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How to represent a word and predict it, too: improving tied architectures for language modelling.

, , and . EMNLP, page 2936-2941. Association for Computational Linguistics, (2018)

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AMORE-UPF at SemEval-2018 Task 4: BiLSTM with Entity Library., , , , and . SemEval@NAACL-HLT, page 65-69. Association for Computational Linguistics, (2018)Putting Words in Context: LSTM Language Models and Lexical Ambiguity., , and . ACL (1), page 3342-3348. Association for Computational Linguistics, (2019)What do Entity-Centric Models Learn? Insights from Entity Linking in Multi-Party Dialogue., , , , and . NAACL-HLT (1), page 3772-3783. Association for Computational Linguistics, (2019)How to represent a word and predict it, too: improving tied architectures for language modelling., , and . EMNLP, page 2936-2941. Association for Computational Linguistics, (2018)A Distributional Study of Negated Adjectives and Antonyms., , and . CLiC-it, volume 2253 of CEUR Workshop Proceedings, CEUR-WS.org, (2018)