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Vision Transformers (ViTs) have achieved state-of-the-art performance on various computer vision applications.
Prime numbers
Richard Crandall and Carl Pomerance · 2001
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Imagenet classification with deep convolutional neural networks
Alex Krizhevsky, Ilya Sutskever, and Geoffrey E Hinton · 2012
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Estimating or propagating gradients through stochastic neurons for conditional computation
Yoshua Bengio, Nicholas Léonard, and Aaron Courville · 2013
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Gaussian error linear units (gelus)
Dan Hendrycks and Kevin Gimpel · 2016
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Dorefa-net: Training low bitwidth convolutional neural networks with low bitwidth gradients
Shuchang Zhou, Yuxin Wu, Zekun Ni, Xinyu Zhou, He Wen, and Yuheng Zou · 2016
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Incremental network quantization: Towards lossless cnns with low-precision weights
Aojun Zhou, Anbang Yao, Yiwen Guo, Lin Xu, and Yurong Chen · 2017
Earlier work this paper cites.
Pact: Parameterized clipping activation for quantized neural networks
Jungwook Choi, Zhuo Wang, Swagath Venkataramani, Pierce I-Jen Chuang, Vijayalakshmi Srinivasan, and Kailash Gopalakrishnan · 2018
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Quantization and training of neural networks for efficient integer-arithmetic-only inference
Benoit Jacob, Skirmantas Kligys, Bo Chen, Menglong Zhu, Matthew Tang, Andrew Howard, Hartwig Adam, and Dmitry Kalenichenko · 2018
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Quantizing deep convolutional networks for efficient inference: A whitepaper
Raghuraman Krishnamoorthi · 2018
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Fixing weight decay regularization in adam
Ilya Loshchilov and Frank Hutter · 2018
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Lq-nets: Learned quantization for highly accurate and compact deep neural networks
Dongqing Zhang, Jiaolong Yang, Dongqiangzi Ye, and Gang Hua · 2018
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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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Learned step size quantization
Steven K Esser, Jeffrey L McKinstry, Deepika Bablani, Rathinakumar Appuswamy, and Dharmendra S Modha · 2019
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Fully quantized network for object detection
Rundong Li, Yan Wang, Feng Liang, Hongwei Qin, Junjie Yan, and Rui Fan · 2019
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Haq: Hardware-aware automated quantization with mixed precision
Kuan Wang, Zhijian Liu, Yujun Lin, Ji Lin, and Song Han · 2019
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Lsq+: Improving low-bit quantization through learnable offsets and better initialization
Yash Bhalgat, Jinwon Lee, Markus Nagel, Tijmen Blankevoort, and Nojun Kwak · 2020
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End-to-end object detection with transformers
Nicolas Carion, Francisco Massa, Gabriel Synnaeve, Nicolas Usunier, Alexander Kirillov, and Sergey Zagoruyko · 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
Cited alongside, same era.
Additive powers-of-two quantization: An efficient non-uniform discretization for neural networks
Yuhang Li, Xin Dong, and Wei Wang · 2020
Cited alongside, same era.
Binary neural networks: A survey
Haotong Qin, Ruihao Gong, Xianglong Liu, Xiao Bai, Jingkuan Song, and Nicu Sebe · 2020
Cited alongside, same era.
Integer quantization for deep learning inference: Principles and empirical evaluation
Hao Wu, Patrick Judd, Xiaojie Zhang, Mikhail Isaev, and Paulius Micikevicius · 2020
Cited alongside, same era.
Efficient precision-adjustable architecture for softmax function in deep learning
Danyang Zhu, Siyuan Lu, Meiqi Wang, Jun Lin, and Zhongfeng Wang · 2020
Cited alongside, same era.
Nvit: Vision transformer compression and parameter redistribution
Huanrui Yang, Hongxu Yin, Pavlo Molchanov, Hai Li, and Jan Kautz · 2021
Later among the works it cites.
Hawq-v3: Dyadic neural network quantization
Zhewei Yao, Zhen Dong, Zhangcheng Zheng, Amir Gholami, Jiali Yu, Eric Tan, Leyuan Wang, Qijing Huang, Yida Wang, Michael Mahoney, et al · 2021
Later among the works it cites.
Ptq4vit: Post-training quantization framework for vision transformers
Zhihang Yuan, Chenhao Xue, Yiqi Chen, Qiang Wu, and Guangyu Sun · 2021
Later among the works it cites.
A survey on vision transformer
Kai Han, Yunhe Wang, Hanting Chen, Xinghao Chen, Jianyuan Guo, Zhenhua Liu, Yehui Tang, An Xiao, Chunjing Xu, Yixing Xu, et al · 2022
Closest in time.
Learning efficient vision transformers via fine-grained manifold distillation
Zhiwei Hao, Jianyuan Guo, Ding Jia, Kai Han, Yehui Tang, Chao Zhang, Han Hu, and Yunhe Wang · 2022
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Deformable detr: Deformable transformers for end-to-end object detection
Xizhou Zhu, Weijie Su, Lewei Lu, Bin Li, Xiaogang Wang, and Jifeng Dai · 2020
Cited alongside, same era.
Vivit: A video vision transformer
Anurag Arnab, Mostafa Dehghani, Georg Heigold, Chen Sun, Mario Lučić, and Cordelia Schmid · 2021
Cited alongside, same era.
Pre-trained image processing transformer
Hanting Chen, Yunhe Wang, Tianyu Guo, Chang Xu, Yiping Deng, Zhenhua Liu, Siwei Ma, Chunjing Xu, Chao Xu, and Wen Gao · 2021
Cited alongside, same era.
A survey of quantization methods for efficient neural network inference
Amir Gholami, Sehoon Kim, Zhen Dong, Zhewei Yao, Michael W Mahoney, and Kurt Keutzer · 2021
Cited alongside, same era.
Transformer in transformer
Kai Han, An Xiao, Enhua Wu, Jianyuan Guo, Chunjing Xu, and Yunhe Wang · 2021
Cited alongside, same era.
I-bert: Integer-only bert quantization
Sehoon Kim, Amir Gholami, Zhewei Yao, Michael W Mahoney, and Kurt Keutzer · 2021
Cited alongside, same era.
Towards fully 8-bit integer inference for the transformer model
Ye Lin, Yanyang Li, Tengbo Liu, Tong Xiao, Tongran Liu, and Jingbo Zhu · 2021
Cited alongside, same era.
Multi-dimensional vision transformer compression via dependency guided gaussian process search
Zejiang Hou and Sun-Yuan Kung · 2022
Closest in time.
Psaq-vit v2: Towards accurate and general data-free quantization for vision transformers
Zhikai Li, Mengjuan Chen, Junrui Xiao, and Qingyi Gu · 2022
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Patch similarity aware data-free quantization for vision transformers
Zhikai Li, Liping Ma, Mengjuan Chen, Junrui Xiao, and Qingyi Gu · 2022
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Dual-discriminator adversarial framework for data-free quantization
Zhikai Li, Liping Ma, Xianlei Long, Junrui Xiao, and Qingyi Gu · 2022
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Repq-vit: Scale reparameterization for post-training quantization of vision transformers
Zhikai Li, Junrui Xiao, Lianwei Yang, and Qingyi Gu · 2022
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Q-vit: Fully differentiable quantization for vision transformer
Zhexin Li, Tong Yang, Peisong Wang, and Jian Cheng · 2022
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Fq-vit: Post-training quantization for fully quantized vision transformer
Yang Lin, Tianyu Zhang, Peiqin Sun, Zheng Li, and Shuchang Zhou · 2022
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FasterTransformer, https://github.com/nvidia/fastertransformer.git, 2022
NVIDIA · 2022
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Patch slimming for efficient vision transformers
Yehui Tang, Kai Han, Yunhe Wang, Chang Xu, Jianyuan Guo, Chao Xu, and Dacheng Tao · 2022
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On-chip qnn: Towards efficient on-chip training of quantum neural networks
Hanrui Wang, Zirui Li, Jiaqi Gu, Yongshan Ding, David Z Pan, and Song Han · 2022
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Minivit: Compressing vision transformers with weight multiplexing
Jinnian Zhang, Houwen Peng, Kan Wu, Mengchen Liu, Bin Xiao, Jianlong Fu, and Lu Yuan · 2022
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