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Transformers yield state-of-the-art results across many tasks.
A note on piecewise linear and multilinear table interpolation in many dimensions
Alan Weiser and Sergio E Zarantonello · 1988
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Learning multiple layers of features from tiny images
Alex Krizhevsky and Geoffrey Hinton · 2009
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ImageNet Large Scale Visual Recognition Challenge
Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, and Li Fei-Fei · 2015
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The cityscapes dataset for semantic urban scene understanding
Marius Cordts, Mohamed Omran, Sebastian Ramos, Timo Rehfeld, Markus Enzweiler, Rodrigo Benenson, Uwe Franke, Stefan Roth, and Bernt Schiele · 2016
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Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Scene parsing through ade20k dataset
Bolei Zhou, Hang Zhao, Xavier Puig, Sanja Fidler, Adela Barriuso, and Antonio Torralba · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova · 2018
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Rethinking the value of network pruning
Zhuang Liu, Mingjie Sun, Tinghui Zhou, Gao Huang, and Trevor Darrell · 2018
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Improving language understanding by generative pre-training
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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The inaturalist species classification and detection dataset
Grant Van Horn, Oisin Mac Aodha, Yang Song, Yin Cui, Chen Sun, Alex Shepard, Hartwig Adam, Pietro Perona, and Serge Belongie · 2018
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Global sparse momentum sgd for pruning very deep neural networks
Xiaohan Ding, Guiguang Ding, Xiangxin Zhou, Yuchen Guo, Jungong Han, and Ji Liu · 2019
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Hawq: Hessian aware quantization of neural networks with mixed-precision
Zhen Dong, Zhewei Yao, Amir Gholami, Michael W Mahoney, and Kurt Keutzer · 2019
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Tinybert: Distilling bert for natural language understanding
Xiaoqi Jiao, Yichun Yin, Lifeng Shang, Xin Jiang, Xiao Chen, Linlin Li, Fang Wang, and Qun Liu · 2019
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Are sixteen heads really better than one?
Paul Michel, Omer Levy, and Graham Neubig · 2019
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Importance estimation for neural network pruning
Pavlo Molchanov, Arun Mallya, Stephen Tyree, Iuri Frosio, and Jan Kautz · 2019
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Robustness via curvature regularization, and vice versa
Seyed-Mohsen Moosavi-Dezfooli, Alhussein Fawzi, Jonathan Uesato, and Pascal Frossard · 2019
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Analyzing multi-head self-attention: Specialized heads do the heavy lifting, the rest can be pruned
Elena Voita, David Talbot, Fedor Moiseev, Rico Sennrich, and Ivan Titov · 2019
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Pytorch image models
Ross Wightman · 2019
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Language models are few-shot learners
Tom B Brown, Benjamin Mann, Nick Ryder, Melanie Subbiah, Jared Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, et al · 2020
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An image is worth 16x16 words: Transformers for image recognition at scale
Alexey Dosovitskiy, Lucas Beyer, Alexander Kolesnikov, Dirk Weissenborn, Xiaohua Zhai, Thomas Unterthiner, Mostafa Dehghani, Matthias Minderer, Georg Heigold, Sylvain Gelly, et al · 2020
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Designing network design spaces
Ilija Radosavovic, Raj Prateek Kosaraju, Ross Girshick, Kaiming He, and Piotr Dollár · 2020
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Dreaming to distill: Data-free knowledge transfer via deepinversion
Hongxu Yin, Pavlo Molchanov, Jose M Alvarez, Zhizhong Li, Arun Mallya, Derek Hoiem, Niraj K Jha, and Jan Kautz · 2020
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Data-free knowledge distillation for object detection
Akshay Chawla, Hongxu Yin, Pavlo Molchanov, and Jose Alvarez · 2021
Accelerating sparse deep neural networks
Asit Mishra, Jorge Albericio Latorre, Jeff Pool, Darko Stosic, Dusan Stosic, Ganesh Venkatesh, Chong Yu, and Paulius Micikevicius · 2021
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Dynamicvit: Efficient vision transformers with dynamic token sparsification
Yongming Rao, Wenliang Zhao, Benlin Liu, Jiwen Lu, Jie Zhou, and Cho-Jui Hsieh · 2021
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Halp: Hardware-aware latency pruning
Maying Shen, Hongxu Yin, Pavlo Molchanov, Lei Mao, Jianna Liu, and Jose M Alvarez · 2021
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Training data-efficient image transformers & distillation through attention
Hugo Touvron, Matthieu Cord, Matthijs Douze, Francisco Massa, Alexandre Sablayrolles, and Hervé Jégou · 2021
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Going deeper with image transformers
Hugo Touvron, Matthieu Cord, Alexandre Sablayrolles, Gabriel Synnaeve, and Hervé Jégou · 2021
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Glit: Neural architecture search for global and local image transformer
Boyu Chen, Peixia Li, Chuming Li, Baopu Li, Lei Bai, Chen Lin, Ming Sun, Junjie Yan, and Wanli Ouyang · 2021
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Autoformer: Searching transformers for visual recognition
Minghao Chen, Houwen Peng, Jianlong Fu, and Haibin Ling · 2021
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Chasing sparsity in vision transformers: An end-to-end exploration
Tianlong Chen, Yu Cheng, Zhe Gan, Lu Yuan, Lei Zhang, and Zhangyang Wang · 2021
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Conditional positional encodings for vision transformers
Xiangxiang Chu, Zhi Tian, Bo Zhang, Xinlong Wang, Xiaolin Wei, Huaxia Xia, and Chunhua Shen · 2021
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Convit: Improving vision transformers with soft convolutional inductive biases
Stéphane d’Ascoli, Hugo Touvron, Matthew L Leavitt, Ari S Morcos, Giulio Biroli, and Levent Sagun · 2021
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Levit: a vision transformer in convnet’s clothing for faster inference
Ben Graham, Alaaeldin El-Nouby, Hugo Touvron, Pierre Stock, Armand Joulin, Hervé Jégou, and Matthijs Douze · 2021
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Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, and Yunhe Wang · 2021
Cited alongside, same era.
Pyramid vision transformer: A versatile backbone for dense prediction without convolutions
Wenhai Wang, Enze Xie, Xiang Li, Deng-Ping Fan, Kaitao Song, Ding Liang, Tong Lu, Ping Luo, and Ling Shao · 2021
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Cvt: Introducing convolutions to vision transformers
Haiping Wu, Bin Xiao, Noel Codella, Mengchen Liu, Xiyang Dai, Lu Yuan, and Lei Zhang · 2021
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Huanrui Yang, Xiaoxuan Yang, Neil Zhenqiang Gong, and Yiran Chen · 2021
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Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Zihang Jiang, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip HS Torr, et al · 2021
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Rethinking semantic segmentation from a sequence-to-sequence perspective with transformers
Sixiao Zheng, Jiachen Lu, Hengshuang Zhao, Xiatian Zhu, Zekun Luo, Yabiao Wang, Yanwei Fu, Jianfeng Feng, Tao Xiang, Philip H.S. Torr, and Li Zhang · 2021
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Deepvit: Towards deeper vision transformer
Daquan Zhou, Bingyi Kang, Xiaojie Jin, Linjie Yang, Xiaochen Lian, Zihang Jiang, Qibin Hou, and Jiashi Feng · 2021
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Mingjian Zhu, Kai Han, Yehui Tang, and Yunhe Wang · 2021
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Auto-scaling vision transformers without training
Wuyang Chen, Wei Huang, Xianzhi Du, Xiaodan Song, Zhangyang Wang, and Denny Zhou · 2022
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Global context vision transformers
Ali Hatamizadeh, Hongxu Yin, Jan Kautz, and Pavlo Molchanov · 2022
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EVit: Expediting vision transformers via token reorganizations
Youwei Liang, Chongjian GE, Zhan Tong, Yibing Song, Jue Wang, and Pengtao Xie · 2022
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Hessian-aware pruning and optimal neural implant
Shixing Yu, Zhewei Yao, Amir Gholami, Zhen Dong, Sehoon Kim, Michael W Mahoney, and Kurt Keutzer · 2022
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