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BioBART: Pretraining and Evaluation of A Biomedical Generative Language Model
[article]
2022
arXiv
pre-print
Pretrained language models have served as important backbones for natural language processing. Recently, in-domain pretraining has been shown to benefit various domain-specific downstream tasks. In the biomedical domain, natural language generation (NLG) tasks are of critical importance, while understudied. Approaching natural language understanding (NLU) tasks as NLG achieves satisfying performance in the general domain through constrained language generation or language prompting. We
arXiv:2204.03905v2
fatcat:sdczfns265ezplidcz5mcebkee