% Key papers for Vision-language model robustness (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{aaai2024_visual_7776,
  title = {{Visual Adversarial Examples Jailbreak Aligned Large Language Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/30150},
}

@inproceedings{cvpr2018_fooling_13128,
  title = {{Fooling Vision and Language Models Despite Localization and Attention Mechanism}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Xu_Fooling_Vision_and_CVPR_2018_paper.html},
}

@inproceedings{cvpr2024_on_24348,
  title = {{On the Robustness of Large Multimodal Models Against Image Adversarial Attacks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29761},
}

@inproceedings{cvpr2024_one_24353,
  title = {{One Prompt Word is Enough to Boost Adversarial Robustness for Pre-trained Vision-Language Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30782},
}

@inproceedings{cvpr2024_asam_22690,
  title = {{ASAM: Boosting Segment Anything Model with Adversarial Tuning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31630},
}

@inproceedings{cvpr2025_anyattack_25501,
  title = {{Anyattack: Towards Large-scale Self-supervised Adversarial Attacks on Vision-language Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35117},
}

@inproceedings{neurips2023_vlattack_69554,
  title = {{VLATTACK: Multimodal Adversarial Attacks on Vision-Language Tasks via Pre-trained Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70371},
}

@inproceedings{aaai2025_mmj_9861,
  title = {{MMJ-Bench: A Comprehensive Study on Jailbreak Attacks and Defenses for Vision Language Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34983},
}

@inproceedings{cvpr2024_language_23920,
  title = {{Language-Driven Anchors for Zero-Shot Adversarial Robustness}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29619},
}

@inproceedings{iclr2023_understanding_32519,
  title = {{Understanding Zero-shot Adversarial Robustness for Large-Scale Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2023},
  url = {https://iclr.cc/virtual/2023/poster/11946},
}

@inproceedings{cvpr2025_on_27136,
  title = {{On the Zero-shot Adversarial Robustness of Vision-Language Models: A Truly Zero-shot and Training-free Approach}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33759},
}

@inproceedings{cvpr2025_r_27344,
  title = {{R-TPT: Improving Adversarial Robustness of Vision-Language Models through Test-Time Prompt Tuning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33087},
}

@inproceedings{cvpr2025_stereo_27551,
  title = {{STEREO: A Two-Stage Framework for Adversarially Robust Concept Erasing from Text-to-Image Diffusion Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32792},
}

@inproceedings{cvpr2025_steering_27752,
  title = {{Steering Away from Harm: An Adaptive Approach to Defending Vision Language Model Against Jailbreaks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33840},
}

@inproceedings{neurips2024_few_73794,
  title = {{Few-Shot Adversarial Prompt Learning on Vision-Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93713},
}

@inproceedings{aaai2025_autonomous_8203,
  title = {{Autonomous LLM-Enhanced Adversarial Attack for Text-to-Motion}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32657},
}

@inproceedings{cvpr2025_tapt_27805,
  title = {{TAPT: Test-Time Adversarial Prompt Tuning for Robust Inference in Vision-Language Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32411},
}

@inproceedings{icml2024_image_43613,
  title = {{Image Hijacks: Adversarial Images can Control Generative Models at Runtime}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34839},
}

@inproceedings{aaai2025_robust_10577,
  title = {{Robust SAM: On the Adversarial Robustness of Vision Foundation Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32616},
}

@inproceedings{cvpr2025_scenetap_27592,
  title = {{SceneTAP: Scene-Coherent Typographic Adversarial Planner against Vision-Language Models in Real-World Environments}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34629},
}

@inproceedings{neurips2024_shadowcast_71564,
  title = {{Shadowcast: Stealthy Data Poisoning Attacks Against Vision-Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95705},
}

@inproceedings{cvpr2025_exploring_26195,
  title = {{Exploring Visual Vulnerabilities via Multi-Loss Adversarial Search for Jailbreaking Vision-Language Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/35162},
}

@inproceedings{cvpr2025_prompt2perturb_27317,
  title = {{Prompt2Perturb (P2P): Text-Guided Diffusion-Based Adversarial Attack on Breast Ultrasound Images}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33473},
}