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Distributed Representations of Geographically Situated Language.

, , and . ACL (2), page 828-834. The Association for Computer Linguistics, (2014)

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Learning the Curriculum with Bayesian Optimization for Task-Specific Word Representation Learning., , , , and . ACL (1), The Association for Computer Linguistics, (2016)Metaphor Detection with Cross-Lingual Model Transfer., , , , and . ACL (1), page 248-258. The Association for Computer Linguistics, (2014)Gaussian LDA for Topic Models with Word Embeddings., , and . ACL (1), page 795-804. The Association for Computer Linguistics, (2015)LSTMs Can Learn Syntax-Sensitive Dependencies Well, But Modeling Structure Makes Them Better., , , , , and . ACL (1), page 1426-1436. Association for Computational Linguistics, (2018)Unsupervised Word Alignment with Arbitrary Features., , , and . ACL, page 409-419. The Association for Computer Linguistics, (2011)Ontology-Aware Token Embeddings for Prepositional Phrase Attachment., , , and . ACL (1), page 2089-2098. Association for Computational Linguistics, (2017)What Do Recurrent Neural Network Grammars Learn About Syntax?, , , , , and . EACL (1), page 1249-1258. Association for Computational Linguistics, (2017)The CMU Machine Translation Systems at WMT 2013: Syntax, Synthetic Translation Options, and Pseudo-References., , , , , , , , , and . WMT@ACL, page 70-77. The Association for Computer Linguistics, (2013)Fast, Easy, and Cheap: Construction of Statistical Machine Translation Models with MapReduce., , , and . WMT@ACL, page 199-207. Association for Computational Linguistics, (2008)Crowdsourcing High-Quality Parallel Data Extraction from Twitter., , , , and . WMT@ACL, page 426-436. The Association for Computer Linguistics, (2014)