% Key papers for Parameter-efficient transfer analysis (scime atlas, https://atlas.scime.ai). Authors are not included: add them from the paper pages.

@inproceedings{cvpr2017_fine_12279,
  title = {{Fine-Tuning Convolutional Neural Networks for Biomedical Image Analysis: Actively and Incrementally}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{iclr2022_towards_30800,
  title = {{Towards a Unified View of Parameter-Efficient Transfer Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6524},
}

@inproceedings{cvpr2019_attentive_13874,
  title = {{Attentive Single-Tasking of Multiple Tasks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2017_growing_12320,
  title = {{Growing a Brain: Fine-Tuning by Increasing Model Capacity}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2017},
}

@inproceedings{icml2019_parameter_37645,
  title = {{Parameter-Efficient Transfer Learning for NLP}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4119},
}

@inproceedings{aaai2020_towards_103169,
  title = {{Towards Making the Most of BERT in Neural Machine Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6479},
}

@inproceedings{icml2019_bert_37172,
  title = {{BERT and PALs: Projected Attention Layers for Efficient Adaptation in Multi-Task Learning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2019},
  url = {https://icml.cc/virtual/2019/poster/4070},
}

@inproceedings{iclr2019_delta_29183,
  title = {{DELTA: DEEP LEARNING TRANSFER USING FEATURE MAP WITH ATTENTION FOR CONVOLUTIONAL NETWORKS}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/644},
}

@inproceedings{aaai2020_bridging_103142,
  title = {{Bridging the Gap between Pre-Training and Fine-Tuning for End-to-End Speech Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6452},
}

@inproceedings{aaai2020_acquiring_103155,
  title = {{Acquiring Knowledge from Pre-Trained Model to Neural Machine Translation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/6465},
}

@inproceedings{cvpr2022_task_19984,
  title = {{Task Adaptive Parameter Sharing for Multi-Task Learning}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2021_transtailor_1552,
  title = {{TransTailor: Pruning the Pre-trained Model for Improved Transfer Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/08627-transtailor-pruning-the-pre-trained-model-for-improved-transfer-learning/},
}

@inproceedings{cvpr2018_efficient_13057,
  title = {{Efficient Parametrization of Multi-Domain Deep Neural Networks}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2018},
  url = {https://openaccess.thecvf.com/content_cvpr_2018/html/Rebuffi_Efficient_Parametrization_of_CVPR_2018_paper.html},
}

@inproceedings{iclr2019_k_28786,
  title = {{K for the Price of 1: Parameter-efficient Multi-task and Transfer Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2019},
  url = {https://iclr.cc/virtual/2019/poster/898},
}

@inproceedings{aaai2020_adafilter_101963,
  title = {{AdaFilter: Adaptive Filter Fine-Tuning for Deep Transfer Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2020},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/5824},
}

@inproceedings{aaai2021_improving_771,
  title = {{Improving the Efficiency and Effectiveness for BERT-based Entity Resolution}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2021},
  url = {https://aaai.org/papers/13226-improving-the-efficiency-and-effectiveness-for-bert-based-entity-resolution/},
}

@inproceedings{aaai2018_efficient_102507,
  title = {{Efficient K-Shot Learning With Regularized Deep Networks}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2018},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/11774},
}

@inproceedings{cvpr2019_nettailor_14563,
  title = {{NetTailor: Tuning the Architecture, Not Just the Weights}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2019},
}

@inproceedings{cvpr2023_clipping_20545,
  title = {{CLIPPING: Distilling CLIP-Based Models With a Student Base for Video-Language Retrieval}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/20979},
}

@inproceedings{neurips2020_what_61095,
  title = {{What Do Neural Networks Learn When Trained With Random Labels?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2020},
  url = {https://nips.cc/virtual/2020/poster/18668},
}

@inproceedings{cvpr2024_time_25016,
  title = {{Time- Memory- and Parameter-Efficient Visual Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30431},
}

@inproceedings{cvpr2024_training_25077,
  title = {{Training-Free Pretrained Model Merging}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31889},
}

@inproceedings{aaai2025_no_10121,
  title = {{No More Tuning: Prioritized Multi-Task Learning with Lagrangian Differential Multiplier Methods}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33255},
}

@inproceedings{iclr2024_when_34143,
  title = {{When Do Prompting and Prefix-Tuning Work? A Theory of Capabilities and Limitations}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18932},
}

@inproceedings{neurips2024_tunetables_71268,
  title = {{TuneTables: Context Optimization for Scalable Prior-Data Fitted Networks}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95977},
}

@inproceedings{iclr2024_lemon_33567,
  title = {{LEMON: Lossless model expansion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19508},
}

@inproceedings{cvpr2024_efficient_23339,
  title = {{Efficient Stitchable Task Adaptation}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/31736},
}

@inproceedings{cvpr2025_pleas_27191,
  title = {{PLeaS - Merging Models with Permutations and Least Squares}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33794},
}

@inproceedings{neurips2024_where_71683,
  title = {{Where does In-context Learning Happen in Large Language Models?}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/95599},
}

@inproceedings{aaai2025_citrus_8416,
  title = {{CiTrus: Squeezing Extra Performance out of Low-data Bio-signal Transfer Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33844},
}

@inproceedings{aaai2025_exploring_9080,
  title = {{Exploring Task-Level Optimal Prompts for Visual In-Context Learning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33199},
}

@inproceedings{aaai2025_wasserstein_11266,
  title = {{Wasserstein Distance Constraint and Parameter Sparsification for Batched and Iterative Knowledge Editing}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/34686},
}

@inproceedings{iclr2024_transferring_34744,
  title = {{Transferring Learning Trajectories of Neural Networks}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18330},
}

@inproceedings{icml2024_revisiting_43351,
  title = {{Revisiting the Power of Prompt for Visual Tuning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/35101},
}

@inproceedings{neurips2025_enhancing_79001,
  title = {{Enhancing Visual Prompting through Expanded Transformation Space and Overfitting Mitigation}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=kdHz4y1ADc},
}

@inproceedings{neurips2025_machine_79465,
  title = {{Machine Unlearning via Task Simplex Arithmetic}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=pe92NSPLE8},
}

@inproceedings{iclr2025_lines_81647,
  title = {{LiNeS: Post-training Layer Scaling Prevents Forgetting and Enhances Model Merging}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/30130},
}

@inproceedings{iclr2025_unsupervised_82101,
  title = {{Unsupervised Model Tree Heritage Recovery}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29687},
}

@inproceedings{iclr2025_towards_83472,
  title = {{Towards Scalable Exact Machine Unlearning Using Parameter-Efficient Fine-Tuning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/28344},
}

@inproceedings{aaai2026_diet_107079,
  title = {{DIET: Machine Unlearning on a Data-Diet}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39431},
}