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        <namePart type="given">Ruslan</namePart>
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    <abstract>Data-to-text (D2T) generation in the biomedical domain is a promising - yet mostly unexplored - field of research. Here, we apply neural models for D2T generation to a real-world dataset consisting of package leaflets of European medicines. We show that fine-tuned transformers are able to generate realistic, multi-sentence text from data in the biomedical domain, yet have important limitations. We also release a new dataset (BioLeaflets) for benchmarking D2T generation models in the biomedical domain.</abstract>
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%0 Conference Proceedings
%T Biomedical Data-to-Text Generation via Fine-Tuning Transformers
%A Yermakov, Ruslan
%A Drago, Nicholas
%A Ziletti, Angelo
%Y Belz, Anya
%Y Fan, Angela
%Y Reiter, Ehud
%Y Sripada, Yaji
%S Proceedings of the 14th International Conference on Natural Language Generation
%D 2021
%8 August
%I Association for Computational Linguistics
%C Aberdeen, Scotland, UK
%F yermakov-etal-2021-biomedical
%X Data-to-text (D2T) generation in the biomedical domain is a promising - yet mostly unexplored - field of research. Here, we apply neural models for D2T generation to a real-world dataset consisting of package leaflets of European medicines. We show that fine-tuned transformers are able to generate realistic, multi-sentence text from data in the biomedical domain, yet have important limitations. We also release a new dataset (BioLeaflets) for benchmarking D2T generation models in the biomedical domain.
%R 10.18653/v1/2021.inlg-1.40
%U https://aclanthology.org/2021.inlg-1.40
%U https://doi.org/10.18653/v1/2021.inlg-1.40
%P 364-370

Markdown (Informal)

[Biomedical Data-to-Text Generation via Fine-Tuning Transformers](https://aclanthology.org/2021.inlg-1.40) (Yermakov et al., INLG 2021)

• Biomedical Data-to-Text Generation via Fine-Tuning Transformers (Yermakov et al., INLG 2021)

ACL

• Ruslan Yermakov, Nicholas Drago, and Angelo Ziletti. 2021. Biomedical Data-to-Text Generation via Fine-Tuning Transformers. In Proceedings of the 14th International Conference on Natural Language Generation, pages 364–370, Aberdeen, Scotland, UK. Association for Computational Linguistics.