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The advantages of neural machine translation (NMT) have been extensively validated for offline translation of several language pairs for different domains of spoken and written language.
Srivastava N, Hinton G, Krizhevsky A, Sutskever I, Salakhutdinov R (2014) Dropout: A simple way to prevent neural networks from overfitting. J Mach Learn Res 15(1):1929–1958
1958
Earlier work this paper cites.
Hochreiter S, Schmidhuber J (1997) Long short-term memory. Neural computation 9(8):1735–1780
1997
Earlier work this paper cites.
Papineni K, Roukos S, Ward T, Zhu WJ (2002) Bleu: A method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics (ACL), Stroudsburg, PA
2002
Earlier work this paper cites.
Nepveu L, Lapalme G, Langlais P, Foster G (2004) Adaptive language and translation models for interactive machine translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Barcelona, Spain
2004
Earlier work this paper cites.
Snover M, Dorr B, Schwartz R, Micciulla L, Makhoul J (2006) A study of translation edit rate with targeted human annotation. In: Proceedings of the Conference of the Association for Machine Translation in the Americas (AMTA), Cambridge, MA
2006
Earlier work this paper cites.
Baayen RH, Davidson DJ, Bates DM (2008) Mixed-effects modeling with crossed random effects for subjects and items. Journal of memory and language 59(4):390–412
2008
Earlier work this paper cites.
Cesa-Bianchi N, Reverberi G, Szedmak S (2008) Online learning algorithms for computer-assisted translation. Tech. rep., SMART
2008
Earlier work this paper cites.
Barrachina S, Bender O, Casacuberta F, Civera J, Cubel E, Khadivi S, Lagarda A, Ney H, Tomás J, Vidal E, et al (2009) Statistical approaches to computer-assisted translation. Computational Linguistics 35(1):3–28
2009
Earlier work this paper cites.
Hardt D, Elming J (2010) Incremental re-training for post-editing SMT. In: Proceedings of the Conference of the Association for Machine Tranlation in the Americas (AMTA), Denver, CO
2010
Earlier work this paper cites.
Ortiz-Martínez D, García-Varea I, Casacuberta F (2010) Online learning for interactive statistical machine translation. In: Proceedings of the Human Language Technologies conference and the Annual Conference of the North American Chapter of the Association for Computational Linguistics (HLT-NAACL), Los Angeles, CA
2010
Earlier work this paper cites.
López-Salcedo FJ, Sanchis-Trilles G, Casacuberta F (2012) Online learning of log-linear weights in interactive machine translation. In: Proceedings of IberSpeech, Madrid, Spain
2012
Earlier work this paper cites.
Martínez-Gómez P, Sanchis-Trilles G, Casacuberta F (2012) Online adaptation strategies for statistical machine translation in post-editing scenarios. Pattern Recognition 45(9):3193–3202
2012
Earlier work this paper cites.
Nakov P, Guzman F, Vogel S (2012) Optimizing for sentence-level BLEU+1 yields short translations. In: Proceedings of the Conference on Computational Linguistics (COLING), Mumbai, India
2012
Earlier work this paper cites.
Barr DJ, Levy R, Scheepers C, Tilly HJ (2013) Random effects structure for confirmatory hypothesis testing: Keep it maximal. Journal of Memory and Language 68(3):255–278
2013
Earlier work this paper cites.
Green S, Heer J, Manning CD (2013) The efficacy of human post-editing for language translation. In: Proceedings of the SIGCHI conference on human factors in computing systems, ACM
2013
Earlier work this paper cites.
Bertoldi N, Simianer P, Cettolo M, Wäschle K, Federico M, Riezler S (2014) Online adaptation to post-edits for phrase-based statistical machine translation. Machine Translation 29:309–339
2014
Earlier work this paper cites.
Green S, Wang S, Chuang J, Heer J, Schuster S, Manning CD (2014) Human effort and machine learnability in computer aided translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Doha, Qatar
2014
Cited alongside, same era.
R Core Team (2014) R: A Language and Environment for Statistical Computing. R Foundation for Statistical Computing, Vienna, Austria
2014
Cited alongside, same era.
Bahdanau D, Cho K, Bengio Y (2015) Neural machine translation by jointly learning to align and translate. In: Proceedings of the International Conference on Learning Representations (ICLR), San Diego, CA
2015
Cited alongside, same era.
Bates D, Mächler M, Bolker B, Walker S (2015) Fitting linear mixed-effects models using lme4. Journal of Statistical Software 67(1):1–48
2015
Cited alongside, same era.
Forcada ML (2017) Making sense of neural machine translation. Translation Spaces 6(2):291–309
2017
Closest in time.
Isabelle P, Cherry C, Foster G (2017) A challenge set approach to evaluating machine translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP)
2017
Closest in time.
Klubička F, Toral A, Sánchez-Cartagena VM (2017) Fine-grained human evaluation of neural versus phrase-based machine translation. The Prague Bulletin of Mathematical Linguistics 108(1):121–132
2017
Closest in time.
Koehn P, Knowles R (2017) Six challenges for neural machine translation. In: Proceedings of the First Workshop on Neural Machine Translation
2017
Closest in time.
Kreutzer J, Sokolov A, Riezler S (2017) Bandit structured prediction for neural sequence-to-sequence learning. In: Proceedings of the 55th Annual Meeting of the Association for Computational Linguistics (ACL), Vancouver, Canada
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Jean S, Firat O, Cho K, Memisevic R, Bengio Y (2015) Montreal neural machine translation systems for WMT’15. In: Proceedings of the Workshop on Statistical Machine Translation (WMT), Lisbon, Portugal
2015
Cited alongside, same era.
Kingma DP, Ba J (2015) Adam: A method for stochastic optimization. In: Proceedings of the International Conference on Learning Representations (ICLR), San Diego, CA
2015
Cited alongside, same era.
Luong M, Manning CD (2015) Stanford neural machine translation systems for spoken language domains. In: Proceedings of the International Workshop on Spoken Language Translation (IWSLT), Da Nang, Vietnam
2015
Cited alongside, same era.
Luong M, Pham H, Manning CD (2015) Effective approaches to attention-based neural machine translation. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Lisbon, Portugal
2015
Cited alongside, same era.
Neubig G (2015) lamtram: A toolkit for language and translation modeling using neural networks. http://www.github.com/neubig/lamtram
2015
Cited alongside, same era.
Graham Y, Baldwin T, Moffat A, Zobel J (2016) Can machine translation systems be evaluated by the crowd alone? Natural Language Engineering 23(1):3–30
2016
Cited alongside, same era.
2016
Cited alongside, same era.
Knowles R, Koehn P (2016) Neural interactive translation prediction. In: Proceedings of the Conference of the Association for Machine Translation in the Americas (AMTA), Austin, TX
2016
Cited alongside, same era.
2017
Closest in time.
Macketanz V, Avramidis E, Burchardt A, Helcl J, Srivastava A (2017) Machine translation: Phrase-based, rule-based and neural approaches with linguistic evaluation. Cybernetics and Information Technologies 17(2):28–43
2017
Closest in time.
2017
Closest in time.
Nguyen K, Daumé H, Boyd-Graber J (2017) Reinforcement learning for bandit neural machine translation with simulated feedback. In: Proceedings of the Conference on Empirical Methods in Natural Language Processing (EMNLP), Copenhagen, Denmark
2017
Closest in time.
Peris Á, Domingo M, Casacuberta F (2017) Interactive neural machine translation. Computer Speech & Language 45:201–220
2017
Closest in time.
Popović M (2017) Comparing language related issues for NMT and PBMT between german and english. The Prague Bulletin of Mathematical Linguistics 108(1):209–220
2017
Closest in time.
Shterionov D, Casanellas PNL, Superbo R, O’Dowd T (2017) Empirical evaluation of NMT and PBSMT quality for large-scale translation production. In: Proceedings of the Annual Conference of the European Association for Machine Translation (EAMT): User Track
2017
Closest in time.
Toral A, Sánchez-Cartagena VM (2017) A multifaceted evaluation of neural versus phrase-based machine translation for 9 language directions. In: Proceedings of the Conference of the European Chapter of the Association for Computational Linguistics (EACL)
2017
Closest in time.
Turchi M, Negri M, Farajian MA, Federico M (2017) Continuous learning from human post-edits for neural machine translation. The Prague Bulletin of Mathematical Linguistics 108(1):233–244
2017
Closest in time.
Bentivogli L, Bisazza A, Cettolo M, Federico M (2018) Neural versus phrase-based MT quality: An in-depth analysis on English–German and English–French. Computer Speech & Language 49:52–70
2018
Closest in time.
Klubička F, Toral A, Sánchez-Cartagena VM (2018) Quantitative fine-grained human evaluation of machine translation systems: a case study on english to croatian. Machine Translation pp 1–21
2018
Closest in time.
Lam TK, Kreutzer J, Riezler S (2018) A reinforcement learning approach to interactive-predictive neural machine translation. In: Proceedings of the 21st Annual Conference of the European Association for Machine Translation (EAMT), Alicante, Spain
2018
Closest in time.