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Pre-trained language models have attracted increasing attention in the biomedical domain, inspired by their great success in the general natural language domain. Among the two main branches of pre-trained language models in the general language domain, i.e. BERT (and its variants) and GPT (and its variants), the first one has been extensively studied in the biomedical domain, such as BioBERT and PubMedBERT, while the second one is under explored. In this talk, we will show how a generative langauge model, BioGPT, together with fine-tuning, can be used for biomedical relation extraction, quesion answering, document classification and generating descriptions for biomedical terms. In particular, BioGPT is the first to achieve human-level performance on the PubMedQA task.
Presented by:
Renqian Luo, Researcher at Microsoft Research
Yingce Xia, Senior Researcher at Microsoft Research
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