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SemEval-2022 Task 2: Multilingual Idiomaticity Detection and Sentence Embedding ...
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Improving Tokenisation by Alternative Treatment of Spaces ...
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NILC-Metrix: assessing the complexity of written and spoken language in Brazilian Portuguese ...
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Multistage BiCross encoder for multilingual access to COVID-19 health information ...
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Multistage BiCross encoder for multilingual access to COVID-19 health information
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In: PLoS One (2021)
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The (un)suitability of automatic evaluation metrics for text simplification
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ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations
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In: ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics ; https://hal.inria.fr/hal-02889823 ; ACL 2020 - 58th Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle / Virtual, United States (2020)
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Toxic Language Detection in Social Media for Brazilian Portuguese: New Dataset and Multilingual Analysis ...
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ASSET: A Dataset for Tuning and Evaluation of Sentence Simplification Models with Multiple Rewriting Transformations ...
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Linguistic analysis model for monitoring user reaction on satirical news for brazilian portuguese
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ASSET: A dataset for tuning and evaluation of sentence simplification models with multiple rewriting transformations
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Data-Driven Sentence Simplification: Survey and Benchmark
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In: Computational Linguistics, Vol 46, Iss 1, Pp 135-187 (2020) (2020)
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Text Simplification From Professionally Produced Corpora ...
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Abstract:
The lack of large and reliable datasets has been hindering progress in Text Simplification (TS). We investigate the application of the recently created Newsela corpus, the largest collection of professionally written simplifications available, in TS tasks. Using new alignment algorithms, we extract 550,644 complex-simple sentence pairs from the corpus. This data is explored in different ways: (i) we show that traditional readability metrics capture surprisingly well the different complexity levels in this corpus, (ii) we build machine learning models to classify sentences into complex vs. simple and to predict complexity levels that outperform their respective baselines, (iii) we introduce a lexical simplifier that uses the corpus to generate candidate simplifications and outperforms the state of the art approaches, and (iv) we show that the corpus can be used to learn sentence simplification patterns in more effective ways than corpora used in previous work. ...
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URL: https://zenodo.org/record/1410450 https://dx.doi.org/10.5281/zenodo.1410450
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SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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Text Simplification From Professionally Produced Corpora ...
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SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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SimPA: A Sentence-Level Simplification Corpus for the Public Administration Domain ...
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Sheffield submissions for the WMT18 quality estimation shared task
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In: 807 ; 813 (2018)
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