%0 Generic %1 Long2021 %A Phan, Long %A Anibal, J. %A Tran, H. %A Chanana, Shaurya %A Bahadroglu, Erol %A Peltekian, A. %A Altan-Bonnet, G. %D 2021 %J ArXiv %K SciFive BiomedicalNLP T5 TextTransformer posted_with_chatgpt %T SciFive: a text-to-text transformer model for biomedical literature %U https://www.semanticscholar.org/paper/6003d268e9b5230dbc3e320497b50329d6186816 %V abs/2106.03598 %X In this report, we introduce SciFive, a domain-specific T5 model that has been pre-trained on large biomedical corpora. Our model outperforms the current SOTA methods (i.e. BERT, BioBERT, Base T5) on tasks in named entity relation, relation extraction, natural language inference, and question-answering. We show that text-generation methods have significant potential in a broad array of biomedical NLP tasks, particularly those requiring longer, more complex outputs. Our results support the exploration of more difficult text generation tasks and the development of new methods in this area

@JournalArticle{Long2021, abstract = {In this report, we introduce SciFive, a domain-specific T5 model that has been pre-trained on large biomedical corpora. Our model outperforms the current SOTA methods (i.e. BERT, BioBERT, Base T5) on tasks in named entity relation, relation extraction, natural language inference, and question-answering. We show that text-generation methods have significant potential in a broad array of biomedical NLP tasks, particularly those requiring longer, more complex outputs. Our results support the exploration of more difficult text generation tasks and the development of new methods in this area}, added-at = {2024-01-06T15:48:31.000+0100}, author = {Phan, Long and Anibal, J. and Tran, H. and Chanana, Shaurya and Bahadroglu, Erol and Peltekian, A. and Altan-Bonnet, G.}, biburl = {https://www.bibsonomy.org/bibtex/2f2018dbccd16f3d1c87a0d12a92fbc0f/tomvoelker}, day = 28, description = {SciFive is introduced, a domain-specific T5 model that has been pre-trained on large biomedical corpora and outperforms the current SOTA methods on tasks in named entity relation, relation extraction, natural language inference, and question-answering.}, interhash = {9ad41b463866e22aad3d4a013b897147}, intrahash = {f2018dbccd16f3d1c87a0d12a92fbc0f}, journal = {ArXiv}, keywords = {SciFive BiomedicalNLP T5 TextTransformer posted_with_chatgpt}, month = {5}, timestamp = {2024-01-06T15:48:31.000+0100}, title = {SciFive: a text-to-text transformer model for biomedical literature}, url = {https://www.semanticscholar.org/paper/6003d268e9b5230dbc3e320497b50329d6186816}, volume = {abs/2106.03598}, year = 2021 }