← Optimization & Theory
Deep Learning › Optimization & Theory ›

Robustness

38 directly classified papers

Papers per year

Papers

CAPTURE: Context-Aware Prompt Injection Testing and Robustness Enhancement ACL 2025
Improving Generalization of Universal Adversarial Perturbation via Dynamic Maximin Optimization AAAI 2025
Boosting Adversarial Transferability by Block Shuffle and Rotation CVPR 2024
1-Lipschitz Layers Compared: Memory Speed and Certifiable Robustness CVPR 2024
SURE: SUrvey REcipes for building reliable and robust deep networks CVPR 2024
Improving Robustness of 3D Point Cloud Recognition from a Fourier Perspective NIPS 2024
Adversarial Initialization with Universal Adversarial Perturbation: A New Approach to Fast Adversarial Training AAAI 2024
ArtPrompt: ASCII Art-based Jailbreak Attacks against Aligned LLMs ACL 2024
The Best Defense Is a Good Offense: Adversarial Augmentation Against Adversarial Attacks CVPR 2023
Language Model Pre-training on True Negatives AAAI 2023
CAP: Robust Point Cloud Classification via Semantic and Structural Modeling CVPR 2023
Dynamic Generative Targeted Attacks With Pattern Injection CVPR 2023
On Robustness of Finetuned Transformer-based NLP Models EMNLP 2023
Optimal Transport Model Distributional Robustness NIPS 2023
Wasserstein distributional robustness of neural networks NIPS 2023
Certified Robustness via Dynamic Margin Maximization and Improved Lipschitz Regularization NIPS 2023
3DeformRS: Certifying Spatial Deformations on Point Clouds CVPR 2022
On Length Divergence Bias in Textual Matching Models ACL 2022
Improving Out-of-Distribution Generalization by Adversarial Training with Structured Priors NIPS 2022
Your Out-of-Distribution Detection Method is Not Robust! NIPS 2022
Robust Models are less Over-Confident NIPS 2022
Adversarial Attack for Asynchronous Event-Based Data AAAI 2022
Bounded Adversarial Attack on Deep Content Features CVPR 2022
Combating Adversaries with Anti-adversaries AAAI 2022
MEMO: Test Time Robustness via Adaptation and Augmentation NIPS 2022