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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.. - : Association for Computational Linguistics (ACL), 2021 BASE Show 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.; Villavicencio, A.. - : Association for Computational Linguistics, 2021 Abstract: Despite their success in a variety of NLP tasks, pre-trained language models, due to their heavy reliance on compositionality, fail in effectively capturing the meanings of multiword expressions (MWEs), especially idioms. Therefore, datasets and methods to improve the representation of MWEs are urgently needed. Existing datasets are limited to providing the degree of idiomaticity of expressions along with the literal and, where applicable, (a single) non-literal interpretation of MWEs. This work presents a novel dataset of naturally occurring sentences containing MWEs manually classified into a fine-grained set of meanings, spanning both English and Portuguese. We use this dataset in two tasks designed to test i) a language model’s ability to detect idiom usage, and ii) the effectiveness of a language model in generating representations of sentences containing idioms. Our experiments demonstrate that, on the task of detecting idiomatic usage, these models perform reasonably well in the one-shot and few-shot scenarios, but that there is significant scope for improvement in the zero-shot scenario. On the task of representing idiomaticity, we find that pre-training is not always effective, while fine-tuning could provide a sample efficient method of learning representations of sentences containing MWEs. URL: https://eprints.whiterose.ac.uk/184561/ https://eprints.whiterose.ac.uk/184561/1/2021.findings-emnlp.294.pdf BASE Hide 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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