% Key papers for Continual test-time adaptation (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2022_continual_18516,
  title = {{Continual Test-Time Domain Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2023_decorate_3418,
  title = {{Decorate the Newcomers: Visual Domain Prompt for Continual Test Time Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/25922},
}

@inproceedings{cvpr2023_ecotta_20881,
  title = {{EcoTTA: Memory-Efficient Continual Test-Time Adaptation via Self-Distilled Regularization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22171},
}

@inproceedings{icml2022_efficient_40498,
  title = {{Efficient Test-Time Model Adaptation without Forgetting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/18323},
}

@inproceedings{cvpr2024_each_23317,
  title = {{Each Test Image Deserves A Specific Prompt: Continual Test-Time Adaptation for 2D Medical Image Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29977},
}

@inproceedings{cvpr2024_continual_23034,
  title = {{Continual-MAE: Adaptive Distribution Masked Autoencoders for Continual Test-Time Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31388},
}

@inproceedings{cvpr2025_maintaining_26904,
  title = {{Maintaining Consistent Inter-Class Topology in Continual Test-Time Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34733},
}

@inproceedings{cvpr2024_a_22669,
  title = {{A Versatile Framework for Continual Test-Time Domain Adaptation: Balancing Discriminability and Generalizability}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31036},
}

@inproceedings{neurips2024_pcotta_70635,
  title = {{PCoTTA: Continual Test-Time Adaptation for Multi-Task Point Cloud Understanding}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96487},
}

@inproceedings{neurips2023_rdumb_68361,
  title = {{RDumb: A simple approach that questions our progress in continual test-time adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71448},
}

@inproceedings{neurips2025_reservoirtta_77793,
  title = {{ReservoirTTA: Prolonged Test-time Adaptation for Evolving and Recurring Domains}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=XewZ4rJYKZ},
}

@inproceedings{icml2024_becotta_43498,
  title = {{BECoTTA: Input-dependent Online Blending of Experts for Continual Test-time Adaptation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/34954},
}

@inproceedings{neurips2024_contrast_73780,
  title = {{CONTRAST: Continual Multi-source Adaptation to Dynamic Distributions}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93726},
}

@inproceedings{aaai2026_shared_107750,
  title = {{Shared \& Domain Self-Adaptive Experts with Frequency-Aware Discrimination for Continual Test-Time Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40102},
}

@inproceedings{icml2025_dpcore_46376,
  title = {{DPCore: Dynamic Prompt Coreset for Continual Test-Time Adaptation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/46187},
}

@inproceedings{icml2025_ranked_48409,
  title = {{Ranked Entropy Minimization for Continual Test-Time Adaptation}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44208},
}

@inproceedings{neurips2025_class_76064,
  title = {{Class-aware Domain Knowledge Fusion and Fission for Continual Test-Time Adaptation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=F74FXkicGK},
}

@inproceedings{iclr2024_continual_33871,
  title = {{Continual Momentum Filtering on Parameter Space for Online Test-time Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19204},
}

@inproceedings{iclr2024_vida_35416,
  title = {{ViDA: Homeostatic Visual Domain Adapter for Continual Test Time Adaptation}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17657},
}

@inproceedings{neurips2026_ctrl_90666,
  title = {{CTRL: Continual Test-Time Reinforcement Learning for Large Language Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/153321},
}

@inproceedings{neurips2026_reliability_94382,
  title = {{Reliability-Budgeted Edge–Cloud Adaptation for Continual Multimodal Dehazing on UAV}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/154996},
}

@inproceedings{cvpr2026_cross_96683,
  title = {{Cross-Architecture Adaptation: Cloud-Edge Continual Test-Time Adaptation with Dynamic Sampling and Heterogeneous Distillation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Xu_Cross-Architecture_Adaptation_Cloud-Edge_Continual_Test-Time_Adaptation_with_Dynamic_Sampling_and_CVPR_2026_paper.html},
}

@inproceedings{cvpr2026_geco_97014,
  title = {{GeCo-SRT: Geometry-aware Continual Adaptation for Cross-Task Sim-to-Real Transfer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Yu_GeCo-SRT_Geometry-aware_Continual_Adaptation_for_Cross-Task_Sim-to-Real_Transfer_CVPR_2026_paper.html},
}

@inproceedings{cvpr2026_hyperbolic_97304,
  title = {{Hyperbolic Prototype Learning with Uncertainty-Aware Consistency for Continual Test-Time Segmentation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Gole_Hyperbolic_Prototype_Learning_with_Uncertainty-Aware_Consistency_for_Continual_Test-Time_Segmentation_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_decomposing_108570,
  title = {{Decomposing the Neurons: Activation Sparsity via Mixture of Experts for Continual Test Time Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/40922},
}