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Document-level neural machine translation (DNMT) has shown promising results by incorporating more context information.
Massively multilingual neural machine translation in the wild: Findings and challenges
Naveen Arivazhagan, Ankur Bapna, Orhan Firat, Dmitry Lepikhin, Melvin Johnson, Maxim Krikun, Mia Xu Chen, Yuan Cao, George F. Foster, Colin Cherry, Wolfgang Macherey, Zhifeng Chen, and Yonghui Wu. 2019 · 1907
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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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Longformer: The Long-Document Transformer
Iz Beltagy, Matthew E. Peters, and Arman Cohan. 2020 · 2004
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Europarl: A Parallel Corpus for Statistical Machine Translation
Philipp Koehn. 2005 · 2005
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Moses: Open source toolkit for statistical machine translation
Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan Herbst. 2007 · 2007
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Cache-based document-level statistical machine translation
Zhengxian Gong, Min Zhang, and Guodong Zhou. 2011 · 2011
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WIT3: Web Inventory of Transcribed and Translated Talks
Mauro Cettolo, Christian Girardi, and Marcello Federico. 2012 · 2012
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Docent: A document-level decoder for phrase-based statistical machine translation
Christian Hardmeier, Sara Stymne, Jörg Tiedemann, and Joakim Nivre. 2013 · 2013
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Document-level machine translation with word vector models
Eva Martínez Garcia, Cristina España-Bonet, and Lluís Màrquez. 2015 · 2015
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chrF: character n-gram F-score for automatic MT evaluation
Maja Popović. 2015 · 2015
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Rethinking the Inception Architecture for Computer Vision
Christian Szegedy, Vincent Vanhoucke, Sergey Ioffe, Jonathon Shlens, and Zbigniew Wojna. 2015 · 2015
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Opensubtitles2016: Extracting large parallel corpora from movie and tv subtitles
Pierre Lison and Jörg Tiedemann. 2016 · 2016
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From Softmax to Sparsemax: A Sparse Model of Attention and Multi-Label Classification
André F. T. Martins and Ramón Fernandez Astudillo. 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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Does Neural Machine Translation Benefit from Larger Context?
Sebastien Jean, Stanislas Lauly, Orhan Firat, and Kyunghyun Cho. 2017 · 2017
Cited alongside, same era.
Adam: A Method for Stochastic Optimization
Diederik P. Kingma and Jimmy Ba. 2017 · 2017
Cited alongside, same era.
Neural machine translation with extended context
Jörg Tiedemann and Yves Scherrer. 2017 · 2017
Cited alongside, same era.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N. Gomez, Lukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Cited alongside, same era.
Exploiting Cross-Sentence Context for Neural Machine Translation
Longyue Wang, Zhaopeng Tu, Andy Way, and Qun Liu. 2017 · 2017
Cited alongside, same era.
Multilingual denoising pre-training for neural machine translation
Yinhan Liu, Jiatao Gu, Naman Goyal, Xian Li, Sergey Edunov, Marjan Ghazvininejad, Mike Lewis, and Luke Zettlemoyer. 2020 · 2020
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A Simple and Effective Unified Encoder for Document-Level Machine Translation
Shuming Ma, Dongdong Zhang, and Ming Zhou. 2020 · 2020
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Efficient context-aware neural machine translation with layer-wise weighting and input-aware gating
Hongfei Xu, Deyi Xiong, Josef van Genabith, and Qiuhui Liu. 2020 · 2020
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Improving context-aware neural machine translation using self-attentive sentence embedding
Hyeongu Yun, Yongkeun Hwang, and Kyomin Jung. 2020 · 2020
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Towards making the most of context in neural machine translation
Zaixiang Zheng, Xiang Yue, Shujian Huang, Jiajun Chen, and Alexandra Birch. 2020 · 2020
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Fusing Recency into Neural Machine Translation with an Inter-Sentence Gate Model
Shaohui Kuang and Deyi Xiong. 2018 · 2018
Cited alongside, same era.
Document-level neural machine translation with hierarchical attention networks
Lesly Miculicich, Dhananjay Ram, Nikolaos Pappas, and James Henderson. 2018 · 2018
Cited alongside, same era.
A Large-Scale Test Set for the Evaluation of Context-Aware Pronoun Translation in Neural Machine Translation
Mathias Müller, Annette Rios, Elena Voita, and Rico Sennrich. 2018 · 2018
Cited alongside, same era.
A call for clarity in reporting BLEU scores
Matt Post. 2018 · 2018
Cited alongside, same era.
Improving the transformer translation model with document-level context
Jiacheng Zhang, Huanbo Luan, Maosong Sun, Feifei Zhai, Jingfang Xu, Min Zhang, and Yang Liu. 2018 · 2018
Cited alongside, same era.
Microsoft translator at WMT 2019: Towards large-scale document-level neural machine translation
Marcin Junczys-Dowmunt. 2019 · 2019
Cited alongside, same era.
Selective attention for context-aware neural machine translation
Sameen Maruf, André F. T. Martins, and Gholamreza Haffari. 2019 · 2019
Cited alongside, same era.
G-transformer for document-level machine translation
Guangsheng Bao, Yue Zhang, Zhiyang Teng, Boxing Chen, and Weihua Luo. 2021 · 2021
Later among the works it cites.
Breaking the Corpus Bottleneck for Context-Aware Neural Machine Translation with Cross-Task Pre-training
Linqing Chen, Junhui Li, Zhengxian Gong, Boxing Chen, Weihua Luo, Min Zhang, and Guodong Zhou. 2021 · 2021
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A survey on document-level neural machine translation: Methods and evaluation
Sameen Maruf, Fahimeh Saleh, and Gholamreza Haffari. 2021 · 2021
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Train short, test long: Attention with linear biases enables input length extrapolation
Ofir Press, Noah A Smith, and Mike Lewis. 2021 · 2021
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Kerple: Kernelized relative positional embedding for length extrapolation
Ta-Chung Chi, Ting-Han Fan, Peter J Ramadge, and Alexander Rudnicky. 2022 · 2022
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Overcoming a Theoretical Limitation of Self-Attention
David Chiang and Peter Cholak. 2022 · 2022
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Divide and Rule: Effective Pre-Training for Context-Aware Multi-Encoder Translation Models
Lorenzo Lupo, Marco Dinarelli, and Laurent Besacier. 2022 · 2022
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Rethinking document-level neural machine translation
Zewei Sun, Mingxuan Wang, Hao Zhou, Chengqi Zhao, Shujian Huang, Jiajun Chen, and Lei Li. 2022b · 2022
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Randomized positional encodings boost length generalization of transformers
Anian Ruoss, Grégoire Delétang, Tim Genewein, Jordi Grau-Moya, Róbert Csordás, Mehdi Bennani, Shane Legg, and Joel Veness. 2023 · 2023
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