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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 Hits 1 – 15 of 15 1 Improving tokenisation by alternative treatment of spaces Gow-Smith, E.; Scarton, C.; Madabushi, H.T.. - 2022 BASE Show details 2 The (un)suitability of automatic evaluation metrics for text simplification Alva-Manchego, F.; Scarton, C.; Specia, L.. - : MIT Press, 2021 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 Multistage BiCross encoder for multilingual access to COVID-19 health information Singh, I.; Scarton, C.; Bontcheva, K.. - : Public Library of Science, 2021 BASE Show details 6 The false COVID-19 narratives that keep being debunked : a spatiotemporal analysis Singh, I.; Bontcheva, K.; Scarton, C.. - 2021 BASE Show details 7 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 8 ASSET : a dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations Alva-Manchego, F.; Martin, L.; Bordes, A.; Scarton, C.; Sagot, B.; Specia, L.. - 2020 Abstract: In order to simplify a sentence, human editors perform multiple rewriting transformations: they split it into several shorter sentences, paraphrase words (i.e. replacing complex words or phrases by simpler synonyms), reorder components, and/or delete information deemed unnecessary. Despite these varied range of possible text alterations, current models for automatic sentence simplification are evaluated using datasets that are focused on a single transformation, such as lexical paraphrasing or splitting. This makes it impossible to understand the ability of simplification models in more realistic settings. To alleviate this limitation, this paper introduces ASSET, a new dataset for assessing sentence simplification in English. ASSET is a crowdsourced multi-reference corpus where each simplification was produced by executing several rewriting transformations. Through quantitative and qualitative experiments, we show that simplifications in ASSET are better at capturing characteristics of simplicity when compared to other standard evaluation datasets for the task. Furthermore, we motivate the need for developing better methods for automatic evaluation using ASSET, since we show that current popular metrics may not be suitable when multiple simplification transformations are performed. URL: https://arxiv.org/abs/2005.00481v1 http://eprints.whiterose.ac.uk/160696/1/2005.00481v1.pdf http://eprints.whiterose.ac.uk/160696/ BASE Hide details 9 Toxic language detection in social media for Brazilian Portuguese : new dataset and multilingual analysis Leite, J.A.; Silva, D.F.; Bontcheva, K.. - : Association for Computational Linguistics (ACL), 2020 BASE Show details 10 Measuring what counts : the case of rumour stance classification Scarton, C.; Silva, D.F.; Bontcheva, K.. - : Association for Computational Linguistics (ACL), 2020 BASE Show details 11 Data-driven sentence simplification: Survey and benchmark Alva-Manchego, F.; Scarton, C.; Specia, L.. - : MIT Press, 2020 BASE Show details 12 EASSE: easier automatic sentence simplification evaluation Alva-Manchego, F.; Martin, L.; Scarton, C.. - : Association for Computational Linguistics, 2019 BASE Show details 13 Exploring gap filling as a cheaper alternative to reading comprehension questionnaires when evaluating machine translation for gisting Forcada, M.L.; Scarton, C.; Specia, L.. - : ACL, 2018 BASE Show details 14 Multi-level translation quality prediction with QuEst++ Specia, L.; Paetzold, G.H.; Scarton, C.. - : Association for Computational Linguistics (ACL), 2015 BASE Show details 15 Automatic classification of written descriptions by healthy adults: An overview of the application of natural language processing and machine learning techniques to clinical discourse analysis Toledo, C.M.; Cunha, A.; Scarton, C.. - : Associação Neurologia Cognitiva e do Comportamento, 2014 BASE Show details

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