% Key papers for Attacks and defenses in sequential settings (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2020_tbt_16316,
  title = {{TBT: Targeted Neural Network Attack With Bit Trojan}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{aaai2019_one_100216,
  title = {{One-Class Adversarial Nets for Fraud Detection}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2019},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/3924},
}

@inproceedings{cvpr2020_defending_15391,
  title = {{Defending and Harnessing the Bit-Flip Based Adversarial Weight Attack}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{icml2021_learning_39546,
  title = {{Learning from History for Byzantine Robust Optimization}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2021},
  url = {https://icml.cc/virtual/2021/poster/9987},
}

@inproceedings{aaai2020_spatiotemporally_102025,
  title = {{Spatiotemporally Constrained Action Space Attacks on Deep Reinforcement Learning Agents}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5887},
}

@inproceedings{cvpr2022_fairness_18829,
  title = {{Fairness-Aware Adversarial Perturbation Towards Bias Mitigation for Deployed Deep Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2021_curse_346,
  title = {{Curse or Redemption? How Data Heterogeneity Affects the Robustness of Federated Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/10807-curse-or-redemption-how-data-heterogeneity-affects-the-robustness-of-federated-learning/},
}

@inproceedings{cvpr2019_defending_14061,
  title = {{Defending Against Adversarial Attacks by Randomized Diversification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2020_ilfo_15667,
  title = {{ILFO: Adversarial Attack on Adaptive Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2020},
}

@inproceedings{neurips2018_online_57477,
  title = {{Online Robust Policy Learning in the Presence of Unknown Adversaries}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11941},
}

@inproceedings{iclr2021_a_30074,
  title = {{A Panda? No, It's a Sloth: Slowdown Attacks on Adaptive Multi-Exit Neural Network Inference}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/3283},
}

@inproceedings{aaai2020_adversary_103684,
  title = {{Adversary for Social Good: Protecting Familial Privacy through Joint Adversarial Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6791},
}

@inproceedings{aaai2021_learning_913,
  title = {{Learning to Attack Real-World Models for Person Re-identification via Virtual-Guided Meta-Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/03128-learning-to-attack-real-world-models-for-person-re-identification-via-virtual-guided-meta-learning/},
}

@inproceedings{neurips2022_practical_65854,
  title = {{Practical Adversarial Attacks on Spatiotemporal Traffic Forecasting Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55401},
}

@inproceedings{aaai2016_a_104768,
  title = {{A Security Game Combining Patrolling and Alarm-Triggered Responses Under Spatial and Detection Uncertainties}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2016},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/10022},
}

@inproceedings{iclr2020_toward_29721,
  title = {{Toward Evaluating Robustness of Deep Reinforcement Learning with Continuous Control}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2020},
  url = {https://openreview.net/forum?id=SylL0krYPS},
}

@inproceedings{neurips2018_unorganized_57743,
  title = {{Unorganized Malicious Attacks Detection}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2018},
  url = {https://nips.cc/virtual/2018/poster/11672},
}

@inproceedings{aaai2020_actor_100276,
  title = {{Actor Critic Deep Reinforcement Learning for Neural Malware Control}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5449},
}

@inproceedings{neurips2022_revisiting_65541,
  title = {{Revisiting Injective Attacks on Recommender Systems}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54261},
}

@inproceedings{cvpr2022_improving_19063,
  title = {{Improving Robustness Against Stealthy Weight Bit-Flip Attacks by Output Code Matching}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2024_optimal_6863,
  title = {{Optimal Attack and Defense for Reinforcement Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29346},
}

@inproceedings{cvpr2024_what_25279,
  title = {{What Sketch Explainability Really Means for Downstream Tasks?}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29465},
}

@inproceedings{aaai2024_generating_6125,
  title = {{Generating Universal Adversarial Perturbations for Quantum Classifiers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28963},
}

@inproceedings{aaai2025_rat_10433,
  title = {{RAT: Adversarial Attacks on Deep Reinforcement Agents for Targeted Behaviors}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33696},
}

@inproceedings{aaai2024_detection_5677,
  title = {{Detection and Defense of Unlearnable Examples}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29667},
}

@inproceedings{aaai2024_game_6101,
  title = {{Game-Theoretic Unlearnable Example Generator}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30130},
}

@inproceedings{cvpr2025_your_28170,
  title = {{Your Scale Factors are My Weapon: Targeted Bit-Flip Attacks on Vision Transformers via Scale Factor Manipulation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33058},
}

@inproceedings{cvpr2024_medbn_24129,
  title = {{MedBN: Robust Test-Time Adaptation against Malicious Test Samples}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30365},
}

@inproceedings{neurips2024_transferable_74554,
  title = {{Transferable Adversarial Attacks on SAM and Its Downstream Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93030},
}

@inproceedings{aaai2025_crossfire_8572,
  title = {{Crossfire: An Elastic Defense Framework for Graph Neural Networks Under Bit Flip Attacks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33979},
}

@inproceedings{aaai2024_stealthy_7411,
  title = {{Stealthy Adversarial Attacks on Stochastic Multi-Armed Bandits}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/29506},
}

@inproceedings{icml2025_expproof_48012,
  title = {{ExpProof : Operationalizing Explanations for Confidential Models with ZKPs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44593},
}

@inproceedings{neurips2024_efficient_71289,
  title = {{Efficient Availability Attacks against Supervised and Contrastive Learning Simultaneously}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95958},
}

@inproceedings{aaai2026_rsa_108502,
  title = {{RSA-CR: Resisting Shilling Attacks in Citation Recommendation via Dumbbell Inductive Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40854},
}

@inproceedings{aaai2025_quickest_10427,
  title = {{Quickest Detection of Adversarial Attacks Against Correlated Equilibria}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33527},
}

@inproceedings{aaai2025_stop_10844,
  title = {{Stop Diverse OOD Attacks: Knowledge Ensemble for Reliable Defense}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34251},
}

@inproceedings{iclr2024_illusory_33993,
  title = {{Illusory Attacks: Information-theoretic detectability matters in adversarial attacks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19082},
}

@inproceedings{iclr2024_respect_34541,
  title = {{Respect the model: Fine-grained and Robust Explanation with Sharing Ratio Decomposition}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18533},
}

@inproceedings{iclr2024_rethinking_35288,
  title = {{Rethinking Adversarial Policies: A Generalized Attack Formulation and Provable Defense in RL}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17785},
}

@inproceedings{icml2024_signsgd_45814,
  title = {{SignSGD with Federated Defense: Harnessing Adversarial Attacks through Gradient Sign Decoding}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/32638},
}