@book{Lamport:Book:1989,
 author = {Lamport, Leslie},
 title = {Latex: A Document Preparation System},
 year = {1986},
 isbn = {0-201-15790-X},
 publisher = {Addison-Wesley Longman Publishing Co., Inc.},
 address = {Boston, MA, USA},
}
@inproceedings{yu2022metaformer,
  title={Metaformer is actually what you need for vision},
  author={Yu, Weihao and Luo, Mi and Zhou, Pan and Si, Chenyang and Zhou, Yichen and Wang, Xinchao and Feng, Jiashi and Yan, Shuicheng},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={10819--10829},
  year={2022}
}
@inproceedings{press2021train,
  title={Train Short, Test Long: Attention with Linear Biases Enables Input Length Extrapolation},
  author={Press, Ofir and Smith, Noah and Lewis, Mike},
  booktitle={International Conference on Learning Representations},
  year={2021}
}
@inproceedings{hua2022transformer,
  title={Transformer quality in linear time},
  author={Hua, Weizhe and Dai, Zihang and Liu, Hanxiao and Le, Quoc},
  booktitle={International conference on machine learning},
  pages={9099--9117},
  year={2022},
  organization={PMLR}
}
@article{wang2023bitnet,
  title={Bitnet: Scaling 1-bit transformers for large language models},
  author={Wang, Hongyu and Ma, Shuming and Dong, Li and Huang, Shaohan and Wang, Huaijie and Ma, Lingxiao and Yang, Fan and Wang, Ruiping and Wu, Yi and Wei, Furu},
  journal={arXiv preprint arXiv:2310.11453},
  year={2023}
}


@article{xie2021segformer,
  title={SegFormer: Simple and efficient design for semantic segmentation with transformers},
  author={Xie, Enze and Wang, Wenhai and Yu, Zhiding and Anandkumar, Anima and Alvarez, Jose M and Luo, Ping},
  journal={Advances in neural information processing systems},
  volume={34},
  pages={12077--12090},
  year={2021}
}
@article{hubara2016binarized,
  title={Binarized neural networks},
  author={Hubara, Itay and Courbariaux, Matthieu and Soudry, Daniel and El-Yaniv, Ran and Bengio, Yoshua},
  journal={Advances in neural information processing systems},
  volume={29},
  year={2016}
}
@inproceedings{bond2022unleashing,
  title={Unleashing transformers: Parallel token prediction with discrete absorbing diffusion for fast high-resolution image generation from vector-quantized codes},
  author={Bond-Taylor, Sam and Hessey, Peter and Sasaki, Hiroshi and Breckon, Toby P and Willcocks, Chris G},
  booktitle={European Conference on Computer Vision},
  pages={170--188},
  year={2022},
  organization={Springer}
}
@article{hering2022learn2reg,
  title={Learn2Reg: comprehensive multi-task medical image registration challenge, dataset and evaluation in the era of deep learning},
  author={Hering, Alessa and Hansen, Lasse and Mok, Tony CW and Chung, Albert CS and Siebert, Hanna and H{\"a}ger, Stephanie and Lange, Annkristin and Kuckertz, Sven and Heldmann, Stefan and Shao, Wei and others},
  journal={IEEE Transactions on Medical Imaging},
  volume={42},
  number={3},
  pages={697--712},
  year={2022},
  publisher={IEEE}
}
@article{van2024lumbar,
  title={Lumbar spine segmentation in MR images: a dataset and a public benchmark},
  author={van der Graaf, Jasper W and van Hooff, Miranda L and Buckens, Constantinus FM and Rutten, Matthieu and van Susante, Job LC and Kroeze, Robert Jan and de Kleuver, Marinus and van Ginneken, Bram and Lessmann, Nikolas},
  journal={Scientific Data},
  volume={11},
  number={1},
  pages={264},
  year={2024}
}
@article{ji2022amos,
  title={Amos: A large-scale abdominal multi-organ benchmark for versatile medical image segmentation},
  author={Ji, Yuanfeng and Bai, Haotian and Ge, Chongjian and Yang, Jie and Zhu, Ye and Zhang, Ruimao and Li, Zhen and Zhanng, Lingyan and Ma, Wanling and Wan, Xiang and others},
  journal={Advances in neural information processing systems},
  volume={35},
  pages={36722--36732},
  year={2022}
}
@article{dorent2023crossmoda,
  title={CrossMoDA 2021 challenge: Benchmark of cross-modality domain adaptation techniques for vestibular schwannoma and cochlea segmentation},
  author={Dorent, Reuben and Kujawa, Aaron and Ivory, Marina and Bakas, Spyridon and Rieke, Nicola and Joutard, Samuel and Glocker, Ben and Cardoso, Jorge and Modat, Marc and Batmanghelich, Kayhan and others},
  journal={Medical Image Analysis},
  volume={83},
  pages={102628},
  year={2023},
  publisher={Elsevier}
}
@article{vaswani2017attention,
  title={Attention is all you need},
 author = {Vaswani, Ashish and Shazeer, Noam and Parmar, Niki and Uszkoreit, Jakob and Jones, Llion and Gomez, Aidan N and Kaiser, \L ukasz and Polosukhin, Illia},
  journal={Advances in Neural Information Processing Systems},
  year={2017}
}
@article{zhang2021medq,
  title={MedQ: Lossless ultra-low-bit neural network quantization for medical image segmentation},
  author={Zhang, Rongzhao and Chung, Albert CS},
  journal={Medical Image Analysis},
  volume={73},
  pages={102200},
  year={2021},
  publisher={Elsevier}
}

@article{banner2018scalable,
  title={Scalable methods for 8-bit training of neural networks},
  author={Banner, Ron and Hubara, Itay and Hoffer, Elad and Soudry, Daniel},
  journal={Advances in neural information processing systems},
  volume={31},
  year={2018}
} 
@inproceedings{wiedemann2020dithered,
  title={Dithered backprop: A sparse and quantized backpropagation algorithm for more efficient deep neural network training},
  author={Wiedemann, Simon and Mehari, Temesgen and Kepp, Kevin and Samek, Wojciech},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition Workshops},
  pages={720--721},
  year={2020}
}
@article{heinrich2018ternarynet,
  title={TernaryNet: faster deep model inference without GPUs for medical 3D segmentation using sparse and binary convolutions},
  author={Heinrich, Mattias P and Blendowski, Max and Oktay, Ozan},
  journal={International journal of computer assisted radiology and surgery},
  volume={13},
  pages={1311--1320},
  year={2018},
  publisher={Springer}
}
@article{liu2021post,
  title={Post-training quantization for vision transformer},
  author={Liu, Zhenhua and Wang, Yunhe and Han, Kai and Zhang, Wei and Ma, Siwei and Gao, Wen},
  journal={Advances in Neural Information Processing Systems},
  volume={34},
  pages={28092--28103},
  year={2021}
}
@article{liu2022bit,
  title={Bit: Robustly binarized multi-distilled transformer},
  author={Liu, Zechun and Oguz, Barlas and Pappu, Aasish and Xiao, Lin and Yih, Scott and Li, Meng and Krishnamoorthi, Raghuraman and Mehdad, Yashar},
  journal={Advances in neural information processing systems},
  volume={35},
  pages={14303--14316},
  year={2022}
}
@inproceedings{kitaev2019reformer,
  title={Reformer: The Efficient Transformer},
  author={Kitaev, Nikita and Kaiser, Lukasz and Levskaya, Anselm},
  booktitle={International Conference on Learning Representations},
  year={2019}
}
@inproceedings{sun2021sparse,
  title={Sparse attention with learning to hash},
  author={Sun, Zhiqing and Yang, Yiming and Yoo, Shinjae},
  booktitle={International Conference on Learning Representations},
  year={2021}
}
@article{dettmers2022gpt3,
  title={Gpt3. int8 (): 8-bit matrix multiplication for transformers at scale},
  author={Dettmers, Tim and Lewis, Mike and Belkada, Younes and Zettlemoyer, Luke},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={30318--30332},
  year={2022}
}

@inproceedings{rastegari2016xnor,
  title={Xnor-net: Imagenet classification using binary convolutional neural networks},
  author={Rastegari, Mohammad and Ordonez, Vicente and Redmon, Joseph and Farhadi, Ali},
  booktitle={European conference on computer vision},
  pages={525--542},
  year={2016},
  organization={Springer}
}
@inproceedings{friedrich2024wdm,
  title={Wdm: 3d wavelet diffusion models for high-resolution medical image synthesis},
  author={Friedrich, Paul and Wolleb, Julia and Bieder, Florentin and Durrer, Alicia and Cattin, Philippe C},
  booktitle={MICCAI Workshop on Deep Generative Models},
  pages={11--21},
  year={2024},
  organization={Springer}
}
@inproceedings{wolleb2022diffusion,
  title={Diffusion models for medical anomaly detection},
  author={Wolleb, Julia and Bieder, Florentin and Sandk{\"u}hler, Robin and Cattin, Philippe C},
  booktitle={International Conference on Medical image computing and computer-assisted intervention},
  pages={35--45},
  year={2022},
  organization={Springer}
}
@inproceedings{bieder2023memory,
  title={Memory-efficient 3d denoising diffusion models for medical image processing},
  author={Bieder, Florentin and Wolleb, Julia and Durrer, Alicia and Sandkuehler, Robin and Cattin, Philippe C},
  booktitle={Medical Imaging with Deep Learning},
  year={2023}
}

@article{courbariaux2015binaryconnect,
  title={Binaryconnect: Training deep neural networks with binary weights during propagations},
  author={Courbariaux, Matthieu and Bengio, Yoshua and David, Jean-Pierre},
  journal={Advances in neural information processing systems},
  year={2015}
}
@inproceedings{zhang2022pokebnn,
  title={Pokebnn: A binary pursuit of lightweight accuracy},
  author={Zhang, Yichi and Zhang, Zhiru and Lew, Lukasz},
  booktitle={Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition},
  pages={12475--12485},
  year={2022}
}
@article{pang2023slim,
  title={Slim UNETR: Scale hybrid transformers to efficient 3D medical image segmentation under limited computational resources},
  author={Pang, Yan and Liang, Jiaming and Huang, Teng and Chen, Hao and Li, Yunhao and Li, Dan and Huang, Lin and Wang, Qiong},
  journal={IEEE Transactions on Medical Imaging},
  year={2023},
  publisher={IEEE}
}
@article{milakov2018online,
  title={Online normalizer calculation for softmax},
  author={Milakov, Maxim and Gimelshein, Natalia},
  journal={arXiv preprint arXiv:1805.02867},
  year={2018}
}

@article{dao2022flashattention,
  title={Flashattention: Fast and memory-efficient exact attention with io-awareness},
  author={Dao, Tri and Fu, Dan and Ermon, Stefano and Rudra, Atri and R{\'e}, Christopher},
  journal={Advances in Neural Information Processing Systems},
  volume={35},
  pages={16344--16359},
  year={2022}
}

@inproceedings{caron2021emerging,
  title={Emerging properties in self-supervised vision transformers},
  author={Caron, Mathilde and Touvron, Hugo and Misra, Ishan and J{\'e}gou, Herv{\'e} and Mairal, Julien and Bojanowski, Piotr and Joulin, Armand},
  booktitle={Proceedings of the IEEE/CVF international conference on computer vision},
  pages={9650--9660},
  year={2021}
}

@article{van2017neural,
  title={Neural discrete representation learning},
  author={Van Den Oord, Aaron and Vinyals, Oriol and others},
  journal={Advances in neural information processing systems},
  volume={30},
  year={2017}
}

@inproceedings{esser2021taming,
  title={Taming transformers for high-resolution image synthesis},
  author={Esser, Patrick and Rombach, Robin and Ommer, Bjorn},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={12873--12883},
  year={2021}
}

@inproceedings{gu2022vector,
  title={Vector quantized diffusion model for text-to-image synthesis},
  author={Gu, Shuyang and Chen, Dong and Bao, Jianmin and Wen, Fang and Zhang, Bo and Chen, Dongdong and Yuan, Lu and Guo, Baining},
  booktitle={Proceedings of the IEEE/CVF conference on computer vision and pattern recognition},
  pages={10696--10706},
  year={2022}
}

@inproceedings{cao2022swin,
  title={Swin-unet: Unet-like pure transformer for medical image segmentation},
  author={Cao, Hu and Wang, Yueyue and Chen, Joy and Jiang, Dongsheng and Zhang, Xiaopeng and Tian, Qi and Wang, Manning},
  booktitle={European conference on computer vision},
  pages={205--218},
  year={2022},
  organization={Springer}
}

@article{chen20233d,
  title={3d transunet: Advancing medical image segmentation through vision transformers},
  author={Chen, Jieneng and Mei, Jieru and Li, Xianhang and Lu, Yongyi and Yu, Qihang and Wei, Qingyue and Luo, Xiangde and Xie, Yutong and Adeli, Ehsan and Wang, Yan and others},
  journal={arXiv preprint arXiv:2310.07781},
  year={2023}
}

@article{chen2021transunet,
  title={Transunet: Transformers make strong encoders for medical image segmentation},
  author={Chen, Jieneng and Lu, Yongyi and Yu, Qihang and Luo, Xiangde and Adeli, Ehsan and Wang, Yan and Lu, Le and Yuille, Alan L and Zhou, Yuyin},
  journal={arXiv preprint arXiv:2102.04306},
  year={2021}
}

@article{he2023h2former,
  title={H2Former: An efficient hierarchical hybrid transformer for medical image segmentation},
  author={He, Along and Wang, Kai and Li, Tao and Du, Chengkun and Xia, Shuang and Fu, Huazhu},
  journal={IEEE Transactions on Medical Imaging},
  volume={42},
  number={9},
  pages={2763--2775},
  year={2023},
  publisher={IEEE}
}
@misc{Hinton:arXiv:2015:Distilling,
 title={Distilling the knowledge in a neural network},
 author={Hinton, Geoffrey and Vinyals, Oriol and Dean, Jeff},
 OPTeprinttype={arXiv},
 OPTeprint={1503.02531},
 howpublished={Eprint \href{http://arxiv.org/abs/1503.02531}{arXiv:1503.02531}},
 OPTurl={http://arxiv.org/abs/1503.02531},
 year=2015
}