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Autoregressive decoding limits the efficiency of transformers for Machine Translation (MT).
Roberta: A robustly optimized bert pretraining approach
Yinhan Liu, Myle Ott, Naman Goyal, Jingfei Du, Mandar Joshi, Danqi Chen, Omer Levy, Mike Lewis, Luke Zettlemoyer, and Veselin Stoyanov. 2019 · 1907
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Iterative Solution of Nonlinear Equations in Several Variables
J.M. Ortega and W.C. Rheinboldt. 1970 · 1970
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Speech understanding systems: A summary of results of the five-year research effort
Raj Reddy. 1977 · 1977
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Semi-autoregressive training improves mask-predict decoding
Marjan Ghazvininejad, Omer Levy, and Luke Zettlemoyer. 2020b · 2001
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Bleu: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
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Glancing transformer for non-autoregressive neural machine translation
Lihua Qian, Hao Zhou, Yu Bao, Mingxuan Wang, Lin Qiu, Weinan Zhang, Yong Yu, and Lei Li. 2021 · 2003
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Iterative methods for sparse linear systems
Yousef Saad. 2003 · 2003
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Very deep transformers for neural machine translation
Xiaodong Liu, Kevin Duh, Liyuan Liu, and Jianfeng Gao. 2020 · 2008
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Multilingual translation with extensible multilingual pretraining and finetuning
Yuqing Tang, Chau Tran, Xian Li, Peng-Jen Chen, Naman Goyal, Vishrav Chaudhary, Jiatao Gu, and Angela Fan. 2020 · 2008
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Japanese and korean voice search
Mike Schuster and Kaisuke Nakajima. 2012 · 2012
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Findings of the 2014 workshop on statistical machine translation
Ondřej Bojar, Christian Buck, Christian Federmann, Barry Haddow, Philipp Koehn, Johannes Leveling, Christof Monz, Pavel Pecina, Matt Post, Herve Saint-Amand, Radu Soricut, Lucia Specia, and Aleš Tamchyna. 2014 · 2014
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Sequence to sequence learning with neural networks
Ilya Sutskever, Oriol Vinyals, and Quoc V Le. 2014 · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2015 · 2015
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The English-Vietnamese machine translation system for IWSLT 2015
Viet Hong Tran, Huyen Vu Thong, Nguyen Van-Vinh, and Trung Le Tien. 2015 · 2015
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Findings of the 2016 conference on machine translation
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Varvara Logacheva, Christof Monz, Matteo Negri, Aurelie Neveol, Mariana Neves, Martin Popel, Matt Post, Raphael Rubino, Carolina Scarton, Lucia Specia, Marco Turchi, Karin Verspoor, and Marcos Zampieri. 2016 · 2016
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Sequence-level knowledge distillation
Yoon Kim and Alexander M. Rush. 2016 · 2016
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Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
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Google’s neural machine translation system: Bridging the gap between human and machine translation
Yonghui Wu, Mike Schuster, Zhifeng Chen, Quoc V Le, Mohammad Norouzi, Wolfgang Macherey, Maxim Krikun, Yuan Cao, Qin Gao, Klaus Macherey, et al. 2016 · 2016
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Findings of the 2017 conference on machine translation (wmt17)
Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Yvette Graham, Barry Haddow, Shujian Huang, Matthias Huck, Philipp Koehn, Qun Liu, Varvara Logacheva, Christof Monz, Matteo Negri, Matt Post, Raphael Rubino, Lucia Specia, and Marco Turchi. 2017 · 2017
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Fast generation for convolutional autoregressive models
Prajit Ramachandran, Tom Le Paine, Pooya Khorrami, Mohammad Babaeizadeh, Shiyu Chang, Yang Zhang, Mark A. Hasegawa-Johnson, Roy H. Campbell, and Thomas S. Huang. 2017 · 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 · 2017
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Understanding back-translation at scale
Sergey Edunov, Myle Ott, Michael Auli, and David Grangier. 2018 · 2018
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Non-autoregressive neural machine translation
Jiatao Gu, James Bradbury, Caiming Xiong, Victor O.K. Li, and Richard Socher. 2018 · 2018
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Subword regularization: Improving neural network translation models with multiple subword candidates
Taku Kudo. 2018 · 2018
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Taku Kudo and John Richardson. 2018 · 2018
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The IIT Bombay English-Hindi parallel corpus
Anoop Kunchukuttan, Pratik Mehta, and Pushpak Bhattacharyya. 2018 · 2018
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A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
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Blockwise parallel decoding for deep autoregressive models
Learning to rewrite for non-autoregressive neural machine translation
Xinwei Geng, Xiaocheng Feng, and Bing Qin. 2021 · 2021
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Fully non-autoregressive neural machine translation: Tricks of the trade
Jiatao Gu and Xiang Kong. 2021 · 2021
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Multi-task learning with shared encoder for non-autoregressive machine translation
Yongchang Hao, Shilin He, Wenxiang Jiao, Zhaopeng Tu, Michael Lyu, and Xing Wang. 2021 · 2021
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Non-autoregressive translation with layer-wise prediction and deep supervision
Chenyang Huang, Hao Zhou, Osmar R. Zaïane, Lili Mou, and Lei Li. 2021 · 2021
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Deep encoder, shallow decoder: Reevaluating non-autoregressive machine translation
Jungo Kasai, Nikolaos Pappas, Hao Peng, James Cross, and Noah Smith. 2021 · 2021
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Mitchell Stern, Noam Shazeer, and Jakob Uszkoreit. 2018 · 2018
Cited alongside, same era.
Semi-autoregressive neural machine translation
Chunqi Wang, Ji Zhang, and Haiqing Chen. 2018 · 2018
Cited alongside, same era.
Bias and fairness in natural language processing
Kai-Wei Chang, Vinodkumar Prabhakaran, and Vicente Ordonez. 2019 · 2019
Cited alongside, same era.
Mask-predict: Parallel decoding of conditional masked language models
Marjan Ghazvininejad, Omer Levy, Yinhan Liu, and Luke Zettlemoyer. 2019 · 2019
Cited alongside, same era.
From research to production and back: Ludicrously fast neural machine translation
Young Jin Kim, Marcin Junczys-Dowmunt, Hany Hassan, Alham Fikri Aji, Kenneth Heafield, Roman Grundkiewicz, and Nikolay Bogoychev. 2019 · 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, Alban Desmaison, Andreas Kopf, Edward Yang, Zachary DeVito, Martin Raison, Alykhan Tejani, Sasank Chilamkurthy, Benoit Steiner, Lu Fang, Junjie Bai, and Soumith Chintala. 2019 · 2019
Cited alongside, same era.
Energy and policy considerations for deep learning in NLP
Emma Strubell, Ananya Ganesh, and Andrew McCallum. 2019 · 2019
Cited alongside, same era.
Quentin Lhoest, Albert Villanova del Moral, Yacine Jernite, Abhishek Thakur, Patrick von Platen, Suraj Patil, Julien Chaumond, Mariama Drame, Julien Plu, Lewis Tunstall, Joe Davison, Mario Šaško, Gunjan Chhablani, Bhavitvya Malik, Simon Brandeis, Teven Le Scao, Victor Sanh, Canwen Xu, Nicolas Patry, Angelina McMillan-Major, Philipp Schmid, Sylvain Gugger, Clément Delangue, Théo Matussière, Lysandre Debut, Stas Bekman, Pierric Cistac, Thibault Goehringer, Victor Mustar, François Lagunas, Alexander Rush, and Thomas Wolf. 2021 · 2021
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Gender Bias in Machine Translation
Beatrice Savoldi, Marco Gaido, Luisa Bentivogli, Matteo Negri, and Marco Turchi. 2021 · 2021
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AligNART: Non-autoregressive neural machine translation by jointly learning to estimate alignment and translate
Jongyoon Song, Sungwon Kim, and Sungroh Yoon. 2021a · 2021
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Instantaneous grammatical error correction with shallow aggressive decoding
Xin Sun, Tao Ge, Furu Wei, and Houfeng Wang. 2021 · 2021
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Answer fast: Accelerating bert on the tensor streaming processor
Ibrahim Ahmed, Sahil Parmar, Matthew Boyd, Michael Beidler, Kris Kang, Bill Liu, Kyle Roach, John Kim, and Dennis Abts. 2022 · 2022
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The Flores-101 evaluation benchmark for low-resource and multilingual machine translation
Naman Goyal, Cynthia Gao, Vishrav Chaudhary, Peng-Jen Chen, Guillaume Wenzek, Da Ju, Sanjana Krishnan, Marc’Aurelio Ranzato, Francisco Guzmán, and Angela Fan. 2022 · 2022
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Improving non-autoregressive translation models without distillation
Xiao Shi Huang, Felipe Perez, and Maksims Volkovs. 2022 · 2022
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Fast inference from transformers via speculative decoding
Yaniv Leviathan, Matan Kalman, and Yossi Matias. 2022 · 2022
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Step-unrolled denoising autoencoders for text generation
Nikolay Savinov, Junyoung Chung, Mikolaj Binkowski, Erich Elsen, and Aaron van den Oord. 2022 · 2022
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switch-GLAT: Multilingual parallel machine translation via code-switch decoder
Zhenqiao Song, Hao Zhou, Lihua Qian, Jingjing Xu, Shanbo Cheng, Mingxuan Wang, and Lei Li. 2022 · 2022
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Lossless speedup of autoregressive translation with generalized aggressive decoding
Heming Xia, Tao Ge, Furu Wei, and Zhifang Sui. 2022 · 2022
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A survey on non-autoregressive generation for neural machine translation and beyond
Yisheng Xiao, Lijun Wu, Junliang Guo, Juntao Li, Min Zhang, Tao Qin, and Tie-yan Liu. 2022 · 2022
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Accelerating large language model decoding with speculative sampling
Charlie Chen, Sebastian Borgeaud, Geoffrey Irving, Jean-Baptiste Lespiau, Laurent Sifre, and John Jumper. 2023 · 2023
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Big little transformer decoder
Sehoon Kim, Karttikeya Mangalam, Jitendra Malik, Michael W. Mahoney, Amir Gholami, and Kurt Keutzer. 2023 · 2023
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Latent autoregressive source separation
Emilian Postolache, Giorgio Mariani, Michele Mancusi, Andrea Santilli, Cosmo Luca, Emanuele Rodola, et al. 2023 · 2023
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High-throughput generative inference of large language models with a single gpu
Ying Sheng, Lianmin Zheng, Binhang Yuan, Zhuohan Li, Max Ryabinin, Daniel Y Fu, Zhiqiang Xie, Beidi Chen, Clark Barrett, Joseph E Gonzalez, et al. 2023 · 2023
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