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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 Page: 1 2 Hits 1 – 20 of 23 1 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Ponti, Edoardo Maria; O’Horan, Helen; Berzak, Yevgeni... In: ISSN: 0891-2017 ; EISSN: 1530-9312 ; Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02425462 ; Computational Linguistics, Massachusetts Institute of Technology Press (MIT Press), 2019, 45 (3), pp.559-601. ⟨10.1162/coli_a_00357⟩ ; https://www.mitpressjournals.org/doi/abs/10.1162/coli_a_00357 (2019) BASE Show details 2 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing ... Ponti, Edoardo; O'Horan, Helen; Berzak, Yevgeni. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 3 Show Some Love to Your n-grams: A Bit of Progress and Stronger n-gram Language Modeling Baselines ... Shareghi, Ehsan; Gerz, Daniela; Vulic, Ivan; Korhonen, Anna-Leena. - : Apollo - University of Cambridge Repository, 2019 Abstract: In recent years neural language models (LMs) have set state-of-the-art performance for several benchmarking datasets. While the reasons for their success and their computational demand are well-documented, a comparison between neural models and more recent developments in n-gram models is neglected. In this paper, we examine the recent progress in n-gram literature, running experiments on 50 languages covering all morphological language families. Experimental results illustrate that a simple extension of Modified Kneser-Ney outperforms an LSTM language model on 42 languages while a word-level Bayesian n-gram LM outperforms the character-aware neural model on average across all languages, and its extension which explicitly injects linguistic knowledge on 8 languages. Further experiments on larger Europarl datasets for 3 languages indicate that neural architectures are able to outperform computationally much cheaper n-gram models: n-gram training is up to 15,000 times quicker. Our experiments illustrate that ... URL: https://www.repository.cam.ac.uk/handle/1810/292617 https://dx.doi.org/10.17863/cam.39778 BASE Hide details 4 Specializing Unsupervised Pretraining Models for Word-Level Semantic Similarity ... Lauscher, Anne; Vulić, Ivan; Ponti, Edoardo Maria. - : arXiv, 2019 BASE Show details 5 Do We Really Need Fully Unsupervised Cross-Lingual Embeddings? ... Vulić, Ivan; Glavaš, Goran; Reichart, Roi. - : arXiv, 2019 BASE Show details 6 How to (Properly) Evaluate Cross-Lingual Word Embeddings: On Strong Baselines, Comparative Analyses, and Some Misconceptions ... Glavas, Goran; Litschko, Robert; Ruder, Sebastian. - : arXiv, 2019 BASE Show details 7 Specialising Distributional Vectors of All Words for Lexical Entailment ... Kamath, Aishwarya; Pfeiffer, Jonas; Ponti, Edoardo. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 8 Multilingual and cross-lingual graded lexical entailment ... Vulic, Ivan; Ponzetto, SP; Glavaš, G. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 9 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment ... Glavaš, G; Vulic, Ivan. - : Apollo - University of Cambridge Repository, 2019 BASE Show details 10 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment Glavaš, G; Vulic, Ivan. - : Association for Computational Linguistics, 2019. : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 2019 BASE Show details 11 Multilingual and cross-lingual graded lexical entailment Vulic, Ivan; Ponzetto, SP; Glavaš, G. - : Association for Computational Linguistics, 2019. : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 2019 BASE Show details 12 How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions Glavaš, G; Litschko, R; Ruder, S. - : Association for Computational Linguistics, 2019. : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 2019 BASE Show details 13 JW300: A wide-coverage parallel corpus for low-resource languages Agic, Ž; Vulic, Ivan. - : Association for Computational Linguistics, 2019. : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Proceedings of the Conference, 2019 BASE Show details 14 Unsupervised cross-lingual representation learning Ruder, S; Søgaard, A; Vulic, Ivan. - : ACL 2019 - 57th Annual Meeting of the Association for Computational Linguistics, Tutorial Abstracts, 2019 BASE Show details 15 Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing Reichart, Roi; Shutova, Ekaterina; Korhonen, Anna-Leena. - : MIT Press - Journals, 2019. : COMPUTATIONAL LINGUISTICS, 2019 BASE Show details 16 Multilingual and cross-lingual graded lexical entailment Glavaš, Goran; Vulić, Ivan; Ponzetto, Simone Paolo. - : Association for Computational Linguistics, 2019 BASE Show details 17 Specializing distributional vectors of all words for lexical entailment Ponti, Edoardo Maria; Kamath, Aishwarya; Pfeiffer, Jonas. - : Association for Computational Linguistics, 2019 BASE Show details 18 How to (properly) evaluate cross-lingual word embeddings: On strong baselines, comparative analyses, and some misconceptions Glavaš, Goran; Litschko, Robert; Ruder, Sebastian. - : Association for Computational Linguistics, 2019 BASE Show details 19 Cross-lingual semantic specialization via lexical relation induction Glavaš, Goran; Vulić, Ivan; Korhonen, Anna. - : Association for Computational Linguistics, 2019 BASE Show details 20 Generalized tuning of distributional word vectors for monolingual and cross-lingual lexical entailment Vulić, Ivan; Glavaš, Goran. - : Association for Computational Linguistics, 2019 BASE Show details Page: 1 2

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