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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 – 7 of 7 1 The (un)suitability of automatic evaluation metrics for text simplification Alva-Manchego, F.; Scarton, C.; Specia, L.. - : MIT Press, 2021 BASE Show details 2 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 3 ASSET : a dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations Alva-Manchego, F.; Martin, L.; Bordes, A.. - 2020 BASE Show details 4 Data-driven sentence simplification: Survey and benchmark Alva-Manchego, F.; Scarton, C.; Specia, L.. - : MIT Press, 2020 Abstract: Sentence Simplification (SS) aims to modify a sentence in order to make it easier to read and understand. In order to do so, several rewriting transformations can be performed such as replacement, reordering, and splitting. Executing these transformations while keeping sentences grammatical, preserving their main idea, and generating simpler output, is a challenging and still far from solved problem. In this article, we survey research on SS, focusing on approaches that attempt to learn how to simplify using corpora of aligned original-simplified sentence pairs in English, which is the dominant paradigm nowadays. We also include a benchmark of different approaches on common datasets so as to compare them and highlight their strengths and limitations. We expect that this survey will serve as a starting point for researchers interested in the task and help spark new ideas for future developments. URL: https://eprints.whiterose.ac.uk/158279/8/coli_a_00370.pdf https://eprints.whiterose.ac.uk/158279/ BASE Hide details 5 EASSE: easier automatic sentence simplification evaluation Alva-Manchego, F.; Martin, L.; Scarton, C.. - : Association for Computational Linguistics, 2019 BASE Show details 6 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 7 Multi-level translation quality prediction with QuEst++ Specia, L.; Paetzold, G.H.; Scarton, C.. - : Association for Computational Linguistics (ACL), 2015 BASE Show details

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