Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Medical Literature Mining and Retrieval in a Conversational Setting   The Covid-19 pandemic has caused a spur in the medical research literature.
With new research advances in understanding the virus, there is a need for
robust text mining tools which can process, extract and present answers from
the literature in a concise and consumable way. With a DialoGPT based
multi-turn conversation generation module, and BM-25 \& neural embeddings based
ensemble information retrieval module, in this paper we present a
conversational system, which can retrieve and answer coronavirus-related
queries from the rich medical literature, and present it in a conversational
setting with the user. We further perform experiments to compare neural
embedding-based document retrieval and the traditional BM25 retrieval algorithm
and report the results.

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The categories of this paper are: atom-ph
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The categories of this paper are: q-fin
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The categories of this paper are: dg-ga
9
The categories of this paper are: nlin
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The categories of this paper are: mtrl-th
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The categories of this paper are: adap-org
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The categories of this paper are: econ
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The categories of this paper are: quant-ph
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The categories of this paper are: stat
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The categories of this paper are: solv-int
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The categories of this paper are: q-bio
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The categories of this paper are: funct-an
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The categories of this paper are: physics
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The categories of this paper are: cmp-lg
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The categories of this paper are: math-ph
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The categories of this paper are: chem-ph