AIScientist: Toward Automated Literature Understanding and Scientific Discovery
Date:
Due to the rapid growth of publications varying in quality, there exists a pressing need to help scientists digest and evaluate relevant papers, thereby facilitating scientific discovery. This talk aims to provide an overview of the AI-assisted scientific paper lifecycle, detailing how machines can augment every stage of the research process for the scientist, including scientific literature understanding, experiment development, manuscript draft writing, and finally draft evaluation. I will first cover fine-grained few-shot scientific entity extraction and then show how the extracted knowledge graph can be applied to scientific literature review and scientific hypothesis discovery.