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We introduce and demonstrate how to effectively train multilingual machine translation models with pixel representations.
Visualizing data using t-sne
Laurens van der Maaten and Geoffrey Hinton. 2008 · 2008
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Adam: A method for stochastic optimization
Diederik P. Kingma and Jimmy Ba. 2015 · 2015
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Multilingual language processing from bytes
Dan Gillick, Cliff Brunk, Oriol Vinyals, and Amarnag Subramanya. 2016 · 2016
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Very deep convolutional networks for end-to-end speech recognition
Yu Zhang, William Chan, and Navdeep Jaitly. 2017 · 2017
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Revisiting character-based neural machine translation with capacity and compression
Colin Cherry, George Foster, Ankur Bapna, Orhan Firat, and Wolfgang Macherey. 2018 · 2018
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The multitarget TED talks task
Kevin Duh. 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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SentencePiece: A simple and language independent subword tokenizer and detokenizer for neural text processing
Taku Kudo and John Richardson. 2018 · 2018
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When and why are pre-trained word embeddings useful for neural machine translation?
Ye Qi, Devendra Sachan, Matthieu Felix, Sarguna Padmanabhan, and Graham Neubig. 2018 · 2018
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Massively multilingual neural machine translation
Roee Aharoni, Melvin Johnson, and Orhan Firat. 2019 · 2019
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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 Foster, Colin Cherry, Wolfgang Macherey, Zhifeng Chen, and Yonghui Wu. 2019 · 2019
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Representation degeneration problem in training natural language generation models
Jun Gao, Di He, Xu Tan, Tao Qin, Liwei Wang, and Tieyan Liu. 2019 · 2019
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A universal parent model for low-resource neural machine translation transfer
Mozhdeh Gheini and Jonathan May. 2019 · 2019
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Parameter-efficient transfer learning for NLP
Neil Houlsby, Andrei Giurgiu, Stanislaw Jastrzebski, Bruna Morrone, Quentin De Laroussilhe, Andrea Gesmundo, Mona Attariyan, and Sylvain Gelly. 2019 · 2019
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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
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Language models are unsupervised multitask learners
Alec Radford, Jeff Wu, Rewon Child, David Luan, Dario Amodei, and Ilya Sutskever. 2019 · 2019
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On Romanization for model transfer between scripts in neural machine translation
Chantal Amrhein and Rico Sennrich. 2020 · 2020
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Improving multilingual models with language-clustered vocabularies
Hyung Won Chung, Dan Garrette, Kiat Chuan Tan, and Jason Riesa. 2020 · 2020
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Unsupervised cross-lingual representation learning at scale
Alexis Conneau, Kartikay Khandelwal, Naman Goyal, Vishrav Chaudhary, Guillaume Wenzek, Francisco Guzmán, Edouard Grave, Myle Ott, Luke Zettlemoyer, and Veselin Stoyanov. 2020 · 2020
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Robust open-vocabulary translation from visual text representations
Elizabeth Salesky, David Etter, and Matt Post. 2021 · 2021
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Probing word translations in the transformer and trading decoder for encoder layers
Hongfei Xu, Josef van Genabith, Qiuhui Liu, and Deyi Xiong. 2021 · 2021
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Canine: Pre-training an efficient tokenization-free encoder for language representation
Jonathan H. Clark, Dan Garrette, Iulia Turc, and John Wieting. 2022 · 2022
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Informative language representation learning for massively multilingual neural machine translation
Renren Jin and Deyi Xiong. 2022 · 2022
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No language left behind: Scaling human-centered machine translation
NLLB Team, Marta R. Costa-jussà, James Cross, Onur Çelebi, Maha Elbayad, Kenneth Heafield, Kevin Heffernan, Elahe Kalbassi, Janice Lam, Daniel Licht, Jean Maillard, Anna Sun, Skyler Wang, Guillaume Wenzek, Al Youngblood, Bapi Akula, Loic Barrault, Gabriel Mejia-Gonzalez, Prangthip Hansanti, John Hoffman, Semarley Jarrett, Kaushik Ram Sadagopan, Dirk Rowe, Shannon Spruit, Chau Tran, Pierre Andrews, Necip Fazil Ayan, Shruti Bhosale, Sergey Edunov, Angela Fan, Cynthia Gao, Vedanuj Goswami, Francisco Guzmán, Philipp Koehn, Alexandre Mourachko, Christophe Ropers, Safiyyah Saleem, Holger Schwenk, and Jeff Wang. 2022 · 2022
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MAD-X: An Adapter-Based Framework for Multi-Task Cross-Lingual Transfer
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Efficient inference for multilingual neural machine translation
Alexandre Berard, Dain Lee, Stephane Clinchant, Kweonwoo Jung, and Vassilina Nikoulina. 2021 · 2021
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Beyond english-centric multilingual machine translation
Angela Fan, Shruti Bhosale, Holger Schwenk, Zhiyi Ma, Ahmed El-Kishky, Siddharth Goyal, Mandeep Baines, Onur Celebi, Guillaume Wenzek, Vishrav Chaudhary, Naman Goyal, Tom Birch, Vitaliy Liptchinsky, Sergey Edunov, Edouard Grave, Michael Auli, and Armand Joulin. 2021 · 2021
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Masked autoencoders are scalable vision learners
Kaiming He, Xinlei Chen, Saining Xie, Yanghao Li, Piotr Dollár, and Ross Girshick. 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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Multilingual neural machine translation with deep encoder and multiple shallow decoders
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Alternative input signals ease transfer in multilingual machine translation
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Scale efficiently: Insights from pretraining and finetuning transformers
Yi Tay, Mostafa Dehghani, Jinfeng Rao, William Fedus, Samira Abnar, Hyung Won Chung, Sharan Narang, Dani Yogatama, Ashish Vaswani, and Donald Metzler. 2022 · 2022
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Do all languages cost the same? tokenization in the era of commercial language models
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Romanization-based large-scale adaptation of multilingual language models
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Language modelling with pixels
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