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Universal Dependencies 2.2
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In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018)
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Beyond task success: A closer look at jointly learning to see, ask, and GuessWhat ...
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Distant Supervision from Disparate Sources for Low-Resource Part-of-Speech Tagging ...
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The Best of Both Worlds: Lexical Resources To Improve Low-Resource Part-of-Speech Tagging ...
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Bleaching Text: Abstract Features for Cross-lingual Gender Prediction ...
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Abstract:
Gender prediction has typically focused on lexical and social network features, yielding good performance, but making systems highly language-, topic-, and platform-dependent. Cross-lingual embeddings circumvent some of these limitations, but capture gender-specific style less. We propose an alternative: bleaching text, i.e., transforming lexical strings into more abstract features. This study provides evidence that such features allow for better transfer across languages. Moreover, we present a first study on the ability of humans to perform cross-lingual gender prediction. We find that human predictive power proves similar to that of our bleached models, and both perform better than lexical models. ... : Proceedings of the 56th Annual Meeting of the Association for Computational Linguistics ...
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Keyword:
Computation and Language cs.CL; FOS Computer and information sciences
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URL: https://dx.doi.org/10.48550/arxiv.1805.03122 https://arxiv.org/abs/1805.03122
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28 |
Universal Dependencies 2.1
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In: https://hal.inria.fr/hal-01682188 ; 2017 (2017)
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When is multitask learning effective? Semantic sequence prediction under varying data conditions
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In: EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01677427 ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2017, Valencia, Spain. pp.1-10 ; http://eacl2017.org/ (2017)
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30 |
Parsing Universal Dependencies without training
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In: Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 1, ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01677405 ; EACL 2017 - 15th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2017, Valencia, Spain. pp.229 - 239 ; http://eacl2017.org/ (2017)
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33 |
Universal Dependencies 2.0 – CoNLL 2017 Shared Task Development and Test Data
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ALL-IN-1: Short Text Classification with One Model for All Languages ...
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Multilingual Projection for Parsing Truly Low-Resource Languageš
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.inria.fr/hal-01426754 ; Transactions of the Association for Computational Linguistics, The MIT Press, 2016 (2016)
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Supersense tagging with inter-annotator disagreement
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In: Linguistic Annotation Workshop 2016 ; https://hal.inria.fr/hal-01426747 ; Linguistic Annotation Workshop 2016, Aug 2016, Berlin, Germany. pp.43 - 48 (2016)
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