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Rethinking Automatic Evaluation in Sentence Simplification
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In: https://hal.inria.fr/hal-03199901 ; 2021 (2021)
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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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MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases ...
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ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations ...
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Controllable Sentence Simplification
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In: https://hal.inria.fr/hal-02445874 ; 2019 (2019)
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CamemBERT: a Tasty French Language Model
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In: https://hal.inria.fr/hal-02445946 ; 2019 (2019)
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Abstract:
Web site: https://camembert-model.fr ; Pretrained language models are now ubiquitous in Natural Language Processing. Despite their success, most available models have either been trained on English data or on the concatenation of data in multiple languages. This makes practical use of such models—in all languages except English—very limited. Aiming to address this issue for French, we release CamemBERT, a French version of the Bi-directional Encoders for Transformers (BERT). We measure the performance of CamemBERT compared to multilingual models in multiple downstream tasks, namely part-of-speech tagging, dependency parsing, named-entity recognition, and natural language inference. CamemBERT improves the state of the art for most of the tasks considered. We release the pretrained model for CamemBERT hoping to foster research and downstream applications for French NLP.
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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-02445946
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