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

@inproceedings{aaai2024_irprunedet_6255,
  title = {{IRPruneDet: Efficient Infrared Small Target Detection via Wavelet Structure-Regularized Soft Channel Pruning}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2024},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/28551},
}

@inproceedings{aaai2022_width_2957,
  title = {{Width \& Depth Pruning for Vision Transformers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2022},
  url = {https://aaai.org/papers/03143-width-depth-pruning-for-vision-transformers/},
}

@inproceedings{neurips2021_chasing_61965,
  title = {{Chasing Sparsity in Vision Transformers: An End-to-End Exploration}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2021},
  url = {https://nips.cc/virtual/2021/poster/28340},
}

@inproceedings{cvpr2023_joint_21292,
  title = {{Joint Token Pruning and Squeezing Towards More Aggressive Compression of Vision Transformers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/23087},
}

@inproceedings{cvpr2023_x_22581,
  title = {{X-Pruner: eXplainable Pruning for Vision Transformers}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22310},
}

@inproceedings{cvpr2023_global_21089,
  title = {{Global Vision Transformer Pruning With Hessian-Aware Saliency}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22150},
}

@inproceedings{cvpr2023_sparsevit_22240,
  title = {{SparseViT: Revisiting Activation Sparsity for Efficient High-Resolution Vision Transformer}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/21307},
}

@inproceedings{cvpr2023_boost_20493,
  title = {{Boost Vision Transformer With GPU-Friendly Sparsity and Quantization}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/22832},
}

@inproceedings{iclr2022_unified_30949,
  title = {{Unified Visual Transformer Compression}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2022},
  url = {https://iclr.cc/virtual/2022/poster/6958},
}

@inproceedings{cvpr2023_pruning_21945,
  title = {{Pruning Parameterization With Bi-Level Optimization for Efficient Semantic Segmentation on the Edge}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2023},
  url = {https://cvpr.thecvf.com/virtual/2023/poster/20987},
}

@inproceedings{aaai2023_gohsp_3752,
  title = {{GOHSP: A Unified Framework of Graph and Optimization-Based Heterogeneous Structured Pruning for Vision Transformer}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2023},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/26298},
}

@inproceedings{icml2022_platon_40986,
  title = {{PLATON: Pruning Large Transformer Models with Upper Confidence Bound of Weight Importance}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2022},
  url = {https://icml.cc/virtual/2022/poster/17017},
}

@inproceedings{neurips2022_savit_66335,
  title = {{SAViT: Structure-Aware Vision Transformer Pruning via Collaborative Optimization}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/55067},
}

@inproceedings{cvpr2024_once_24351,
  title = {{Once for Both: Single Stage of Importance and Sparsity Search for Vision Transformer Compression}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2024},
  url = {https://cvpr.thecvf.com/virtual/2024/poster/30044},
}

@inproceedings{neurips2022_vtc_64508,
  title = {{VTC-LFC: Vision Transformer Compression with Low-Frequency Components}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2022},
  url = {https://nips.cc/virtual/2022/poster/54752},
}

@inproceedings{neurips2024_finding_70779,
  title = {{Finding Transformer Circuits With Edge Pruning}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/96350},
}

@inproceedings{neurips2024_exploring_73171,
  title = {{Exploring Token Pruning in Vision State Space Models}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2024},
  url = {https://neurips.cc/virtual/2024/poster/94262},
}

@inproceedings{icml2026_rethinking_50046,
  title = {{Rethinking Depth Pruning for Vision Transformers: A Heterogeneity-Aware Perspective}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=8X5SOsxwQi},
}

@inproceedings{icml2026_toast_55126,
  title = {{ToaSt: Token Channel Selection and Structured Pruning for Efficient ViT}},
  booktitle = {International Conference on Machine Learning (ICML)},
  year = {2026},
  url = {https://openreview.net/forum?id=vpwx8GRbkZ},
}

@inproceedings{neurips2025_elastic_76922,
  title = {{Elastic ViTs from Pretrained Models without Retraining}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2025},
  url = {https://openreview.net/forum?id=OU6FXkSIe0},
}

@inproceedings{iclr2025_adaptive_82413,
  title = {{Adaptive Pruning of Pretrained Transformer via Differential Inclusions}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2025},
  url = {https://iclr.cc/virtual/2025/poster/29380},
}

@inproceedings{neurips2026_corp_90556,
  title = {{CORP: Closed-Form One-shot Representation-Preserving Structured Pruning for Transformers}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/150895},
}

@inproceedings{neurips2026_dense_90726,
  title = {{Dense Structural Compression of Transformers via Gauge-Correct Channel Removal}},
  booktitle = {Advances in Neural Information Processing Systems (NeurIPS)},
  year = {2026},
  url = {https://neurips.cc/virtual/2026/poster/149337},
}

@inproceedings{cvpr2026_nuwa_99664,
  title = {{NuWa: Deriving Lightweight Class-Specific Vision Transformers for Edge Devices}},
  booktitle = {IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR)},
  year = {2026},
  url = {https://openaccess.thecvf.com/content/CVPR2026/html/Wei_NuWa_Deriving_Lightweight_Class-Specific_Vision_Transformers_for_Edge_Devices_CVPR_2026_paper.html},
}

@inproceedings{aaai2026_logic_106843,
  title = {{LoGIC: Multi-LoRA Guided Importance Consensus for Multi-Task Pruning in Vision Transformers}},
  booktitle = {AAAI Conference on Artificial Intelligence (AAAI)},
  year = {2026},
  url = {https://ojs.aaai.org/index.php/AAAI/article/view/39195},
}

@inproceedings{iclr2024_synergistic_33900,
  title = {{Synergistic Patch Pruning for Vision Transformer: Unifying Intra- \& Inter-Layer Patch Importance}},
  booktitle = {International Conference on Learning Representations (ICLR)},
  year = {2024},
  url = {https://iclr.cc/virtual/2024/poster/19175},
}