% Key papers for Adversarial training refinements (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2018_improving_101292,
  title = {{Improving the Adversarial Robustness and Interpretability of Deep Neural Networks by Regularizing Their Input Gradients}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11504},
}

@inproceedings{iclr2020_improving_29856,
  title = {{Improving Adversarial Robustness Requires Revisiting Misclassified Examples}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=rklOg6EFwS},
}

@inproceedings{neurips2020_adversarial_59350,
  title = {{Adversarial Weight Perturbation Helps Robust Generalization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17064},
}

@inproceedings{cvpr2020_adversarial_15133,
  title = {{Adversarial Vertex Mixup: Toward Better Adversarially Robust Generalization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2019_a_57817,
  title = {{A Little Is Enough: Circumventing Defenses For Distributed Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13920},
}

@inproceedings{neurips2018_sparse_57637,
  title = {{Sparse DNNs with Improved Adversarial Robustness}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11050},
}

@inproceedings{iclr2019_the_28980,
  title = {{The Limitations of Adversarial Training and the Blind-Spot Attack}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/730},
}

@inproceedings{aaai2021_understanding_1582,
  title = {{Understanding Catastrophic Overfitting in Single-step Adversarial Training}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08119-understanding-catastrophic-overfitting-in-single-step-adversarial-training/},
}

@inproceedings{neurips2019_you_59210,
  title = {{You Only Propagate Once: Accelerating Adversarial Training via Maximal Principle}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13267},
}

@inproceedings{cvpr2023_boosting_20494,
  title = {{Boosting Accuracy and Robustness of Student Models via Adaptive Adversarial Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21151},
}

@inproceedings{aaai2022_consistency_1864,
  title = {{Consistency Regularization for Adversarial Robustness}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/08414-consistency-regularization-for-adversarial-robustness/},
}

@inproceedings{neurips2019_error_58223,
  title = {{Error Correcting Output Codes Improve Probability Estimation and Adversarial Robustness of Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2019},
  url = {https://nips.cc/virtual/2019/poster/13921},
}

@inproceedings{cvpr2023_cfa_20531,
  title = {{CFA: Class-Wise Calibrated Fair Adversarial Training}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21369},
}

@inproceedings{cvpr2023_randomized_21977,
  title = {{Randomized Adversarial Training via Taylor Expansion}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21847},
}

@inproceedings{neurips2020_understanding_61040,
  title = {{Understanding and Improving Fast Adversarial Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18567},
}

@inproceedings{neurips2020_adversarial_59341,
  title = {{Adversarial Distributional Training for Robust Deep Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/17781},
}

@inproceedings{neurips2021_exploring_62109,
  title = {{Exploring Architectural Ingredients of Adversarially Robust Deep Neural Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28697},
}

@inproceedings{neurips2022_make_64740,
  title = {{Make Some Noise: Reliable and Efficient Single-Step Adversarial Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/53035},
}

@inproceedings{neurips2021_towards_63038,
  title = {{Towards Efficient and Effective Adversarial Training}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/26270},
}

@inproceedings{neurips2020_guided_59979,
  title = {{Guided Adversarial Attack for Evaluating and Enhancing Adversarial Defenses}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18876},
}

@inproceedings{cvpr2024_revisiting_24650,
  title = {{Revisiting Adversarial Training Under Long-Tailed Distributions}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29795},
}

@inproceedings{cvpr2024_robust_24671,
  title = {{Robust Overfitting Does Matter: Test-Time Adversarial Purification With FGSM}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29332},
}

@inproceedings{aaai2024_adversarial_5147,
  title = {{Adversarial Initialization with Universal Adversarial Perturbation: A New Approach to Fast Adversarial Training}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30147},
}

@inproceedings{cvpr2024_soften_24851,
  title = {{Soften to Defend: Towards Adversarial Robustness via Self-Guided Label Refinement}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31746},
}

@inproceedings{cvpr2024_peeraid_24447,
  title = {{PeerAiD: Improving Adversarial Distillation from a Specialized Peer Tutor}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30248},
}

@inproceedings{aaai2024_perturbation_6949,
  title = {{Perturbation-Invariant Adversarial Training for Neural Ranking Models: Improving the Effectiveness-Robustness Trade-Off}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28730},
}

@inproceedings{iclr2024_adversarial_34621,
  title = {{Adversarial Training Should Be Cast as a Non-Zero-Sum Game}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18453},
}

@inproceedings{aaai2025_enhancing_8989,
  title = {{Enhancing Robustness in Incremental Learning with Adversarial Training}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32254},
}

@inproceedings{aaai2025_enhancing_8995,
  title = {{Enhancing the Adversarial Robustness via Manifold Projection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32024},
}

@inproceedings{iclr2024_efficient_34476,
  title = {{Efficient local linearity regularization to overcome catastrophic overfitting}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18598},
}

@inproceedings{icml2024_enhancing_44386,
  title = {{Enhancing Adversarial Robustness in SNNs with Sparse Gradients}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34066},
}

@inproceedings{neurips2024_exploring_72194,
  title = {{Exploring Adversarial Robustness of Deep State Space Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95147},
}

@inproceedings{neurips2024_improving_73602,
  title = {{Improving Adversarial Robust Fairness via Anti-Bias Soft Label Distillation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93884},
}

@inproceedings{iclr2025_democratic_80750,
  title = {{Democratic Training Against Universal Adversarial Perturbations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/31018},
}

@inproceedings{cvpr2025_stop_27758,
  title = {{Stop Walking in Circles! Bailing Out Early in Projected Gradient Descent}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35078},
}

@inproceedings{iclr2024_the_34239,
  title = {{The Effectiveness of Random Forgetting for Robust Generalization}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18836},
}

@inproceedings{iclr2024_doubly_34325,
  title = {{Doubly Robust Instance-Reweighted Adversarial Training}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18750},
}

@inproceedings{icml2024_on_43336,
  title = {{On the Duality Between Sharpness-Aware Minimization and Adversarial Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35116},
}

@inproceedings{icml2024_layer_45265,
  title = {{Layer-Aware Analysis of Catastrophic Overfitting: Revealing the Pseudo-Robust Shortcut Dependency}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33187},
}

@inproceedings{icml2025_identifying_46706,
  title = {{Identifying and Understanding Cross-Class Features in Adversarial Training}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45866},
}