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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 34 1 Understanding the effects of negative (and positive) pointwise mutual information on word vectors Salle, A.; Villavicencio, A.. - : Taylor & Francis, 2022 BASE Show details 2 Improving tokenisation by alternative treatment of spaces Gow-Smith, E.; Scarton, C.; Madabushi, H.T.. - 2022 BASE Show details 3 Assessing idiomaticity representations in vector models with a noun compound dataset labeled at type and token levels Garcia, M.; Kramer Vieira, T.; Scarton, C.; Idiart, M.A.P.; Villavicencio, A.. - : Association for Computational Linguistics (ACL), 2021 Abstract: Accurate assessment of the ability of embedding models to capture idiomaticity may require evaluation at token rather than type level, to account for degrees of idiomaticity and possible ambiguity between literal and idiomatic usages. However, most existing resources with annotation of idiomaticity include ratings only at type level. This paper presents the Noun Compound Type and Token Idiomaticity (NCTTI) dataset, with human annotations for 280 noun compounds in English and 180 in Portuguese at both type and token level. We compiled 8,725 and 5,091 token level annotations for English and Portuguese, respectively, which are strongly correlated with the corresponding scores obtained at type level. The NCTTI dataset is used to explore how vector space models reflect the variability of idiomaticity across sentences. Several experiments using state-of-the-art contextualised models suggest that their representations are not capturing the noun compounds idiomaticity as human annotators. This new multilingual resource also contains suggestions for paraphrases of the noun compounds both at type and token levels, with uses for lexical substitution or disambiguation in context. URL: http://eprints.whiterose.ac.uk/173800/ BASE Hide details 4 Probing for idiomaticity in vector space models Garcia, M.; Vieira, T.K.; Scarton, C.. - : Association for Computational Linguistics (ACL), 2021 BASE Show details 5 AStitchInLanguageModels : dataset and methods for the exploration of idiomaticity in pre-trained language models Tayyar Madabushi, H.; Gow-Smith, E.; Scarton, C.. - : Association for Computational Linguistics, 2021 BASE Show details 6 CogNLP-Sheffield at CMCL 2021 Shared Task: Blending cognitively inspired features with transformer-based language models for predicting eye tracking patterns Vickers, P.; Wainwright, R.; Tayyar Madabushi, H.. - : Association for Computational Linguistics (ACL), 2021 BASE Show details 7 Investigating language impact in bilingual approaches for computational language documentation Boito, M.Z.; Villavicencio, A.; Besacier, L.. - : Special Interest Group: Under-resourced Languages (SIGUL), 2020 BASE Show details 8 Unsupervised compositionality prediction of nominal compounds Cordeiro, S.; Villavicencio, A.; Idiart, M.. - : MIT Press - Journals, 2019 BASE Show details 9 A dual-attention hierarchical recurrent neural network for dialogue act classification Li, R.; Lin, C.; Collinson, M.. - : Association for Computational Linguistics (ACL), 2019 BASE Show details 10 When the whole is greater than the sum of its parts : multiword expressions and idiomaticity Villavicencio, A.. - : Association for Computational Linguistics, 2019 BASE Show details 11 Proceedings of the 23rd Conference on Computational Natural Language Learning (CoNLL) Bansal, M.; Villavicencio, A.. - : Association for Computational Linguistics (ACL), 2019 BASE Show details 12 Discovering multiword expressions Villavicencio, A.; Idiart, M.. - : Cambridge University Press (CUP), 2019 BASE Show details 13 Empirical evaluation of sequence-to-sequence models for word discovery in low-resource settings Boito, M.Z.; Villavicencio, A.; Besacier, L.. - : International Speech Communication Association (ISCA), 2019 BASE Show details 14 Unsupervised word segmentation from speech with attention Godard, P.; Boito, M.Z.; Ondel, L.. - : ISCA, 2018 BASE Show details 15 Similarity Measures for the Detection of Clinical Conditions with Verbal Fluency Tasks Paula, F.; Wilkens, R.; Idiart, M.. - : Association for Computational Linguistics, 2018 BASE Show details 16 A corpus study of verbal multiword expressions in Brazilian Portuguese Ramisch, C.; Ramisch, R.; Zilio, L.. - : Springer International Publishing, 2018 BASE Show details 17 Unwritten languages demand attention too! Word discovery with encoder-decoder models Boito, M.Z.; Bérard, A.; Villavicencio, A.. - : IEEE, 2018 BASE Show details 18 Restricted recurrent neural tensor networks: Exploiting word frequency and compositionality Salle, A.; Villavicencio, A.. - : Association for Computational Linguistics, 2018 BASE Show details 19 UFRGS&LIF at SemEval-2016 task 10: Rule-based MWE identification and predominant-supersense tagging Cordeiro, S.R.; Ramisch, C.; Villavicencio, A.. - : Association for Computational Linguistics, 2016 BASE Show details 20 How naked is the naked truth? A multilingual lexicon of nominal compound compositionality Villavicencio, A.; Wilkens, R.; Ramisch, C.. - : Association for Computational Linguistics, 2016 BASE Show details Page: 1 2

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