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        <title>BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP</title>
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        <namePart type="given">Pablo</namePart>
        <namePart type="given">Botton</namePart>
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        <namePart type="given">Matheus</namePart>
        <namePart type="given">Camasmie</namePart>
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    <name type="personal">
        <namePart type="given">Samuel</namePart>
        <namePart type="given">Caetano</namePart>
        <namePart type="family">Silva</namePart>
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            <namePart type="given">Ruslan</namePart>
            <namePart type="family">Mitkov</namePart>
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            <namePart type="given">Galia</namePart>
            <namePart type="family">Angelova</namePart>
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    <abstract>Transformer-based language models such as Bidirectional Encoder Representations from Transformers (BERT) are now mainstream in the NLP field, but extensions to languages other than English, to new domains and/or to more specific text genres are still in demand. In this paper we introduced BERTabaporu, a BERT language model that has been pre-trained on Twitter data in the Brazilian Portuguese language. The model is shown to outperform the best-known general-purpose model for this language in three Twitter-related NLP tasks, making a potentially useful resource for Portuguese NLP in general.</abstract>
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        <date>2023-09</date>
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%0 Conference Proceedings
%T BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP
%A Costa, Pablo Botton
%A Pavan, Matheus Camasmie
%A Santos, Wesley Ramos
%A Silva, Samuel Caetano
%A Paraboni, Ivandré
%Y Mitkov, Ruslan
%Y Angelova, Galia
%S Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing
%D 2023
%8 September
%I INCOMA Ltd., Shoumen, Bulgaria
%C Varna, Bulgaria
%F costa-etal-2023-bertabaporu
%X Transformer-based language models such as Bidirectional Encoder Representations from Transformers (BERT) are now mainstream in the NLP field, but extensions to languages other than English, to new domains and/or to more specific text genres are still in demand. In this paper we introduced BERTabaporu, a BERT language model that has been pre-trained on Twitter data in the Brazilian Portuguese language. The model is shown to outperform the best-known general-purpose model for this language in three Twitter-related NLP tasks, making a potentially useful resource for Portuguese NLP in general.
%U https://aclanthology.org/2023.ranlp-1.24
%P 217-223

Markdown (Informal)

[BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP](https://aclanthology.org/2023.ranlp-1.24) (Costa et al., RANLP 2023)

• BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP (Costa et al., RANLP 2023)

ACL

• Pablo Botton Costa, Matheus Camasmie Pavan, Wesley Ramos Santos, Samuel Caetano Silva, and Ivandré Paraboni. 2023. BERTabaporu: Assessing a Genre-Specific Language Model for Portuguese NLP. In Proceedings of the 14th International Conference on Recent Advances in Natural Language Processing, pages 217–223, Varna, Bulgaria. INCOMA Ltd., Shoumen, Bulgaria.