LightSeq: A High Performance Inference Library for Transformers

Effective approaches to attention-based neural machine translation

Thang Luong, Hieu Pham, and Christopher D. Manning. 2015 · 2015

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Efficient inference with tensorrt

Han Vanholder. 2016 · 2016

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A computational model for tensorflow: an introduction

Martín Abadi, Michael Isard, and Derek Gordon Murray. 2017 · 2017

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Enriching word vectors with subword information

Piotr Bojanowski, Edouard Grave, Armand Joulin, and Tomas Mikolov. 2017 · 2017

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Attention is all you need

Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017b · 2017

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TVM: An automated end-to-end optimizing compiler for deep learning

Tianqi Chen, Thierry Moreau, Ziheng Jiang, Lianmin Zheng, Eddie Yan, Haichen Shen, Meghan Cowan, Leyuan Wang, Yuwei Hu, Luis Ceze, Carlos Guestrin, and Arvind Krishnamurthy. 2018 · 2018

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Understanding back-translation at scale

Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018 · 2018

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Diverse beam search for improved description of complex scenes

Ashwin K. Vijayakumar, Michael Cogswell, Ramprasaath R. Selvaraju, Qing Sun, Stefan Lee, David J. Crandall, and Dhruv Batra. 2018 · 2018

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Transformer-xl: Attentive language models beyond a fixed-length context

Zihang Dai, Zhilin Yang, Yiming Yang, Jaime G. Carbonell, Quoc Viet Le, and Ruslan Salakhutdinov. 2019 · 2019

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BERT: pre-training of deep bidirectional transformers for language understanding

Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019

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Language models are unsupervised multitask learners

Alec Radford, Jeffrey Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019

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The curious case of neural text degeneration

Efficient inference for neural machine translation

Yi-Te Hsu, Sarthak Garg, Yi-Hsiu Liao, and Ilya Chatsviorkin. 2020 · 2020

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FastFormers: Highly efficient transformer models for natural language understanding

Young Jin Kim and Hany Hassan. 2020 · 2020

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Pre-training multilingual neural machine translation by leveraging alignment information

Zehui Lin, Xiao Pan, Mingxuan Wang, Xipeng Qiu, Jiangtao Feng, Hao Zhou, and Lei Li. 2020 · 2020

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Prophetnet: Predicting future n-gram for sequence-to-sequence pre-training

Weizhen Qi, Yu Yan, Yeyun Gong, Dayiheng Liu, Nan Duan, Jiusheng Chen, Ruofei Zhang, and Ming Zhou. 2020 · 2020

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Towards making the most of BERT in neural machine translation

Original

Jiacheng Yang, Mingxuan Wang, Hao Zhou, Chengqi Zhao, Weinan Zhang, Yong Yu, and Lei Li. 2020 · 2020

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