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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 Rethinking Automatic Evaluation in Sentence Simplification Scialom, Thomas; Martin, Louis; Staiano, Jacopo... In: https://hal.inria.fr/hal-03199901 ; 2021 (2021) BASE Show details 2 Multilingual Unsupervised Sentence Simplification Martin, Louis; Fan, Angela; de la Clergerie, Éric... In: https://hal.inria.fr/hal-03109299 ; 2021 (2021) BASE Show details 3 MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases ... Martin, Louis; Fan, Angela; de la Clergerie, Éric. - : arXiv, 2020 BASE Show details 4 ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations ... Alva-Manchego, Fernando; Martin, Louis; Bordes, Antoine; Scarton, Carolina; Sagot, Benoît; Specia, Lucia. - : arXiv, 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 ... : Accepted to ACL 2020 (camera-ready version) ... Keyword: Computation and Language cs.CL; FOS Computer and information sciences URL: https://arxiv.org/abs/2005.00481 https://dx.doi.org/10.48550/arxiv.2005.00481 BASE Hide details 5 Controllable Sentence Simplification Martin, Louis; Sagot, Benoît; Villemonte de La Clergerie, Éric... In: https://hal.inria.fr/hal-02445874 ; 2019 (2019) BASE Show details 6 CamemBERT: a Tasty French Language Model Martin, Louis; Muller, Benjamin; Ortiz Suárez, Pedro Javier... In: https://hal.inria.fr/hal-02445946 ; 2019 (2019) BASE Show details 7 Controllable Sentence Simplification ... Martin, Louis; Sagot, Benoît; de la Clergerie, Éric. - : arXiv, 2019 BASE Show details

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