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Vision Transformers (ViTs) have shown competitive accuracy in image classification tasks compared with CNNs.
The pascal recognising textual entailment challenge
Ido Dagan, Oren Glickman, and Bernardo Magnini · 2005
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Automatically constructing a corpus of sentential paraphrases
William B. Dolan and Chris Brockett · 2005
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The second pascal recognising textual entailment challenge
R Bar Haim, Ido Dagan, Bill Dolan, Lisa Ferro, Danilo Giampiccolo, Bernardo Magnini, and Idan Szpektor · 2006
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The third pascal recognizing textual entailment challenge
Danilo Giampiccolo, Bernardo Magnini, Ido Dagan, and Bill Dolan · 2007
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The fifth pascal recognizing textual entailment challenge
Luisa Bentivogli, Peter Clark, Ido Dagan, and Danilo Giampiccolo · 2009
Earlier work this paper cites.
Imagenet: A large-scale hierarchical image database
Jia Deng, Wei Dong, Richard Socher, Li-Jia Li, Kai Li, and Li Fei-Fei · 2009
Earlier work this paper cites.
The winograd schema challenge
Hector Levesque, Ernest Davis, and Leora Morgenstern · 2012
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Learning invariant representations with local transformations
Kihyuk Sohn and Honglak Lee · 2012
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Recursive deep models for semantic compositionality over a sentiment treebank
Richard Socher, Alex Perelygin, Jean Wu, Jason Chuang, Christopher D Manning, Andrew Y Ng, and Christopher Potts · 2013
Earlier work this paper cites.
Long short-term memory recurrent neural network architectures for large scale acoustic modeling
Hasim Sak, Andrew W Senior, and Françoise Beaufays · 2014
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Deep residual learning for image recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, and Jian Sun · 2016
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Recurrent neural network for text classification with multi-task learning
Pengfei Liu, Xipeng Qiu, and Xuanjing Huang · 2016
Earlier work this paper cites.
SQuAD: 100,000+ questions for machine comprehension of text
Pranav Rajpurkar, Jian Zhang, Konstantin Lopyrev, and Percy Liang · 2016
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SemEval-2017 task 1: Semantic textual similarity multilingual and crosslingual focused evaluation
Daniel Cer, Mona Diab, Eneko Agirre, Iñigo Lopez-Gazpio, and Lucia Specia · 2017
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Mobilenets: Efficient convolutional neural networks for mobile vision applications
Andrew G Howard, Menglong Zhu, Bo Chen, Dmitry Kalenichenko, Weijun Wang, Tobias Weyand, Marco Andreetto, and Hartwig Adam · 2017
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Scale-aware fast r-cnn for pedestrian detection
Jianan Li, Xiaodan Liang, ShengMei Shen, Tingfa Xu, Jiashi Feng, and Shuicheng Yan · 2017
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Understanding the effective receptive field in deep convolutional neural networks
Wenjie Luo, Yujia Li, Raquel Urtasun, and Richard Zemel · 2017
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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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Residual attention network for image classification
Fei Wang, Mengqing Jiang, Chen Qian, Shuo Yang, Cheng Li, Honggang Zhang, Xiaogang Wang, and Xiaoou Tang · 2017
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Aggregated residual transformations for deep neural networks
Saining Xie, Ross Girshick, Piotr Dollár, Zhuowen Tu, and Kaiming He · 2017
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Quora question pairs, 2018
Zihan Chen, Hongbo Zhang, Xiaoji Zhang, and Leqi Zhao · 2018
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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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Improving language understanding by generative pre-training, 2018
Alec Radford, Karthik Narasimhan, Tim Salimans, and Ilya Sutskever · 2018
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Mobilenetv2: Inverted residuals and linear bottlenecks
Mark Sandler, Andrew Howard, Menglong Zhu, Andrey Zhmoginov, and Liang-Chieh Chen · 2018
Cited alongside, same era.
Glue: A multi-task benchmark and analysis platform for natural language understanding
Alex Wang, Amanpreet Singh, Julian Michael, Felix Hill, Omer Levy, and Samuel R Bowman · 2018
Cited alongside, same era.
A broad-coverage challenge corpus for sentence understanding through inference
Adina Williams, Nikita Nangia, and Samuel Bowman · 2018
Cited alongside, same era.
End-to-end dense video captioning with masked transformer
Luowei Zhou, Yingbo Zhou, Jason J Corso, Richard Socher, and Caiming Xiong · 2018
Cited alongside, same era.
Similarity of neural network representations revisited
Simon Kornblith, Mohammad Norouzi, Honglak Lee, and Geoffrey Hinton · 2019
Cited alongside, same era.
End-to-end video instance segmentation with transformers
Yuqing Wang, Zhaoliang Xu, Xinlong Wang, Chunhua Shen, Baoshan Cheng, Hao Shen, and Huaxia Xia · 2020
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Learning texture transformer network for image super-resolution
Fuzhi Yang, Huan Yang, Jianlong Fu, Hongtao Lu, and Baining Guo · 2020
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Revisiting knowledge distillation via label smoothing regularization
Li Yuan, Francis EH Tay, Guilin Li, Tao Wang, and Jiashi Feng · 2020
Later among the works it cites.
Learning joint spatial-temporal transformations for video inpainting
Yanhong Zeng, Jianlong Fu, and Hongyang Chao · 2020
Later among the works it cites.
Hengshuang Zhao, Li Jiang, Jiaya Jia, Philip Torr, and Vladlen Koltun · 2020
Later among the works it cites.
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Zhenzhong Lan, Mingda Chen, Sebastian Goodman, Kevin Gimpel, Piyush Sharma, and Radu Soricut · 2019
Cited alongside, same era.
Pytorch: An imperative style, high-performance deep learning library
Adam Paszke, Sam Gross, Francisco Massa, Adam Lerer, James Bradbury, Gregory Chanan, Trevor Killeen, Zeming Lin, Natalia Gimelshein, Luca Antiga, et al · 2019
Cited alongside, same era.
Efficientnet: Rethinking model scaling for convolutional neural networks
Mingxing Tan and Quoc V Le · 2019
Cited alongside, same era.
Fixing the train-test resolution discrepancy
Hugo Touvron, Andrea Vedaldi, Matthijs Douze, and Hervé Jégou · 2019
Cited alongside, same era.
Neural network acceptability judgments
Alex Warstadt, Amanpreet Singh, and Samuel R Bowman · 2019
Cited alongside, same era.
Pytorch image models
Ross Wightman · 2019
Cited alongside, same era.
Neural epitome search for architecture-agnostic network compression
Daquan Zhou, Xiaojie Jin, Qibin Hou, Kaixin Wang, Jianchao Yang, and Jiashi Feng · 2019
Cited alongside, same era.
Minghang Zheng, Peng Gao, Xiaogang Wang, Hongsheng Li, and Hao Dong · 2020
Later among the works it cites.
Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Later among the works it cites.
Lambdanetworks: Modeling long-range interactions without attention
Irwan Bello · 2021
Closest in time.
High-performance large-scale image recognition without normalization
Andrew Brock, Soham De, Samuel L Smith, and Karen Simonyan · 2021
Closest in time.
Crossvit: Cross-attention multi-scale vision transformer for image classification
Chun-Fu Chen, Quanfu Fan, and Rameswar Panda · 2021
Closest in time.
Convit: Improving vision transformers with soft convolutional inductive biases
Stéphane d’Ascoli, Hugo Touvron, Matthew Leavitt, Ari Morcos, Giulio Biroli, and Levent Sagun · 2021
Closest in time.
Attention is not all you need: Pure attention loses rank doubly exponentially with depth
Yihe Dong, Jean-Baptiste Cordonnier, and Andreas Loukas · 2021
Closest in time.
Improve vision transformers training by suppressing over-smoothing
Chengyue Gong, Dilin Wang, Meng Li, Vikas Chandra, and Qiang Liu · 2021
Closest in time.
Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, and Yunhe Wang · 2021
Closest in time.
Token labeling: Training a 85.4% top-1 accuracy vision transformer with 56m parameters on imagenet
Zihang Jiang, Qibin Hou, Li Yuan, Daquan Zhou, Xiaojie Jin, Anran Wang, and Jiashi Feng · 2021
Closest in time.
Localvit: Bringing locality to vision transformers
Yawei Li, Kai Zhang, Jiezhang Cao, Radu Timofte, and Luc Van Gool · 2021
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Swin transformer: Hierarchical vision transformer using shifted windows
Ze Liu, Yutong Lin, Yue Cao, Han Hu, Yixuan Wei, Zheng Zhang, Stephen Lin, and Baining Guo · 2021
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Conformer: Local features coupling global representations for visual recognition
Zhiliang Peng, Wei Huang, Shanzhi Gu, Lingxi Xie, Yaowei Wang, Jianbin Jiao, and Qixiang Ye · 2021
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Bottleneck transformers for visual recognition
Aravind Srinivas, Tsung-Yi Lin, Niki Parmar, Jonathon Shlens, Pieter Abbeel, and Ashish Vaswani · 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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Tokens-to-token vit: Training vision transformers from scratch on imagenet
Li Yuan, Yunpeng Chen, Tao Wang, Weihao Yu, Yujun Shi, Francis EH Tay, Jiashi Feng, and Shuicheng Yan · 2021
Closest in time.
Deepvit: Towards deeper vision transformer
Daquan Zhou, Bingyi Kang, Xiaojie Jin, Linjie Yang, Xiaochen Lian, Qibin Hou, and Jiashi Feng · 2021
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