Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Identifying Supporting Facts for Multi-hop Question Answering with
  Document Graph Networks   Recent advances in reading comprehension have resulted in models that surpass
human performance when the answer is contained in a single, continuous passage
of text. However, complex Question Answering (QA) typically requires multi-hop
reasoning - i.e. the integration of supporting facts from different sources, to
infer the correct answer. This paper proposes Document Graph Network (DGN), a
message passing architecture for the identification of supporting facts over a
graph-structured representation of text. The evaluation on HotpotQA shows that
DGN obtains competitive results when compared to a reading comprehension
baseline operating on raw text, confirming the relevance of structured
representations for supporting multi-hop reasoning.

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The categories of this paper are: hep-ex
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The categories of this paper are: eess
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The categories of this paper are: patt-sol
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The categories of this paper are: comp-gas
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The categories of this paper are: physics
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The categories of this paper are: hep-lat
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The categories of this paper are: cond-mat
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The categories of this paper are: gr-qc
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The categories of this paper are: quant-ph
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The categories of this paper are: math
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The categories of this paper are: dg-ga
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The categories of this paper are: chao-dyn
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The categories of this paper are: plasm-ph
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The categories of this paper are: econ
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The categories of this paper are: nlin
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The categories of this paper are: stat