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1
Semantic changes in harm-related concepts in English ...
Vylomova, Ekaterina; Haslam, Nick. - : Zenodo, 2021
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2
Semantic changes in harm-related concepts in English ...
Vylomova, Ekaterina; Haslam, Nick. - : Zenodo, 2021
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3
More confident, less formal: stylistic changes in academic psychology writing from 1970 to 2016
In: Scientometrics, Vol. 126, no. 12 (Dec 2021), pp. 9603-9612 (2021)
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4
SIGMORPHON 2020 Shared Task 0: Typologically Diverse Morphological Inflection ...
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5
SIGTYP 2020 Shared Task: Prediction of Typological Features ...
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6
UniMorph 3.0: Universal Morphology
In: Proceedings of the 12th Language Resources and Evaluation Conference (2020)
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7
UniMorph 3.0: Universal Morphology ...
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8
Harm inflation: Making sense of concept creep
In: European Review of Social Psychology, Vol. 31, no. 1 (Jan 2020), pp. 254-286 (2020)
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9
Contextualization of Morphological Inflection ...
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10
The SIGMORPHON 2019 Shared Task: Morphological Analysis in Context and Cross-Lingual Transfer for Inflection ...
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11
Compositional morphology through deep learning
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12
Context-Aware Prediction of Derivational Word-forms ...
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13
Paradigm Completion for Derivational Morphology ...
Abstract: The generation of complex derived word forms has been an overlooked problem in NLP; we fill this gap by applying neural sequence-to-sequence models to the task. We overview the theoretical motivation for a paradigmatic treatment of derivational morphology, and introduce the task of derivational paradigm completion as a parallel to inflectional paradigm completion. State-of-the-art neural models, adapted from the inflection task, are able to learn a range of derivation patterns, and outperform a non-neural baseline by 16.4%. However, due to semantic, historical, and lexical considerations involved in derivational morphology, future work will be needed to achieve performance parity with inflection-generating systems. ... : EMNLP 2017 ...
Keyword: Computation and Language cs.CL; FOS Computer and information sciences
URL: https://arxiv.org/abs/1708.09151
https://dx.doi.org/10.48550/arxiv.1708.09151
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14
Take and Took, Gaggle and Goose, Book and Read: Evaluating the Utility of Vector Differences for Lexical Relation Learning ...
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