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1
Licensing Complex Prepositions via Lexical Constraints
Trawiński, Beata [Verfasser]; Bond, Francis [Herausgeber]; Korhonen, Anna [Herausgeber]. - Mannheim : Institut für Deutsche Sprache, Bibliothek, 2017
DNB Subject Category Language
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2
Investigating the cross-lingual translatability of VerbNet-style classification [<Journal>]
Majewska, Olga [Verfasser]; Vulić, Ivan [Sonstige]; McCarthy, Diana [Sonstige].
DNB Subject Category Language
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3
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations ...
Vulić, Ivan; Schwartz, Roy; Rappoport, Ari. - : Apollo - University of Cambridge Repository, 2017
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4
Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
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5
Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules ...
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6
Decoding Sentiment from Distributed Representations of Sentences ...
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7
Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation ...
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8
Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
Mrkšić, Nikola; Vulić, Ivan; Ó Séaghdha, Diarmuid. - : Apollo - University of Cambridge Repository, 2017
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9
Decoding sentiment from distributed representations of sentences ...
Ponti, Edoardo; Vulić, I; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2017
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10
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment ...
Vulić, I; Gerz, D; Kiela, D. - : Apollo - University of Cambridge Repository, 2017
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11
Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules ...
Vulic, Ivan; Mrkšic, N; Reichart, R. - : Apollo - University of Cambridge Repository, 2017
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12
Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints
Mrkšić, Nikola; Vulić, Ivan; Ó Séaghdha, Diarmuid. - : Association for Computational Linguistics, 2017. : https://www.transacl.org/ojs/index.php/tacl/article/view/1171, 2017. : Transactions of the Association for Computational Linguistics (TACL), 2017
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13
Decoding sentiment from distributed representations of sentences
Ponti, Edoardo; Vulić, I; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : *SEM 2017 - 6th Joint Conference on Lexical and Computational Semantics, Proceedings, 2017
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14
HyperLex: A Large-Scale Evaluation of Graded Lexical Entailment
Vulić, I; Gerz, D; Kiela, D. - : MIT Press, 2017. : Computational Linguistics, 2017
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15
Event-Related Features in Feedforward Neural Networks Contribute to Identifying Causal Relations in Discourse
Ponti, Edoardo; Korhonen, Anna-Leena. - : LSDSem 2017 - 2nd Workshop on Linking Models of Lexical, Sentential and Discourse-Level Semantics, Proceedings of the Workshop, 2017
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16
Morph-fitting: Fine-tuning word vector spaces with simple language-specific rules
Vulic, Ivan; Mrkšic, N; Reichart, R; Séaghdha, D; Young, Steve; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : ACL 2017 - 55th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference (Long Papers), 2017
Abstract: Morphologically rich languages accentuate two properties of distributional vector space models: 1) the difficulty of inducing accurate representations for low-frequency word forms; and 2) insensitivity to distinct lexical relations that have similar distributional signatures. These effects are detrimental for language understanding systems, which may infer that inexpensive is a rephrasing for expensive or may not associate acquire with acquires. In this work, we propose a novel morph-fitting procedure which moves past the use of curated semantic lexicons for improving distributional vector spaces. Instead, our method injects morphological constraints generated using simple language-specific rules, pulling inflectional forms of the same word close together and pushing derivational antonyms far apart. In intrinsic evaluation over four languages, we show that our approach: 1) improves low-frequency word estimates; and 2) boosts the semantic quality of the entire word vector collection. Finally, we show that morph-fitted vectors yield large gains in the downstream task of dialogue state tracking, highlighting the importance of morphology for tackling long-tail phenomena in language understanding tasks.
Keyword: Dialogue state tracking; Morphologically complex languages; Semantic specialisation; Vector space models; Word embeddings
URL: https://doi.org/10.17863/CAM.10176
https://www.repository.cam.ac.uk/handle/1810/264637
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17
Automatic Selection of Context Configurations for Improved Class-Specific Word Representations
Rappoport, Ari; Reichart, Roi; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : https://arxiv.org/pdf/1608.05528.pdf, 2017. : Proceedings of the 21st Conference on Computational Natural Language Learning (CoNLL 2017), 2017
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18
Evaluation by association: A systematic study of quantitative word association evaluation
Vulić, I; Kiela, D; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : 15th Conference of the European Chapter of the Association for Computational Linguistics, EACL 2017 - Proceedings of Conference, 2017
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19
Initializing neural networks for hierarchical multi-label text classification
Baker, Simon; Korhonen, Anna-Leena. - : Association for Computational Linguistics, 2017. : BioNLP 2017 - SIGBioMed Workshop on Biomedical Natural Language Processing, Proceedings of the 16th BioNLP Workshop, 2017
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