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Multilingual and Cross-Lingual Intent Detection from Spoken Data ...
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Multilingual and Cross-Lingual Intent Detection from Spoken Data ...
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Data-Driven Language Understanding for Spoken Dialogue Systems ...
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Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ...
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Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
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Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ...
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Post-specialisation: Retrofitting vectors of words unseen in lexical resources
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Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization
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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
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Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules ...
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Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation ...
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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ...
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Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints
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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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Counter-fitting Word Vectors to Linguistic Constraints ...
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Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Thomson, Blaise; Gašić, Milica; Rojas-Barahona, Lina; Su, Pei-Hao; Vandyke, David; Wen, Tsung-Hsien; Young, Steve. - : arXiv, 2016
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Abstract:
In this work, we present a novel counter-fitting method which injects antonymy and synonymy constraints into vector space representations in order to improve the vectors' capability for judging semantic similarity. Applying this method to publicly available pre-trained word vectors leads to a new state of the art performance on the SimLex-999 dataset. We also show how the method can be used to tailor the word vector space for the downstream task of dialogue state tracking, resulting in robust improvements across different dialogue domains. ... : Paper accepted for the 15th Annual Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 2016) ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG
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URL: https://dx.doi.org/10.48550/arxiv.1603.00892 https://arxiv.org/abs/1603.00892
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Neural Belief Tracker: Data-Driven Dialogue State Tracking ...
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Research data supporting "On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems"
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Multi-domain Dialog State Tracking using Recurrent Neural Networks ...
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Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking ...
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