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Can Machines Learn to Comprehend Scientific Literature?
2019
IEEE Access
To measure the ability of a machine to understand professional-level scientific articles, we construct a scientific question answering task called PaperQA. The PaperQA task is based on more than 80 000 "fill-in-the-blank" type questions on articles from reputed scientific journals such as Nature and Science. We perform fine-grained linguistic analysis and evaluation to compare PaperQA and other conventional question and answering (QA) tasks on general literature (e.g., books, news articles, and
doi:10.1109/access.2019.2891666
fatcat:t35pl7o7pvdmhh2ehullgow2di