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Controllable Sentence Simplification

Abstract : Text simplification aims at making a text easier to read and understand by simplifying grammar and structure while keeping the underlying information identical. It is often considered an all-purpose generic task where the same simplification is suitable for all; however multiple audiences can benefit from simplified text in different ways. We adapt a discrete parametrization mechanism that provides explicit control on simplification systems based on Sequence-to-Sequence models. As a result, users can condition the simplifications returned by a model on attributes such as length, amount of paraphrasing, lexical complexity and syntactic complexity. We also show that carefully chosen values of these attributes allow out-of-the-box Sequence-to-Sequence models to outperform their standard counterparts on simplification benchmarks. Our model, which we call ACCESS (as shorthand for AudienCe-CEntric Sentence Simplification), establishes the state of the art at 41.87 SARI on the WikiLarge test set, a +1.42 improvement over the best previously reported score.
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https://hal.inria.fr/hal-02678214
Contributor : Benoît Sagot <>
Submitted on : Sunday, May 31, 2020 - 8:12:26 PM
Last modification on : Thursday, January 14, 2021 - 3:14:10 PM

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  • HAL Id : hal-02678214, version 1

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Louis Martin, Éric Villemonte de la Clergerie, Benoît Sagot, Antoine Bordes. Controllable Sentence Simplification. LREC 2020 - 12th Language Resources and Evaluation Conference, May 2020, Marseille, France. ⟨hal-02678214⟩

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