{"total":51,"rows":[{"id":"2102.08452","title":"Globally-Robust Neural Networks","created":"2021-02-16","cited_by_count":108,"area":null},{"id":"2103.15670","title":"On the Adversarial Robustness of Vision Transformers","created":"2021-03-29","cited_by_count":106,"area":null},{"id":"2105.11417","title":"Skew Orthogonal Convolutions","created":"2021-05-24","cited_by_count":67,"area":null},{"id":"2104.04448","title":"Relating Adversarially Robust Generalization to Flat Minima","created":"2021-04-09","cited_by_count":57,"area":null},{"id":"2210.01787","title":"Rethinking Lipschitz Neural Networks and Certified Robustness: A Boolean Function Perspective","created":"2022-10-04","cited_by_count":51,"area":null},{"id":"2111.09277","title":"SmoothMix: Training Confidence-calibrated Smoothed Classifiers for Certified Robustness","created":"2021-11-17","cited_by_count":49,"area":null},{"id":"2108.04062","title":"Improved deterministic l2 robustness on CIFAR-10 and CIFAR-100","created":"2021-08-05","cited_by_count":47,"area":null},{"id":"2107.12045","title":"How to Certify Machine Learning Based Safety-critical Systems? A Systematic Literature Review","created":"2021-07-26","cited_by_count":39,"area":null},{"id":"2305.00241","title":"When Deep Learning Meets Polyhedral Theory: A Survey","created":"2023-04-29","cited_by_count":39,"area":null},{"id":"2110.03109","title":"Consistent Counterfactuals for Deep Models","created":"2021-10-06","cited_by_count":37,"area":null},{"id":"2302.03015","title":"Exploring and Exploiting Decision Boundary Dynamics for Adversarial Robustness","created":"2023-02-06","cited_by_count":36,"area":null},{"id":"2110.06850","title":"Boosting the Certified Robustness of L-infinity Distance Nets","created":"2021-10-13","cited_by_count":24,"area":null},{"id":"2103.11257","title":"Robust Models Are More Interpretable Because Attributions Look Normal","created":"2021-03-20","cited_by_count":21,"area":null},{"id":"2106.06685","title":"Adversarial Robustness via Fisher-Rao Regularization","created":"2021-06-12","cited_by_count":19,"area":null},{"id":"2110.12072","title":"How and When Adversarial Robustness Transfers in Knowledge Distillation?","created":"2021-10-22","cited_by_count":16,"area":"distill"},{"id":"2103.03438","title":"Towards Evaluating the Robustness of Deep Diagnostic Models by Adversarial Attack","created":"2021-03-05","cited_by_count":15,"area":null},{"id":"2107.00379","title":"On the Expected Complexity of Maxout Networks","created":"2021-07-01","cited_by_count":15,"area":null},{"id":"2111.08922","title":"Traversing the Local Polytopes of ReLU Neural Networks: A Unified Approach for Network Verification","created":"2021-11-17","cited_by_count":13,"area":null},{"id":"2301.12549","title":"Unlocking Deterministic Robustness Certification on ImageNet","created":"2023-01-29","cited_by_count":13,"area":null},{"id":"2307.08278","title":"Adversarial Attacks on Traffic Sign Recognition: A Survey","created":"2023-07-17","cited_by_count":13,"area":null},{"id":"2402.12572","title":"FairProof : Confidential and Certifiable Fairness for Neural Networks","created":"2024-02-19","cited_by_count":13,"area":null},{"id":"2307.02318","title":"Deep Contract Design via Discontinuous Networks","created":"2023-07-05","cited_by_count":11,"area":null},{"id":"2107.14742","title":"Connections between Numerical Algorithms for PDEs and Neural Networks","created":"2021-07-30","cited_by_count":10,"area":null},{"id":"2211.08453","title":"Improved techniques for deterministic l2 robustness","created":"2022-11-15","cited_by_count":9,"area":null},{"id":"2211.10752","title":"Towards Robust Dataset Learning","created":"2022-11-19","cited_by_count":9,"area":null},{"id":"2212.09000","title":"Confidence-aware Training of Smoothed Classifiers for Certified Robustness","created":"2022-12-18","cited_by_count":9,"area":null},{"id":"2402.04971","title":"Multi-Sender Persuasion: A Computational Perspective","created":"2024-02-07","cited_by_count":9,"area":null},{"id":"2412.18283","title":"On the Local Complexity of Linear Regions in Deep ReLU Networks","created":"2024-12-24","cited_by_count":9,"area":null},{"id":"2103.13598","title":"Recent Advances in Large Margin Learning","created":"2021-03-25","cited_by_count":7,"area":null},{"id":"2108.11939","title":"Understanding and Accelerating Neural Architecture Search with Training-Free and Theory-Grounded Metrics","created":"2021-08-26","cited_by_count":7,"area":null},{"id":"2106.06624","title":"Relaxing Local Robustness","created":"2021-06-11","cited_by_count":6,"area":null},{"id":"2211.12713","title":"Reliable Robustness Evaluation via Automatically Constructed Attack Ensembles","created":"2022-11-23","cited_by_count":6,"area":null},{"id":"2202.01341","title":"Robust Binary Models by Pruning Randomly-initialized Networks","created":"2022-02-03","cited_by_count":5,"area":null},{"id":"2305.09145","title":"Deep ReLU Networks Have Surprisingly Simple Polytopes","created":"2023-05-16","cited_by_count":5,"area":null},{"id":"2412.14714","title":"Holistic Adversarially Robust Pruning","created":"2024-12-19","cited_by_count":5,"area":null},{"id":"2112.05235","title":"The Fundamental Limits of Interval Arithmetic for Neural Networks","created":"2021-12-09","cited_by_count":4,"area":null},{"id":"2301.08842","title":"Limitations of Piecewise Linearity for Efficient Robustness Certification","created":"2023-01-21","cited_by_count":4,"area":null},{"id":"2304.10446","title":"Certified Adversarial Robustness Within Multiple Perturbation Bounds","created":"2023-04-20","cited_by_count":4,"area":null},{"id":"2105.07776","title":"DISCO Verification: Division of Input Space into COnvex polytopes for neural network verification","created":"2021-05-17","cited_by_count":1,"area":null},{"id":"2204.10839","title":"How Sampling Impacts the Robustness of Stochastic Neural Networks","created":"2022-04-22","cited_by_count":1,"area":null},{"id":"2206.01705","title":"Gradient Obfuscation Checklist Test Gives a False Sense of Security","created":"2022-06-03","cited_by_count":1,"area":null},{"id":"2307.00721","title":"Neural Polytopes","created":"2023-07-03","cited_by_count":1,"area":null},{"id":"2402.00576","title":"Tropical Decision Boundaries for Neural Networks Are Robust Against Adversarial Attacks","created":"2024-02-01","cited_by_count":1,"area":null},{"id":"2504.08414","title":"Adversarial Examples in Environment Perception for Automated Driving (Review)","created":"2025-04-11","cited_by_count":1,"area":null},{"id":"2602.02626","title":"Learning Better Certified Models from Empirically-Robust Teachers","created":"2026-02-02","cited_by_count":1,"area":"distill"},{"id":"2112.15111","title":"Improving the Behaviour of Vision Transformers with Token-consistent Stochastic Layers","created":"2021-12-30","cited_by_count":0,"area":null},{"id":"2506.00661","title":"Elytra: A Flexible Framework for Securing Large Vision Systems","created":"2025-05-31","cited_by_count":0,"area":null},{"id":"2512.15123","title":"TrajSyn: Privacy-Preserving Dataset Distillation from Federated Model Trajectories for Server-Side Adversarial Training","created":"2025-12-17","cited_by_count":0,"area":null},{"id":"2602.18674","title":"Theoretical Lower Bounds on the Robustness of Deep ReLU Networks","created":"2026-02-21","cited_by_count":0,"area":null},{"id":"2604.24393","title":"Complexity of Linear Regions in Self-supervised Deep ReLU Networks","created":"2026-04-27","cited_by_count":0,"area":"distill"},{"id":"2609.32695","title":"Affine Geometry of Gaussian ReLU Networks via Conditional Kac-Rice Formulas","created":"2026-09-26","cited_by_count":0,"area":null}],"next_cursor":null}