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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 3 4 5 6 7 Hits 21 – 40 of 123 21 Multitask Easy-First Dependency Parsing ... The 28th International Conference on Computational Linguistics 2020; Habash, Nizar; Kankanampati, Yash. - : Underline Science Inc., 2020 BASE Show details 22 Adversarial Multitask Learning for Joint Multi-Feature and Multi-Dialect Morphological Modeling ... Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019 BASE Show details 23 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 24 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 25 Joint Diacritization, Lemmatization, Normalization, and Fine-Grained Morphological Tagging ... Zalmout, Nasser; Habash, Nizar. - : arXiv, 2019 Abstract: Semitic languages can be highly ambiguous, having several interpretations of the same surface forms, and morphologically rich, having many morphemes that realize several morphological features. This is further exacerbated for dialectal content, which is more prone to noise and lacks a standard orthography. The morphological features can be lexicalized, like lemmas and diacritized forms, or non-lexicalized, like gender, number, and part-of-speech tags, among others. Joint modeling of the lexicalized and non-lexicalized features can identify more intricate morphological patterns, which provide better context modeling, and further disambiguate ambiguous lexical choices. However, the different modeling granularity can make joint modeling more difficult. Our approach models the different features jointly, whether lexicalized (on the character-level), where we also model surface form normalization, or non-lexicalized (on the word-level). We use Arabic as a test case, and achieve state-of-the-art results for Modern ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1910.02267 https://arxiv.org/abs/1910.02267 BASE Hide details 26 CoNLL-UL: Universal Morphological Lattices for Universal Dependency Parsing More, Amir; Çetinoğlu, Özlem; Çöltekin, Çağri... In: 11th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-01786125 ; 11th Language Resources and Evaluation Conference, May 2018, Miyazaki, Japan ; http://lrec2018.lrec-conf.org (2018) BASE Show details 27 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko... In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018) BASE Show details 28 MADARi: A Web Interface for Joint Arabic Morphological Annotation and Spelling Correction ... Obeid, Ossama; Khalifa, Salam; Habash, Nizar. - : arXiv, 2018 BASE Show details 29 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 30 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 31 Utilizing Character and Word Embeddings for Text Normalization with Sequence-to-Sequence Models ... Watson, Daniel; Zalmout, Nasser; Habash, Nizar. - : arXiv, 2018 BASE Show details 32 Identifying effective translations for cross-lingual Arabic-to-English user-generated speech search Khwileh, Ahmad; Way, Andy; Jones, Gareth J.F.... In: Khwileh, Ahmad, Afli, Haithem orcid:0000-0002-7449-4707 , Jones, Gareth J.F. orcid:0000-0003-2923-8365 and Way, Andy orcid:0000-0001-5736-5930 (2017) Identifying effective translations for cross-lingual Arabic-to-English user-generated speech search. In: Third Arabic Natural Language Processing Workshop (WANLP), 3 Apr 2017, Valencia, Spain. (2017) BASE Show details 33 Universal Dependencies 2.1 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars... In: https://hal.inria.fr/hal-01682188 ; 2017 (2017) BASE Show details 34 Universal Dependencies 2.0 alpha (obsolete) Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017 BASE Show details 35 Universal Dependencies 2.0 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017 BASE Show details 36 Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017 BASE Show details 37 Universal Dependencies 2.1 Nivre, Joakim; Agić, Željko; Ahrenberg, Lars. - : Universal Dependencies Consortium, 2017 BASE Show details 38 Low Resourced Machine Translation via Morpho-syntactic Modeling: The Case of Dialectal Arabic ... Erdmann, Alexander; Habash, Nizar; Taji, Dima. - : arXiv, 2017 BASE Show details 39 CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies Çöltekin, Çağrı; Kayadelen, Tolga; Droganova, Kira. - : Association for Computational Linguistics, 2017. : country:USA, 2017. : place:Stroudsburg, PA, 2017 BASE Show details 40 Optimizing Tokenization Choice for Machine Translation across Multiple Target Languages Zalmout Nasser; Habash Nizar In: Prague Bulletin of Mathematical Linguistics , Vol 108, Iss 1, Pp 257-269 (2017) (2017) BASE Show details Page: 1 2 3 4 5 6 7

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