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Active learning can play an important role in low-resource settings (i.e., where annotated data is scarce), by selecting which instances may be more worthy to annotate.
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Online Choice of Active Learning Algorithms
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Low Cost Portability for Statistical Machine Translation based on N-gram Frequency and TF-IDF
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Language model adaptation for statistical machine translation based on information retrieval
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Balancing exploration and exploitation: A new algorithm for active machine learning
Osugi, Thomas, Deng Kun, and Stephen Scott. 2005 · 2005
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Prediction, Learning and Games
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Developing Deployable Spoken Language Translation Systems given Limited Resources
Eck, Matthias. 2008 · 2008
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Efficient data selection for machine translation
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An analysis of active learning strategies for sequence labeling tasks
Settles, Burr and Mark Craven. 2008 · 2008
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Active learning for statistical phrase-based machine translation
Haffari, Gholamreza, Maxim Roy, and Anoop Sarkar. 2009 · 2009
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A semi-supervised batch-mode active learning strategy for improved statistical machine translation
Ananthakrishnan, Sankaranarayanan, Rohit Prasad, David Stallard, and Prem Natarajan. 2010 · 2010
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EGAL: Exploration Guided Active Learning for TCBR
Hu, Rong, Sarah Jane Delany, and Brian Mac Namee. 2010 · 2010
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Stream-based translation models for statistical machine translation
Levenberg, Abby, Chris Callison-Burch, and Miles Osborne. 2010 · 2010
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Active Learning Literature Survey
Settles, Burr. 2010 · 2010
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Multi-Strategy Approaches to Active Learning for Statistical Machine Translation
Ambati, Vamshi, Stephan Vogel, and Jaime Carbonell. 2011 · 2011
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An active learning scenario for interactive machine translation
González-Rubio, Jesús, Daniel Ortiz-Martínez, and Francisco Casacuberta. 2011 · 2011
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Active Learning and Crowd-Sourcing for Machine Translation in Low Resource Scenarios
Ambati, Vamshi. 2012 · 2012
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Active learning for interactive machine translation
González-Rubio, Jesús, Daniel Ortiz-Martínez, and Francisco Casacuberta. 2012 · 2012
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Online Learning Approaches in Computer Assisted Translation
Mathur, Prashant, Mauro Cettolo, and Marcello Federico. 2013 · 2013
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Learning from post-editing: Online model adaptation for statistical machine translation
Denkowski, Michael, Chris Dyer, and Alon Lavie. 2014 · 2014
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Cost-sensitive active learning for computer-assisted translation
González-Rubio, Jesús and Francisco Casacuberta. 2014 · 2014
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A quality-based active sample selection strategy for statistical machine translation
ParaNMT-50M: Pushing the Limits of Paraphrastic Sentence Embeddings with Millions of Machine Translations
Wieting, John and Kevin Gimpel. 2018 · 2018
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bert-as-service
Xiao, Han. 2018 · 2018
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Active Learning for Neural Machine Translation
Zhang, Pei, Xueying Xu, and Deyi Xiong. 2018 · 2018
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Findings of the 2019 Conference on Machine Translation (WMT19)
Barrault, Loïc, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Philipp Koehn, Shervin Malmasi, Christof Monz, Mathias Müller, Santanu Pal, Matt Post, and Marcos Zampieri. 2019 · 2019
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The University of Edinburgh’s Submissions to the WMT19 News Translation Task
Bawden, Rachel, Nikolay Bogoychev, Ulrich Germann, Roman Grundkiewicz, Faheem Kirefu, Antonio Valerio Miceli Barone, and Alexandra Birch. 2019 · 2019
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Logacheva, Varvara and Lucia Specia. 2014 · 2014
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Multidimensional quality metrics (MQM): A framework for declaring and describing translation quality metrics
Lommel, Arle, Aljoscha Burchardt, and Hans Uszkoreit. 2014 · 2014
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Survey of data-selection methods in statistical machine translation
Eetemadi, Sauleh, William Lewis, Kristina Toutanova, and Hayder Radha. 2015 · 2015
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Active learning by learning
Hsu, Wei-Ning and Hsuan-Tien Lin. 2015 · 2015
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chrF: character n-gram F-score for automatic MT evaluation
Popović, Maja. 2015 · 2015
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Can Active Learning Experience Be Transferred?
Chu, Hong-Min and Hsuan-Tien Lin. 2016 · 2016
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Online Learning for Statistical Machine Translation
Ortiz-Martínez, Daniel. 2016 · 2016
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Bei, Chao, Hao Zong, Conghu Yuan, Qingming Liu, and Baoyong Fan. 2019 · 2019
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LIUM’s Contributions to the WMT2019 News Translation Task: Data and Systems for German-French Language Pairs
Bougares, Fethi, Jane Wottawa, Anne Baillot, Loïc Barrault, and Adrien Bardet. 2019 · 2019
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NICT’s Supervised Neural Machine Translation Systems for the WMT19 News Translation Task
Dabre, Raj, Kehai Chen, Benjamin Marie, Rui Wang, Atsushi Fujita, Masao Utiyama, and Eiichiro Sumita. 2019 · 2019
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Microsoft Translator at WMT 2019: Towards Large-Scale Document-Level Neural Machine Translation
Junczys-Dowmunt, Marcin. 2019 · 2019
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The NiuTrans Machine Translation Systems for WMT19
Li, Bei, Yinqiao Li, Chen Xu, Ye Lin, Jiqiang Liu, Hui Liu, Ziyang Wang, Yuhao Zhang, Nuo Xu, Zeyang Wang, Kai Feng, Hexuan Chen, Tengbo Liu, Yanyang Li, Qiang Wang, Tong Xiao, and Jingbo Zhu. 2019 · 2019
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Practical Obstacles to Deploying Active Learning
Lowell, David, Zachary C. Lipton, and Byron C. Wallace. 2019 · 2019
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Facebook FAIR’s WMT19 News Translation Task Submission
Ng, Nathan, Kyra Yee, Alexei Baevski, Myle Ott, Michael Auli, and Sergey Edunov. 2019 · 2019
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eTranslation’s Submissions to the WMT 2019 News Translation Task
Oravecz, Csaba, Katina Bontcheva, Adrien Lardilleux, László Tihanyi, and Andreas Eisele. 2019 · 2019
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Online learning for effort reduction in interactive neural machine translation
Peris, Álvaro and Francisco Casacuberta. 2019 · 2019
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Tilde’s Machine Translation Systems for WMT 2019
Pinnis, Marcis, Rihards Krišlauks, and Matīss Rikters. 2019 · 2019
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Learning How to Active Learn by Dreaming
Vu, Thuy-Trang, Ming Liu, Dinh Phung, and Gholamreza Haffari. 2019 · 2019
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Microsoft Research Asia’s Systems for WMT19
Xia, Yingce, Xu Tan, Fei Tian, Fei Gao, Weicong Chen, Yang Fan, Linyuan Gong, Yichong Leng, Renqian Luo, Yiren Wang, Lijun Wu, Jinhua Zhu, Tao Qin, and Tie-Yan Liu. 2019 · 2019
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Empirical Evaluation of Active Learning Techniques for Neural MT
Zeng, Xiangkai, Sarthak Garg, Rajen Chatterjee, Udhyakumar Nallasamy, and Matthias Paulik. 2019 · 2019
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Findings of the 2020 conference on machine translation (WMT20)
Barrault, Loïc, Magdalena Biesialska, Ondřej Bojar, Marta R. Costa-jussà, Christian Federmann, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Matthias Huck, Eric Joanis, Tom Kocmi, Philipp Koehn, Chi-kiu Lo, Nikola Ljubešić, Christof Monz, Makoto Morishita, Masaaki Nagata, Toshiaki Nakazawa, Santanu Pal, Matt Post, and Marcos Zampieri. 2020 · 2020
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Human-assisted Neural Machine Translation: Harnessing Human Feedback for Machine Translation
Finkelstein, Paige. 2020 · 2020
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Query Strategies, Assemble! Active Learning with Expert Advice for Low-resource Natural Language Processing
Mendonça, Vânia, Luisa Coheur, Alberto Sardinha, and Ana Lúcia Santos. 2020 · 2020
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Machine Translation System Selection from Bandit Feedback
Naradowsky, Jason, Xuan Zhang, and Kevin Duh. 2020 · 2020
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COMET: A neural framework for MT evaluation
Rei, Ricardo, Craig Stewart, Ana C. Farinha, and Alon Lavie. 2020 · 2020
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Automatic Machine Translation Evaluation in Many Languages via Zero-Shot Paraphrasing
Thompson, Brian and Matt Post. 2020 · 2020
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Findings of the 2021 conference on machine translation (WMT21)
Akhbardeh, Farhad, Arkady Arkhangorodsky, Magdalena Biesialska, Ondřej Bojar, Rajen Chatterjee, Vishrav Chaudhary, Marta R. Costa-jussa, Cristina España-Bonet, Angela Fan, Christian Federmann, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Barry Haddow, Leonie Harter, Kenneth Heafield, Christopher Homan, Matthias Huck, Kwabena Amponsah-Kaakyire, Jungo Kasai, Daniel Khashabi, Kevin Knight, Tom Kocmi, Philipp Koehn, Nicholas Lourie, Christof Monz, Makoto Morishita, Masaaki Nagata, Ajay Nagesh, Toshiaki Nakazawa, Matteo Negri, Santanu Pal, Allahsera Auguste Tapo, Marco Turchi, Valentin Vydrin, and Marcos Zampieri. 2021 · 2021
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Active 2 Learning: Actively reducing redundancies in Active Learning methods for Sequence Tagging and Machine Translation
Hazra, Rishi, Parag Dutta, Shubham Gupta, Mohammed Abdul Qaathir, and Ambedkar Dukkipati. in press · 2021
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Online Learning Meets Machine Translation Evaluation: Finding the Best Systems with the Least Human Effort
Mendonça, Vânia, Ricardo Rei, Luisa Coheur, Alberto Sardinha, and Ana Lúcia Santos. 2021 · 2021
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