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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 20 of 20 1 Multilingual and Cross-Lingual Intent Detection from Spoken Data ... Gerz, Daniela; Su, Pei-Hao; Kusztos, Razvan. - : arXiv, 2021 BASE Show details 2 Multilingual and Cross-Lingual Intent Detection from Spoken Data ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; Gerz, Daniela; Kusztos, Razvan. - : Underline Science Inc., 2021 BASE Show details 3 Fully Statistical Neural Belief Tracking ... Mrkšić, Nikola; Vulić, Ivan. - : arXiv, 2018 BASE Show details 4 Data-Driven Language Understanding for Spoken Dialogue Systems ... Mrkšić, Nikola. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 5 Adversarial Propagation and Zero-Shot Cross-Lingual Transfer of Word Vector Specialization ... Ponti, Edoardo Maria; Vulić, Ivan; Glavaš, Goran. - : arXiv, 2018 BASE Show details 6 Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ... Vulić, Ivan; Glavaš, Goran; Mrkšić, Nikola. - : arXiv, 2018 BASE Show details 7 Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ... Vulic, Ivan; Glavaš, Goran; Mrkšić, Nikola; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2018 Abstract: Word vector specialisation (also known as retrofitting) is a portable, light-weight approach to fine-tuning arbitrary distributional word vector spaces by injecting external knowledge from rich lexical resources such as WordNet. By design, these post-processing methods only update the vectors of words occurring in external lexicons, leaving the representations of all unseen words intact. In this paper, we show that constraint-driven vector space specialisation can be extended to unseen words. We propose a novel post-specialisation method that: a) preserves the useful linguistic knowledge for seen words; while b) propagating this external signal to unseen words in order to improve their vector representations as well. Our post-specialisation approach explicits a non-linear specialisation function in the form of a deep neural network by learning to predict specialised vectors from their original distributional counterparts. The learned function is then used to specialise vectors of unseen words. This approach, ... : https://www.aclweb.org/anthology/N18-1048 ... URL: https://www.repository.cam.ac.uk/handle/1810/294076 https://dx.doi.org/10.17863/cam.41176 BASE Hide details 8 Post-specialisation: Retrofitting vectors of words unseen in lexical resources Mrkšić, Nikola; Glavaš, Goran; Korhonen, Anna. - : Association for Computational Linguistics, 2018 BASE Show details 9 Adversarial propagation and zero-shot cross-lingual transfer of word vector specialization Ponti, Edoardo Maria; Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2018 BASE Show details 10 Specialising Word Vectors for Lexical Entailment ... Vulić, Ivan; Mrkšić, Nikola. - : arXiv, 2017 BASE Show details 11 Semantic Specialisation of Distributional Word Vector Spaces using Monolingual and Cross-Lingual Constraints ... Mrkšić, Nikola; Vulić, Ivan; Séaghdha, Diarmuid Ó. - : arXiv, 2017 BASE Show details 12 Morph-fitting: Fine-Tuning Word Vector Spaces with Simple Language-Specific Rules ... Vulić, Ivan; Mrkšić, Nikola; Reichart, Roi. - : arXiv, 2017 BASE Show details 13 Cross-Lingual Induction and Transfer of Verb Classes Based on Word Vector Space Specialisation ... Vulić, Ivan; Mrkšić, Nikola; Korhonen, Anna. - : arXiv, 2017 BASE Show details 14 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 BASE Show details 15 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 BASE Show details 16 Counter-fitting Word Vectors to Linguistic Constraints ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Thomson, Blaise. - : arXiv, 2016 BASE Show details 17 Neural Belief Tracker: Data-Driven Dialogue State Tracking ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Wen, Tsung-Hsien. - : arXiv, 2016 BASE Show details 18 Research data supporting "On-line Active Reward Learning for Policy Optimisation in Spoken Dialogue Systems" Su, Pei-Hao; Gasic, Milica; Mrksic, Nikola. - : University of Cambridge, 2016 BASE Show details 19 Multi-domain Dialog State Tracking using Recurrent Neural Networks ... Mrkšić, Nikola; Séaghdha, Diarmuid Ó; Thomson, Blaise. - : arXiv, 2015 BASE Show details 20 Stochastic Language Generation in Dialogue using Recurrent Neural Networks with Convolutional Sentence Reranking ... Wen, Tsung-Hsien; Gasic, Milica; Kim, Dongho. - : arXiv, 2015 BASE Show details

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