  We present CAiRE-COVID, a real-time question answering (QA) and
multi-document summarization system, which won one of the 10 tasks in the
Kaggle COVID-19 Open Research Dataset Challenge, judged by medical experts. Our
system aims to tackle the recent challenge of mining the numerous scientific
articles being published on COVID-19 by answering high priority questions from
the community and summarizing salient question-related information. It combines
information extraction with state-of-the-art QA and query-focused
multi-document summarization techniques, selecting and highlighting evidence
snippets from existing literature given a query. We also propose query-focused
abstractive and extractive multi-document summarization methods, to provide
more relevant information related to the question. We further conduct
quantitative experiments that show consistent improvements on various metrics
for each module. We have launched our website CAiRE-COVID for broader use by
the medical community, and have open-sourced the code for our system, to
bootstrap further study by other researches.
