Fetching the paper…
Reading the bibliography…
While many parallel corpora are not publicly accessible for data copyright, data privacy and competitive differentiation reasons, trained translation models are increasingly available on open platforms.
BLEU: a method for automatic evaluation of machine translation
Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002 · 2002
Earlier work this paper cites.
Europarl: A parallel corpus for statistical machine translation
Philipp Koehn. 2005 · 2005
Earlier work this paper cites.
Parallel data, tools and interfaces in OPUS
Jörg Tiedemann. 2012 · 2012
Earlier work this paper cites.
Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio. 2014 · 2014
Earlier work this paper cites.
Adam: A method for stochastic optimization
Diederik P Kingma and Jimmy Ba. 2014 · 2014
Earlier work this paper cites.
Distilling the knowledge in a neural network
Geoffrey Hinton, Oriol Vinyals, and Jeff Dean. 2015 · 2015
Earlier work this paper cites.
OpenSubtitles2016: Extracting large parallel corpora from movie and TV subtitles
Pierre Lison and Jörg Tiedemann. 2016 · 2016
Earlier work this paper cites.
Neural machine translation of rare words with subword units
Rico Sennrich, Barry Haddow, and Alexandra Birch. 2016 · 2016
Earlier work this paper cites.
Ensemble distillation for neural machine translation
Markus Freitag, Yaser Al-Onaizan, and Baskaran Sankaran. 2017 · 2017
Earlier work this paper cites.
Efficient knowledge distillation from an ensemble of teachers
Takashi Fukuda, Masayuki Suzuki, Gakuto Kurata, Samuel Thomas, Jia Cui, and Bhuvana Ramabhadran. 2017 · 2017
Earlier work this paper cites.
Overcoming catastrophic forgetting in neural networks
James Kirkpatrick, Razvan Pascanu, Neil Rabinowitz, Joel Veness, Guillaume Desjardins, Andrei A Rusu, Kieran Milan, John Quan, Tiago Ramalho, Agnieszka Grabska-Barwinska, et al. 2017 · 2017
Earlier work this paper cites.
Tilde MODEL - multilingual open data for EU languages
Roberts Rozis and Raivis Skadiņš. 2017 · 2017
Earlier work this paper cites.
Attention is all you need
Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Ł ukasz Kaiser, and Illia Polosukhin. 2017 · 2017
Earlier work this paper cites.
AI challenger : A large-scale dataset for going deeper in image understanding
Jiahong Wu, He Zheng, Bo Zhao, Yixin Li, Baoming Yan, Rui Liang, Wenjia Wang, Shipei Zhou, Guosen Lin, Yanwei Fu, Yizhou Wang, and Yonggang Wang. 2017 · 2017
Cited alongside, same era.
Learning from multiple teacher networks
Shan You, Chang Xu, Chao Xu, and Dacheng Tao. 2017 · 2017
Cited alongside, same era.
Regularized training objective for continued training for domain adaptation in neural machine translation
Huda Khayrallah, Brian Thompson, Kevin Duh, and Philipp Koehn. 2018 · 2018
Cited alongside, same era.
Rapid adaptation of neural machine translation to new languages
Graham Neubig and Junjie Hu. 2018 · 2018
Cited alongside, same era.
Adapting multilingual neural machine translation to unseen languages
Surafel M. Lakew, Alina Karakanta, Marcello Federico, Matteo Negri, and Marco Turchi. 2019 · 2019
Cited alongside, same era.
Continual learning for neural machine translation
Yue Cao, Hao-Ran Wei, Boxing Chen, and Xiaojun Wan. 2021 · 2021
Later among the works it cites.
Towards continual learning for multilingual machine translation via vocabulary substitution
Xavier Garcia, Noah Constant, Ankur Parikh, and Orhan Firat. 2021 · 2021
Later among the works it cites.
Knowledge distillation: A survey
Jianping Gou, Baosheng Yu, Stephen J. Maybank, and Dacheng Tao. 2021 · 2021
Later among the works it cites.
Finding sparse structures for domain specific neural machine translation
Jianze Liang, Chengqi Zhao, Mingxuan Wang, Xipeng Qiu, and Lei Li. 2021 · 2021
Later among the works it cites.
Continual mixed-language pre-training for extremely low-resource neural machine translation
Zihan Liu, Genta Indra Winata, and Pascale Fung. 2021 · 2021
Later among the works it cites.
Communication-efficient federated learning for neural machine translation
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Domain adaptive inference for neural machine translation
Danielle Saunders, Felix Stahlberg, Adrià de Gispert, and Bill Byrne. 2019 · 2019
Cited alongside, same era.
Iterative dual domain adaptation for neural machine translation
Jiali Zeng, Yang Liu, Jinsong Su, Yubing Ge, Yaojie Lu, Yongjing Yin, and Jiebo Luo. 2019 · 2019
Cited alongside, same era.
Lifelong language knowledge distillation
Yung-Sung Chuang, Shang-Yu Su, and Yun-Nung Chen. 2020 · 2020
Cited alongside, same era.
Train no evil: Selective masking for task-guided pre-training
Yuxian Gu, Zhengyan Zhang, Xiaozhi Wang, Zhiyuan Liu, and Maosong Sun. 2020 · 2020
Cited alongside, same era.
Membership inference attacks on sequence-to-sequence models: Is my data in your machine translation system?
Sorami Hisamoto, Matt Post, and Kevin Duh. 2020 · 2020
Cited alongside, same era.
Adaptive multi-teacher multi-level knowledge distillation
Yuang Liu, Wei Zhang, and Jun Wang. 2020 · 2020
Cited alongside, same era.
Improved knowledge distillation via teacher assistant
Seyed Iman Mirzadeh, Mehrdad Farajtabar, Ang Li, Nir Levine, Akihiro Matsukawa, and Hassan Ghasemzadeh. 2020 · 2020
Cited alongside, same era.
Tanya G. Roosta, Peyman Passban, and Ankit Chadha. 2021 · 2021
Later among the works it cites.
Modeling without sharing privacy: Federated neural machine translation
Jianzong Wang, Zhangcheng Huang, Lingwei Kong, Denghao Li, and Jing Xiao. 2021b · 2021
Later among the works it cites.
Towards security threats of deep learning systems: A survey
Yingzhe He, Guozhu Meng, Kai Chen, Xingbo Hu, and Jinwen He. 2022 · 2022
Closest in time.
Entropy-based vocabulary substitution for incremental learning in multilingual neural machine translation
Kaiyu Huang, Peng Li, Jin Ma, and Yang Liu. 2022 · 2022
Closest in time.
Knowledge inheritance for pre-trained language models
Yujia Qin, Yankai Lin, Jing Yi, Jiajie Zhang, Xu Han, Zhengyan Zhang, Yusheng Su, Zhiyuan Liu, Peng Li, Maosong Sun, and Jie Zhou. 2022 · 2022
Closest in time.
Data selection for efficient model update in federated learning
Hongrui Shi and Valentin Radu. 2022 · 2022
Closest in time.
Overcoming catastrophic forgetting during domain adaptation of neural machine translation
Brian Thompson, Jeremy Gwinnup, Huda Khayrallah, Kevin Duh, and Philipp Koehn. 2019 · 2068
Closest in time.