Ruslan Yermakov


2021

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Biomedical Data-to-Text Generation via Fine-Tuning Transformers
Ruslan Yermakov | Nicholas Drago | Angelo Ziletti
Proceedings of the 14th International Conference on Natural Language Generation

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.