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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 – 9 of 9 1 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo,; O 'horan, Helen; Berzak, Yevgeni... In: https://hal.archives-ouvertes.fr/hal-01856176 ; 2018 (2018) BASE Show details 2 Unsupervised Cross-Lingual Information Retrieval using Monolingual Data Only ... Litschko, Robert; Glavaš, Goran; Ponzetto, Simone Paolo. - : arXiv, 2018 BASE Show details 3 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing ... Ponti, Edoardo Maria; O'Horan, Helen; Berzak, Yevgeni; Vulić, Ivan; Reichart, Roi; Poibeau, Thierry; Shutova, Ekaterina; Korhonen, Anna. - : arXiv, 2018 Abstract: Linguistic typology aims to capture structural and semantic variation across the world's languages. A large-scale typology could provide excellent guidance for multilingual Natural Language Processing (NLP), particularly for languages that suffer from the lack of human labeled resources. We present an extensive literature survey on the use of typological information in the development of NLP techniques. Our survey demonstrates that to date, the use of information in existing typological databases has resulted in consistent but modest improvements in system performance. We show that this is due to both intrinsic limitations of databases (in terms of coverage and feature granularity) and under-employment of the typological features included in them. We advocate for a new approach that adapts the broad and discrete nature of typological categories to the contextual and continuous nature of machine learning algorithms used in contemporary NLP. In particular, we suggest that such approach could be facilitated by ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/1807.00914 https://dx.doi.org/10.48550/arxiv.1807.00914 BASE Hide details 4 On the Limitations of Unsupervised Bilingual Dictionary Induction ... Søgaard, Anders; Ruder, Sebastian; Vulić, Ivan. - : arXiv, 2018 BASE Show details 5 Fully Statistical Neural Belief Tracking ... Mrkšić, Nikola; Vulić, Ivan. - : arXiv, 2018 BASE Show details 6 Bio-SimVerb ... Chiu, Hon Wing; Pyysalo, Sampo; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2018 BASE Show details 7 Scoring Lexical Entailment with a Supervised Directional Similarity Network ... Rei, Marek; Gerz, Daniela; Vulić, Ivan. - : arXiv, 2018 BASE Show details 8 Post-Specialisation: Retrofitting Vectors of Words Unseen in Lexical Resources ... Vulić, Ivan; Glavaš, Goran; Mrkšić, Nikola. - : arXiv, 2018 BASE Show details 9 Bio-SimVerb Chiu, Hon Wing; Pyysalo, Sampo; Vulic, Ivan. - 2018 BASE Show details

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