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Word alignment over parallel corpora has a wide variety of applications, including learning translation lexicons, cross-lingual transfer of language processing tools, and automatic evaluation or analysis of translation outputs.
A generalized solution of the orthogonal procrustes problem
Peter H Schönemann. 1966 · 1966
Earlier work this paper cites.
Concerning nonnegative matrices and doubly stochastic matrices
Richard Sinkhorn and Paul Knopp. 1967 · 1967
Earlier work this paper cites.
The mathematics of statistical machine translation: Parameter estimation
Peter F Brown, Stephen A Della Pietra, Vincent J Della Pietra, and Robert L Mercer. 1993 · 1993
Earlier work this paper cites.
Hmm-based word alignment in statistical translation
Stephan Vogel, Hermann Ney, and Christoph Tillmann. 1996 · 1996
Earlier work this paper cites.
Improved statistical alignment models
Franz Josef Och and Hermann Ney. 2000 · 2000
Earlier work this paper cites.
Inducing multilingual text analysis tools via robust projection across aligned corpora
David Yarowsky, Grace Ngai, and Richard Wicentowski. 2001 · 2001
Earlier work this paper cites.
Introduction to the CoNLL-2002 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang. 2002 · 2002
Earlier work this paper cites.
An evaluation exercise for word alignment
Rada Mihalcea and Ted Pedersen. 2003 · 2003
Earlier work this paper cites.
A systematic comparison of various statistical alignment models
Franz Josef Och and Hermann Ney. 2003 · 2003
Earlier work this paper cites.
Introduction to the CoNLL-2003 shared task: Language-independent named entity recognition
Erik F. Tjong Kim Sang and Fien De Meulder. 2003 · 2003
Earlier work this paper cites.
Europarl: A parallel corpus for statistical machine translation
Philipp Koehn. 2005 · 2005
Earlier work this paper cites.
Edinburgh system description for the 2005 iwslt speech translation evaluation
Philipp Koehn, Amittai Axelrod, Alexandra Birch Mayne, Chris Callison-Burch, Miles Osborne, and David Talbot. 2005 · 2005
Earlier work this paper cites.
Optimization of word alignment clues
Jörg Tiedemann. 2005 · 2005
Earlier work this paper cites.
Alignment by agreement
Percy Liang, Ben Taskar, and Dan Klein. 2006 · 2006
Earlier work this paper cites.
AER: Do we need to “improve” our alignments?
David Vilar, Maja Popović, and Hermann Ney. 2006 · 2006
Earlier work this paper cites.
Measuring word alignment quality for statistical machine translation
Alexander Fraser and Daniel Marcu. 2007 · 2007
Earlier work this paper cites.
Parallel implementations of word alignment tool
Qin Gao and Stephan Vogel. 2008 · 2008
Earlier work this paper cites.
A phrase-based alignment model for natural language inference
Bill MacCartney, Michel Galley, and Christopher D Manning. 2008 · 2008
Earlier work this paper cites.
Cross-lingual annotation projection for semantic roles
Sebastian Padó and Mirella Lapata. 2009 · 2009
Earlier work this paper cites.
Empirical lower bounds on translation unit error rate for the full class of inversion transduction grammars
Anders Søgaard and Dekai Wu. 2009 · 2009
Earlier work this paper cites.
Alignment-based profiling of europarl data in an english-swedish parallel corpus
Lars Ahrenberg. 2010 · 2010
Earlier work this paper cites.
The Kyoto free translation task
Graham Neubig. 2011 · 2011
Earlier work this paper cites.
Pointwise prediction for robust, adaptable japanese morphological analysis
Graham Neubig, Yosuke Nakata, and Shinsuke Mori. 2011 · 2011
Earlier work this paper cites.
What types of word alignment improve statistical machine translation?
Patrik Lambert, Simon Petitrenaud, Yanjun Ma, and Andy Way. 2012 · 2012
Earlier work this paper cites.
Sinkhorn distances: Lightspeed computation of optimal transport
Marco Cuturi. 2013 · 2013
Earlier work this paper cites.
A simple, fast, and effective reparameterization of IBM model 2
Chris Dyer, Victor Chahuneau, and Noah A Smith. 2013 · 2013
Earlier work this paper cites.
Estimating word alignment quality for smt reordering tasks
Sara Stymne, Jörg Tiedemann, and Joakim Nivre. 2014 · 2014
Earlier work this paper cites.
Back to basics for monolingual alignment: Exploiting word similarity and contextual evidence
Md Arafat Sultan, Steven Bethard, and Tamara Sumner. 2014 · 2014
Cited alongside, same era.
Recurrent neural networks for word alignment model
Akihiro Tamura, Taro Watanabe, and Eiichiro Sumita. 2014 · 2014
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Rediscovering annotation projection for cross-lingual parser induction
Jörg Tiedemann. 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
Cited alongside, same era.
From word embeddings to document distances
Matt Kusner, Yu Sun, Nicholas Kolkin, and Kilian Weinberger. 2015 · 2015
Cited alongside, same era.
Contrastive unsupervised word alignment with non-local features
BERT: Pre-training of deep bidirectional transformers for language understanding
Jacob Devlin, Ming-Wei Chang, Kenton Lee, and Kristina Toutanova. 2019 · 2019
Later among the works it cites.
Jointly learning to align and translate with transformer models
Sarthak Garg, Stephan Peitz, Udhyakumar Nallasamy, and Matthias Paulik. 2019 · 2019
Later among the works it cites.
Unsupervised alignment of embeddings with wasserstein procrustes
Edouard Grave, Armand Joulin, and Quentin Berthet. 2019 · 2019
Later among the works it cites.
Domain adaptation of neural machine translation by lexicon induction
Junjie Hu, Mengzhou Xia, Graham Neubig, and Jaime G Carbonell. 2019 · 2019
Later among the works it cites.
Cross-lingual language model pretraining
Guillaume Lample and Alexis Conneau. 2019 · 2019
Later among the works it cites.
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Yang Liu and Maosong Sun. 2015 · 2015
Cited alongside, same era.
Effective approaches to attention-based neural machine translation
Minh-Thang Luong, Hieu Pham, and Christopher D Manning. 2015 · 2015
Cited alongside, same era.
Multilingual projection for parsing truly low-resource languages
Željko Agić, Anders Johannsen, Barbara Plank, Héctor Martínez Alonso, Natalie Schluter, and Anders Søgaard. 2016 · 2016
Cited alongside, same era.
Massively multilingual word embeddings
Waleed Ammar, George Mulcaire, Yulia Tsvetkov, Guillaume Lample, Chris Dyer, and Noah A Smith. 2016 · 2016
Cited alongside, same era.
Incorporating discrete translation lexicons into neural machine translation
Philip Arthur, Graham Neubig, and Satoshi Nakamura. 2016 · 2016
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Incorporating structural alignment biases into an attentional neural translation model
Trevor Cohn, Cong Duy Vu Hoang, Ekaterina Vymolova, Kaisheng Yao, Chris Dyer, and Gholamreza Haffari. 2016 · 2016
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Neural network-based word alignment through score aggregation
Joël Legrand, Michael Auli, and Ronan Collobert. 2016 · 2016
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On the word alignment from neural machine translation
Xintong Li, Guanlin Li, Lemao Liu, Max Meng, and Shuming Shi. 2019 · 2019
Later among the works it cites.
How language-neutral is multilingual BERT?
Jindřich Libovickỳ, Rudolf Rosa, and Alexander Fraser. 2019 · 2019
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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 · 2019
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Decoupled weight decay regularization
I. Loshchilov and F. Hutter. 2019 · 2019
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compare-mt: A tool for holistic comparison of language generation systems
Graham Neubig, Zi-Yi Dou, Junjie Hu, Paul Michel, Danish Pruthi, and Xinyi Wang. 2019 · 2019
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Learning morphosyntactic analyzers from the Bible via iterative annotation projection across 26 languages
Garrett Nicolai and David Yarowsky. 2019 · 2019
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Sparse sequence-to-sequence models
Ben Peters, Vlad Niculae, and André FT Martins. 2019 · 2019
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Evaluating gender bias in machine translation
Gabriel Stanovsky, Noah A Smith, and Luke Zettlemoyer. 2019 · 2019
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A discriminative neural model for cross-lingual word alignment
Elias Stengel-Eskin, Tzu-ray Su, Matt Post, and Benjamin Van Durme. 2019 · 2019
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Improving end-to-end speech recognition with pronunciation-assisted sub-word modeling
Hainan Xu, Shuoyang Ding, and Shinji Watanabe. 2019 · 2019
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Adding interpretable attention to neural translation models improves word alignment
Thomas Zenkel, Joern Wuebker, and John DeNero. 2019 · 2019
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Regularizing neural machine translation by target-bidirectional agreement
Zhirui Zhang, Shuangzhi Wu, Shujie Liu, Mu Li, Ming Zhou, and Tong Xu. 2019 · 2019
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Language models are few-shot learners
Tom B. Brown, Benjamin Pickman Mann, Nick Ryder, Melanie Subbiah, Jean Kaplan, Prafulla Dhariwal, Arvind Neelakantan, Pranav Shyam, Girish Sastry, Amanda Askell, Sandhini Agarwal, Ariel Herbert-Voss, G. Krüger, Tom Henighan, Rewon Child, Aditya Ramesh, Daniel M. Ziegler, Jeffrey Wu, Clemens Winter, Christopher Hesse, Mark Chen, Eric J Sigler, Mateusz Litwin, Scott Gray, Benjamin Chess, Jack Clark, Christopher Berner, Sam McCandlish, Alec Radford, Ilya Sutskever, and Dario Amodei. 2020 · 2020
Later among the works it cites.
Accurate word alignment induction from neural machine translation
Yun Chen, Yang Liu, Guanhua Chen, Xin Jiang, and Qun Liu. 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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Don’t stop pretraining: Adapt language models to domains and tasks
Suchin Gururangan, Ana Marasović, Swabha Swayamdipta, Kyle Lo, Iz Beltagy, Doug Downey, and Noah A. Smith. 2020 · 2020
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A supervised word alignment method based on cross-language span prediction using multilingual BERT
Masaaki Nagata, Chousa Katsuki, and Masaaki Nishino. 2020 · 2020
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A retrieve-and-rewrite initialization method for unsupervised machine translation
Shuo Ren, Yu Wu, Shujie Liu, Ming Zhou, and Shuai Ma. 2020 · 2020
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Masoud Jalili Sabet, Philipp Dufter, François Yvon, and Hinrich Schütze. 2020 · 2020
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Rationalizing text matching: Learning sparse alignments via optimal transport
Kyle Swanson, Lili Yu, and Tao Lei. 2020 · 2020
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On the inference calibration of neural machine translation
Shuo Wang, Zhaopeng Tu, Shuming Shi, and Yang Liu. 2020 · 2020
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End-to-end neural word alignment outperforms GIZA++
Thomas Zenkel, Joern Wuebker, and John DeNero. 2020 · 2020
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