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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 32 1 Coloring the Blank Slate: Pre-training Imparts a Hierarchical Inductive Bias to Sequence-to-sequence Models ... Mueller, Aaron; Frank, Robert; Linzen, Tal. - : arXiv, 2022 BASE Show details 2 Can language models capture syntactic associations without surface cues? A case study of reflexive anaphor licensing in English control constructions Lee, Soo-Hwan; Schuster, Sebastian In: Proceedings of the Society for Computation in Linguistics (2022) BASE Show details 3 Universal Dependencies 2.9 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 4 Universal Dependencies 2.8.1 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 5 Universal Dependencies 2.8 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2021 BASE Show details 6 NOPE: A Corpus of Naturally-Occurring Presuppositions in English ... Parrish, Alicia; Schuster, Sebastian; Warstadt, Alex. - : arXiv, 2021 BASE Show details 7 NOPE: A Corpus of Naturally-Occurring Presuppositions in English ... The 2021 Conference on Empirical Methods in Natural Language Processing 2021; ., Alex; Agha, Omar. - : Underline Science Inc., 2021 BASE Show details 8 Predicting Scalar Inferences From "Or" to "Not Both" Using Neural Sentence Encoders Li, Elissa; Schuster, Sebastian; Degen, Judith In: Proceedings of the Society for Computation in Linguistics (2021) BASE Show details 9 I’ve got a construction looks funny – representing and recovering non-standard constructions in UD Ruppenhofer, Josef [Verfasser]; Rehbein, Ines [Verfasser]; de Marneffe, Marie-Catherine [Herausgeber]. - Mannheim : Leibniz-Institut für Deutsche Sprache (IDS), Bibliothek, 2020 DNB Subject Category Language Show details 10 Universal Dependencies 2.7 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 11 Universal Dependencies 2.6 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2020 BASE Show details 12 Universal Dependencies v2: An Evergrowing Multilingual Treebank Collection ... Nivre, Joakim; de Marneffe, Marie-Catherine; Ginter, Filip. - : arXiv, 2020 BASE Show details 13 Universal Dependencies 2.5 Zeman, Daniel; Nivre, Joakim; Abrams, Mitchell. - : Universal Dependencies Consortium, 2019 BASE Show details 14 Universal Dependencies 2.4 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2019 BASE Show details 15 Harnessing the linguistic signal to predict scalar inferences ... Schuster, Sebastian; Chen, Yuxing; Degen, Judith. - : arXiv, 2019 Abstract: Pragmatic inferences often subtly depend on the presence or absence of linguistic features. For example, the presence of a partitive construction (of the) increases the strength of a so-called scalar inference: listeners perceive the inference that Chris did not eat all of the cookies to be stronger after hearing "Chris ate some of the cookies" than after hearing the same utterance without a partitive, "Chris ate some cookies." In this work, we explore to what extent neural network sentence encoders can learn to predict the strength of scalar inferences. We first show that an LSTM-based sentence encoder trained on an English dataset of human inference strength ratings is able to predict ratings with high accuracy (r=0.78). We then probe the model's behavior using manually constructed minimal sentence pairs and corpus data. We find that the model inferred previously established associations between linguistic features and inference strength, suggesting that the model learns to use linguistic features to ... : ACL 2020; 16 pages, 8 figures ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://dx.doi.org/10.48550/arxiv.1910.14254 https://arxiv.org/abs/1910.14254 BASE Hide details 16 Kauderwelsch, kryptische Aussagen und Fachvokabular : Wirkung des Politikerdeutschen auf Jugendliche und Jungwähler Schuster, Sebastian [Verfasser]. - München : GRIN Verlag, 2018 DNB Subject Category Language Show details 17 Kauderwelsch, kryptische Aussagen und Fachvokabular : Wirkung des Politikerdeutschen auf Jugendliche und Jungwähler Schuster, Sebastian [Verfasser]. - München : GRIN Verlag, 2018 DNB Subject Category Language Show details 18 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko... In: https://hal.archives-ouvertes.fr/hal-01930733 ; 2018 (2018) BASE Show details 19 Universal Dependencies 2.3 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details 20 Universal Dependencies 2.2 Nivre, Joakim; Abrams, Mitchell; Agić, Željko. - : Universal Dependencies Consortium, 2018 BASE Show details Page: 1 2

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