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Between words and characters: A Brief History of Open-Vocabulary Modeling and Tokenization in NLP
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In: https://hal.inria.fr/hal-03540069 ; 2022 (2022)
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Automatic Normalisation of Early Modern French
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In: https://hal.inria.fr/hal-03540226 ; 2022 (2022)
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From FreEM to D'AlemBERT ; From FreEM to D'AlemBERT: a Large Corpus and a Language Model for Early Modern French
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In: Proceedings of the 13th Language Resources and Evaluation Conference ; https://hal.inria.fr/hal-03596653 ; Proceedings of the 13th Language Resources and Evaluation Conference, European Language Resources Association, Jun 2022, Marseille, France (2022)
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Towards a Cleaner Document-Oriented Multilingual Crawled Corpus
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In: https://hal.inria.fr/hal-03536361 ; 2022 (2022)
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Probing Multilingual Cognate Prediction Models
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In: Findings of the Association for Computational Linguistics: ACL 2022 ; https://hal.inria.fr/hal-03614691 ; Findings of the Association for Computational Linguistics: ACL 2022, May 2022, Dublin, Ireland (2022)
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Can Character-based Language Models Improve Downstream Task Performance in Low-Resource and Noisy Language Scenarios?
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In: Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021) ; https://hal.inria.fr/hal-03527328 ; Seventh Workshop on Noisy User-generated Text (W-NUT 2021, colocated with EMNLP 2021), Jan 2022, punta cana, Dominican Republic ; https://aclanthology.org/2021.wnut-1.47/ (2022)
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Towards a Cleaner Document-Oriented Multilingual Crawled Corpus ...
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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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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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Ungoliant: An Optimized Pipeline for the Generation of a Very Large-Scale Multilingual Web Corpus
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In: CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora ; https://hal.inria.fr/hal-03301590 ; CMLC 2021 - 9th Workshop on Challenges in the Management of Large Corpora, Jul 2021, Limerick / Virtual, Ireland. ⟨10.14618/ids-pub-10468⟩ ; https://www.cl2021.org/ (2021)
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First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
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In: https://hal.inria.fr/hal-03161685 ; 2021 (2021)
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Can Multilingual Language Models Transfer to an Unseen Dialect? A Case Study on North African Arabizi
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In: https://hal.inria.fr/hal-03161677 ; 2021 (2021)
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First Align, then Predict: Understanding the Cross-Lingual Ability of Multilingual BERT
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In: EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03239087 ; EACL 2021 - The 16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kyiv / Virtual, Ukraine ; https://2021.eacl.org/ (2021)
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When Being Unseen from mBERT is just the Beginning: Handling New Languages With Multilingual Language Models
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In: NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies ; https://hal.inria.fr/hal-03251105 ; NAACL-HLT 2021 - 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Jun 2021, Mexico City, Mexico (2021)
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Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets
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In: https://hal.inria.fr/hal-03177623 ; 2021 (2021)
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Can Cognate Prediction Be Modelled as a Low-Resource Machine Translation Task?
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In: Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 ; https://hal.inria.fr/hal-03243380 ; Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Aug 2021, Bangkok, Thailand (2021)
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Synthetic Data Augmentation for Zero-Shot Cross-Lingual Question Answering
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In: https://hal.inria.fr/hal-03109187 ; 2021 (2021)
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Variation graphique dans les documents d'Ancien Régime : Nouvelles approches scriptométriques
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In: Journée d’étude : « Pour une histoire de la langue ‘par en bas’: textes privés et variation des langues dans le passé » ; https://hal.inria.fr/hal-03357080 ; Journée d’étude : « Pour une histoire de la langue ‘par en bas’: textes privés et variation des langues dans le passé », Sep 2021, Paris, France (2021)
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Expanding the content model of annotationBlock
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In: Next Gen TEI, 2021 - TEI Conference and Members’ Meeting ; https://hal.archives-ouvertes.fr/hal-03380805 ; Next Gen TEI, 2021 - TEI Conference and Members’ Meeting, Oct 2021, Virtual, United States (2021)
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