Sirvi Autor "Östling, Robert" järgi

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Cross-lingual Learning of Semantic Textual Similarity with Multilingual Word Representations
(Gothenburg, Sweden, Association for Computational Linguistics, pp. 211--215, 2017) Bjerva, Johannes; Östling, Robert; Tiedemann, Jörg; Tahmasebi, Nina
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Enriching the Swedish Sign Language Corpus with Part of Speech Tags Using Joint Bayesian Word Alignment and Annotation Transfer
(Vilnius, Lithuania, Linköping University Electronic Press, Sweden, pp. 263--268, 2015) Östling, Robert; Börstell, Carl; Wallin, Lars; Megyesi, Beáta
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Iconic Locations in Swedish Sign Language: Mapping Form to Meaning with Lexical Databases
(Gothenburg, Sweden, Association for Computational Linguistics, pp. 221--225, 2017) Börstell, Carl; Östling, Robert; Tiedemann, Jörg; Tahmasebi, Nina
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Inferring the location of authors from words in their texts
(Vilnius, Lithuania, Linköping University Electronic Press, Sweden, pp. 211--218, 2015) Berggren, Max; Karlgren, Jussi; Östling, Robert; Parkvall, Mikael; Megyesi, Beáta
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Tagging a Morphologically Complex Language Using an Averaged Perceptron Tagger: The Case of Icelandic
(Oslo, Norway, Linköping University Electronic Press, Sweden, pp. 105--119, 2013) Loftsson, Hrafn; Östling, Robert; Oepen, Stephan; Hagen, Kristin; Johannessen, Janne Bondi
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The MultiGEC-2025 Shared Task on Multilingual Grammatical Error Correction at NLP4CALL
(University of Tartu Library, 2025-03) Masciolini, Arianna; Caines, Andrew; De Clercq, Orphée; Kruijsbergen, Joni; Kurfalı, Murathan; Muñoz Sánchez, Ricardo; Volodina, Elena; Östling, Robert; Muñoz Sánchez, Ricardo; Alfter, David; Volodina, Elena; Kallas, Jelena
This paper reports on MultiGEC-2025, the first shared task in text-level Multilingual Grammatical Error Correction. The shared task features twelve European languages (Czech, English, Estonian, German, Greek, Icelandic, Italian, Latvian, Russian, Slovene, Swedish and Ukrainian) and is organized into two tracks, one for systems producing minimally corrected texts, thus preserving as much as possible of the original language use, and one dedicated to systems that prioritize fluency and idiomaticity. We introduce the task setup, data, evaluation metrics and baseline; present results obtained by the submitted systems and discuss key takeaways and ideas for future work.
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Universal Dependencies for Swedish Sign Language
(Gothenburg, Sweden, Association for Computational Linguistics, pp. 303--308, 2017) Östling, Robert; Börstell, Carl; Gärdenfors, Moa; Wirén, Mats; Tiedemann, Jörg; Tahmasebi, Nina