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    <abstract>We exploit the pre-trained seq2seq model mBART for multilingual text style transfer. Using machine translated data as well as gold aligned English sentences yields state-of-the-art results in the three target languages we consider. Besides, in view of the general scarcity of parallel data, we propose a modular approach for multilingual formality transfer, which consists of two training strategies that target adaptation to both language and task. Our approach achieves competitive performance without monolingual task-specific parallel data and can be applied to other style transfer tasks as well as to other languages.</abstract>
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%0 Conference Proceedings
%T Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer
%A Lai, Huiyuan
%A Toral, Antonio
%A Nissim, Malvina
%Y Muresan, Smaranda
%Y Nakov, Preslav
%Y Villavicencio, Aline
%S Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
%D 2022
%8 May
%I Association for Computational Linguistics
%C Dublin, Ireland
%F lai-etal-2022-multilingual
%X We exploit the pre-trained seq2seq model mBART for multilingual text style transfer. Using machine translated data as well as gold aligned English sentences yields state-of-the-art results in the three target languages we consider. Besides, in view of the general scarcity of parallel data, we propose a modular approach for multilingual formality transfer, which consists of two training strategies that target adaptation to both language and task. Our approach achieves competitive performance without monolingual task-specific parallel data and can be applied to other style transfer tasks as well as to other languages.
%R 10.18653/v1/2022.acl-short.29
%U https://aclanthology.org/2022.acl-short.29
%U https://doi.org/10.18653/v1/2022.acl-short.29
%P 262-271

Markdown (Informal)

[Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer](https://aclanthology.org/2022.acl-short.29) (Lai et al., ACL 2022)

• Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer (Lai et al., ACL 2022)

ACL

• Huiyuan Lai, Antonio Toral, and Malvina Nissim. 2022. Multilingual Pre-training with Language and Task Adaptation for Multilingual Text Style Transfer. In Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 262–271, Dublin, Ireland. Association for Computational Linguistics.