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Learning to Prune: Context-Sensitive Pruning for Syntactic MT.

, , , and . ACL (2), page 352-357. The Association for Computer Linguistics, (2013)

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A tree does not make a well-formed sentence: Improving syntactic string-to-tree statistical machine translation with more linguistic knowledge., , and . Comput. Speech Lang., 32 (1): 27-45 (2015)Edinburgh's Syntax-Based Systems at WMT 2014., , , , , and . WMT@ACL, page 207-214. The Association for Computer Linguistics, (2014)ELITR Non-Native Speech Translation at IWSLT 2020., , , , , , , , and . IWSLT, page 200-208. Association for Computational Linguistics, (2020)ELITR Multilingual Live Subtitling: Demo and Strategy., , , , , , , , , and 9 other author(s). EACL (System Demonstrations), page 271-277. Association for Computational Linguistics, (2021)Improving Massively Multilingual Neural Machine Translation and Zero-Shot Translation., , , and . ACL, page 1628-1639. Association for Computational Linguistics, (2020)SPROUT: A program for structure generation., , , , and . J. Comput. Aided Mol. Des., 7 (2): 127-153 (1993)Access to information in Europe.. Comput. Commun., 1 (6): 290-294 (1978)The University of Edinburgh's Neural MT Systems for WMT17., , , , , , , and . WMT, page 389-399. Association for Computational Linguistics, (2017)Edinburgh's Syntax-Based Machine Translation Systems., , and . WMT@ACL, page 170-176. The Association for Computer Linguistics, (2013)Edinburgh's Syntax-Based Systems at WMT 2015., , , , and . WMT@EMNLP, page 199-209. The Association for Computer Linguistics, (2015)