% Key papers for Synthetic data and merging for CLIP (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{iclr2021_conditionally_30484,
  title = {{Conditionally Adaptive Multi-Task Learning: Improving Transfer Learning in NLP Using Fewer Parameters \& Less Data}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2021},
  url = {https://iclr.cc/virtual/2021/poster/2893},
}

@inproceedings{cvpr2024_pre_24505,
  title = {{Pre-trained Vision and Language Transformers Are Few-Shot Incremental Learners}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31093},
}

@inproceedings{cvpr2025_cl_25649,
  title = {{CL-LoRA: Continual Low-Rank Adaptation for Rehearsal-Free Class-Incremental Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34286},
}

@inproceedings{cvpr2024_continual_23030,
  title = {{Continual Forgetting for Pre-trained Vision Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31873},
}

@inproceedings{cvpr2024_brain_22874,
  title = {{Brain Decodes Deep Nets}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/29908},
}

@inproceedings{cvpr2025_synthetic_27790,
  title = {{Synthetic Data is an Elegant GIFT for Continual Vision-Language Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/32691},
}

@inproceedings{neurips2025_mixture_80117,
  title = {{Mixture of Noise for Pre-Trained Model-Based Class-Incremental Learning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=wI6oHXeTR8},
}

@inproceedings{neurips2025_merging_79665,
  title = {{Merging on the Fly Without Retraining: A Sequential Approach to Scalable Continual Model Merging}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=rdGMyTPhui},
}

@inproceedings{aaai2026_icm_104313,
  title = {{ICM-Fusion: In-Context Meta-Optimized LoRA Fusion for Multi-Task Adaptation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37840},
}

@inproceedings{cvpr2025_low_26824,
  title = {{Low-Rank Adaptation in Multilinear Operator Networks for Security-Preserving Incremental Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33975},
}

@inproceedings{neurips2023_learning_68637,
  title = {{Learning to Modulate pre-trained Models in RL}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/71201},
}

@inproceedings{neurips2024_leveraging_73958,
  title = {{Leveraging Catastrophic Forgetting to Develop Safe Diffusion Models against Malicious Finetuning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93554},
}

@inproceedings{aaai2026_compensating_107346,
  title = {{Compensating Distribution Drifts in Continual Learning with Pre-trained Vision Transformers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39698},
}

@inproceedings{cvpr2025_targeted_27822,
  title = {{Targeted Forgetting of Image Subgroups in CLIP Models}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/34034},
}

@inproceedings{iclr2024_tail_34433,
  title = {{TAIL: Task-specific Adapters for Imitation Learning with Large Pretrained Models}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18642},
}

@inproceedings{icml2025_proxy_47430,
  title = {{Proxy-FDA: Proxy-based Feature Distribution Alignment for Fine-tuning Vision Foundation Models without Forgetting}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45163},
}

@inproceedings{icml2025_lada_48872,
  title = {{LADA: Scalable Label-Specific CLIP Adapter for Continual Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43751},
}

@inproceedings{icml2026_continual_51062,
  title = {{Continual Model Routing in Evolving Model Hubs}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=IT7lA8t0S6},
}

@inproceedings{icml2026_can_51534,
  title = {{Can Muon Fine-tune Adam-Pretrained Models?}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=NKKwTEYdAm},
}

@inproceedings{icml2026_orthogonal_54466,
  title = {{Orthogonal Model Merging}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=pCaeMsqpCa},
}

@inproceedings{neurips2025_geoada_75531,
  title = {{GeoAda: Efficiently Finetune Geometric Diffusion Models with Equivariant Adapters}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=9AMNN3U7Ug},
}

@inproceedings{neurips2025_devfd_77812,
  title = {{DevFD : Developmental Face Forgery Detection by Learning Shared and Orthogonal LoRA Subspaces}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=Xpuci4SV06},
}