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Multilingual Unsupervised Sentence Simplification
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In: https://hal.inria.fr/hal-03109299 ; 2021 (2021)
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Abstract:
Progress in Sentence Simplification has been hindered by the lack of supervised data, particularly in languages other than English. Previous work has aligned sentences from original and simplified corpora such as English Wikipedia and Simple English Wikipedia, but this limits corpus size, domain, and language. In this work, we propose using unsupervised mining techniques to automatically create training corpora for simplification in multiple languages from raw Common Crawl web data. When coupled with a controllable generation mechanism that can flexibly adjust attributes such as length and lexical complexity, these mined paraphrase corpora can be used to train simplification systems in any language. We further incorporate multilingual unsupervised pretraining methods to create even stronger models and show that by training on mined data rather than supervised corpora, we outperform the previous best results. We evaluate our approach on English, French, and Spanish simplification benchmarks and reach state-of-the-art performance with a totally unsupervised approach. We will release our models and code to mine the data in any language included in Common Crawl.
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Keyword:
[INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]
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URL: https://hal.inria.fr/hal-03109299
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Text Generation with and without Retrieval ; Génération de textes basés sur la connaissance avec et sans recherche
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In: https://hal.univ-lorraine.fr/tel-03542634 ; Computer Science [cs]. Université de Lorraine, 2021. English. ⟨NNT : 2021LORR0164⟩ (2021)
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Multilingual AMR-to-Text Generation
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In: 2020 Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-02999676 ; 2020 Conference on Empirical Methods in Natural Language Processing, Nov 2020, Punta Cana, Dominican Republic (2020)
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Augmenting Transformers with KNN-Based Composite Memory for Dialog
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In: EISSN: 2307-387X ; Transactions of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02999678 ; Transactions of the Association for Computational Linguistics, The MIT Press, In press, ⟨10.1162/tacl_a_00356⟩ ; https://transacl.org/index.php/tacl (2020)
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