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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. - : Apollo - University of Cambridge Repository, 2018 BASE Show 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; Thomson, Blaise; Young, Steve. - : arXiv, 2016 Abstract: One of the core components of modern spoken dialogue systems is the belief tracker, which estimates the user's goal at every step of the dialogue. However, most current approaches have difficulty scaling to larger, more complex dialogue domains. This is due to their dependency on either: a) Spoken Language Understanding models that require large amounts of annotated training data; or b) hand-crafted lexicons for capturing some of the linguistic variation in users' language. We propose a novel Neural Belief Tracking (NBT) framework which overcomes these problems by building on recent advances in representation learning. NBT models reason over pre-trained word vectors, learning to compose them into distributed representations of user utterances and dialogue context. Our evaluation on two datasets shows that this approach surpasses past limitations, matching the performance of state-of-the-art models which rely on hand-crafted semantic lexicons and outperforming them when such lexicons are not provided. ... : Accepted as a long paper for the 55th Annual Meeting of the Association for Computational Linguistics (ACL 2017) ... Keyword: Artificial Intelligence cs.AI; Computation and Language cs.CL; FOS Computer and information sciences; Machine Learning cs.LG URL: https://arxiv.org/abs/1606.03777 https://dx.doi.org/10.48550/arxiv.1606.03777 BASE Hide 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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