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

@inproceedings{cvpr2023_visual_22542,
  title = {{Visual Prompt Multi-Modal Tracking}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22544},
}

@inproceedings{cvpr2022_expanding_18788,
  title = {{Expanding Large Pre-Trained Unimodal Models With Multimodal Information Injection for Image-Text Multimodal Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2022},
}

@inproceedings{aaai2024_dgl_5559,
  title = {{DGL: Dynamic Global-Local Prompt Tuning for Text-Video Retrieval}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28475},
}

@inproceedings{iclr2024_uniadapter_34876,
  title = {{UniAdapter: Unified Parameter-Efficient Transfer Learning for Cross-modal Modeling}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18198},
}

@inproceedings{aaai2025_densely_8692,
  title = {{Densely Connected Parameter-Efficient Tuning for Referring Image Segmentation}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32380},
}

@inproceedings{cvpr2024_fair_23447,
  title = {{Fair-VPT: Fair Visual Prompt Tuning for Image Classification}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30745},
}

@inproceedings{neurips2024_visual_73839,
  title = {{Visual Fourier Prompt Tuning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/93669},
}

@inproceedings{cvpr2024_calibrating_22943,
  title = {{Calibrating Multi-modal Representations: A Pursuit of Group Robustness without Annotations}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30214},
}

@inproceedings{cvpr2025_skip_27690,
  title = {{Skip Tuning: Pre-trained Vision-Language Models are Effective and Efficient Adapters Themselves}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33614},
}

@inproceedings{cvpr2025_da_25811,
  title = {{DA-VPT: Semantic-Guided Visual Prompt Tuning for Vision Transformers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2025},
  url = {https://cvpr.thecvf.com/virtual/2025/poster/33078},
}

@inproceedings{icml2023_pouf_41388,
  title = {{POUF: Prompt-Oriented Unsupervised Fine-tuning for Large Pre-trained Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/24588},
}

@inproceedings{icml2023_improving_41418,
  title = {{Improving Visual Prompt Tuning for Self-supervised Vision Transformers}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/25142},
}

@inproceedings{iclr2024_facing_34737,
  title = {{Facing the Elephant in the Room: Visual Prompt Tuning or Full finetuning?}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18337},
}

@inproceedings{aaai2025_in_9545,
  title = {{In-context Prompt-augmented Micro-video Popularity Prediction}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/33254},
}

@inproceedings{iclr2024_c_35077,
  title = {{C-TPT: Calibrated Test-Time Prompt Tuning for Vision-Language Models via Text Feature Dispersion}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17996},
}

@inproceedings{neurips2023_parameter_69503,
  title = {{Parameter-efficient Tuning of Large-scale Multimodal Foundation Model}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2023},
  url = {https://nips.cc/virtual/2023/poster/70411},
}

@inproceedings{iclr2024_mixture_35502,
  title = {{Mixture of LoRA Experts}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/17571},
}

@inproceedings{aaai2025_black_8273,
  title = {{Black-Box Test-Time Prompt Tuning for Vision-Language Models}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32652},
}

@inproceedings{aaai2025_prompt_10376,
  title = {{Prompt Tuning In a Compact Attribute Space}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2025},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/32365},
}

@inproceedings{icml2023_mitigating_42102,
  title = {{Mitigating Spurious Correlations in Multi-modal Models during Fine-tuning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2023},
  url = {https://icml.cc/virtual/2023/poster/23575},
}

@inproceedings{icml2025_qmamba_48015,
  title = {{QMamba: On First Exploration of Vision Mamba for Image Quality Assessment}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/44591},
}

@inproceedings{iclr2024_learning_34507,
  title = {{Learning Semantic Proxies from Visual Prompts for Parameter-Efficient Fine-Tuning in Deep Metric Learning}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/18567},
}

@inproceedings{icml2024_transferring_44652,
  title = {{Transferring Knowledge From Large Foundation Models to Small Downstream Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2024},
  url = {https://icml.cc/virtual/2024/poster/33800},
}

@inproceedings{icml2025_learn_46678,
  title = {{Learn from Downstream and Be Yourself in Multimodal Large Language Models Fine-Tuning}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/45894},
}

@inproceedings{aaai2026_peft_102592,
  title = {{PEFT-BoA: Parameter-Efficient Fine-Tuning with Bag-of-Adapters for Multi-Modal Object Re-identification}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/37537},
}

@inproceedings{icml2025_understanding_48844,
  title = {{Understanding and Mitigating Miscalibration in Prompt Tuning for Vision-Language Models}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2025},
  url = {https://icml.cc/virtual/2025/poster/43778},
}