407.15549] Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs Abstract page for arXiv paper 2407.15549: Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs https://arxiv.org/abs/2401.10657 [2401.10657] FIMBA: Evaluating the Robustness of AI in Genomics via Feature Importance Adversarial... Abstract page for arXiv paper 2401.10657: FIMBA: Evaluating the Robustness of AI in Genomics via Feature Importance Adversarial Attacks https://arxiv.org/abs/2408.08374 [2408.08374] Evaluating Text Classification Robustness to Part-of-Speech Adversarial Examples Abstract page for arXiv paper 2408.08374: Evaluating Text Classification Robustness to Part-of-Speech Adversarial Examples part of speech text classification https://openreview.net/forum?id=g4NNK4RH715 Certified robustness against adversarial patch attacks via randomized cropping | OpenReview This paper proposes a new defense against patch attack which decomposes an image into a random set of crops, each of which is processed by a classifier, and... adversarial patch certified robustness attacks via https://openreview.net/forum?id=6LxMeRlkWl Latent Adversarial Training Improves Robustness to Persistent Harmful Behaviors in LLMs | OpenReview Large language models (LLMs) can often be made to behave in undesirable ways that they are explicitly fine-tuned not to. For example, the LLM red-teaming... adversarial training https://www.analyticsvidhya.com/blog/2023/02/exploring-the-use-of-adversarial-learning-in-improving-model-robustness/ Adversarial Learning: Improving Model Robustness Jun 22, 2023 - This article explains the concept of adversarial learning and how it can be used to improve the model robustness for Deep learning projects. adversarial learning improving model robustness https://research.google/pubs/on-the-robustness-of-image-based-malware-detection-against-adversarial-attacks/ On the Robustness of Image-based Malware Detection against Adversarial Attacks on the image based malware detection robustness https://easychair.org/publications/preprint/W6Hh Towards Robustness of Convolutional Neural Network against Adversarial Examples convolutional neural network towards robustness adversarial examples https://openreview.net/forum?id=WVX0NNVBBkV&referrer=%5Bthe%20profile%20of%20Chong%20Xiang%5D(%2Fprofile%3Fid%3D~Chong_Xiang1) Robust Learning Meets Generative Models: Can Proxy Distributions Improve Adversarial Robustness? |... While additional training data improves the robustness of deep neural networks against adversarial examples, it presents the challenge of curating a large... generative models robust learning meets https://github.com/MadryLab/mnist_challenge GitHub - MadryLab/mnist_challenge: A challenge to explore adversarial robustness of neural networks... A challenge to explore adversarial robustness of neural networks on MNIST. - MadryLab/mnist_challenge challenge a to explore https://huggingface.co/papers/2411.19508 Paper page - On the Adversarial Robustness of Instruction-Tuned Large Language Models for Code Join the discussion on this paper page https://openreview.net/forum?id=XgK05fssnx AlignFix: Fixing Adversarial Perturbations by Agreement Checking for Adversarial Robustness against... Motivated by the vulnerability of feed-forward visual pathways to adversarial-like inputs and the overall robustness of biological perception, commonly... fixing adversarial perturbations agreement checking https://deepai.org/publication/critical-checkpoints-for-evaluating-defence-models-against-adversarial-attack-and-robustness Critical Checkpoints for Evaluating Defence Models Against Adversarial Attack and Robustness |... Feb 18, 2022 - 02/18/22 - From past couple of years there is a cycle of researchers proposing a defence model for adversaries in machine learning which is a... adversarial attack critical checkpoints evaluating defence https://openreview.net/forum?id=Hkg7rbcp67 Investigating Robustness and Interpretability of Link Prediction via Adversarial Modifications |... Representing entities and relations in an embedding space is a well-studied approach for machine learning on relational data. Existing approaches, however,... link prediction investigating robustness interpretability via