Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: How Much is 131 Million Dollars? Putting Numbers in Perspective with
  Compositional Descriptions   How much is 131 million US dollars? To help readers put such numbers in
context, we propose a new task of automatically generating short descriptions
known as perspectives, e.g. "$131 million is about the cost to employ everyone
in Texas over a lunch period". First, we collect a dataset of numeric mentions
in news articles, where each mention is labeled with a set of rated
perspectives. We then propose a system to generate these descriptions
consisting of two steps: formula construction and description generation. In
construction, we compose formulae from numeric facts in a knowledge base and
rank the resulting formulas based on familiarity, numeric proximity and
semantic compatibility. In generation, we convert a formula into natural
language using a sequence-to-sequence recurrent neural network. Our system
obtains a 15.2% F1 improvement over a non-compositional baseline at formula
construction and a 12.5 BLEU point improvement over a baseline description
generation.

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The categories of this paper are: q-alg
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The categories of this paper are: hep-ex
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The categories of this paper are: nucl-th
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The categories of this paper are: solv-int
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The categories of this paper are: cmp-lg
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The categories of this paper are: econ
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The categories of this paper are: dg-ga
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The categories of this paper are: q-fin
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The categories of this paper are: quant-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: atom-ph
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The categories of this paper are: patt-sol
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The categories of this paper are: physics
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The categories of this paper are: math-ph
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The categories of this paper are: bayes-an
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The categories of this paper are: nucl-ex