Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Incorporating Both Distributional and Relational Semantics in Word
  Representations   We investigate the hypothesis that word representations ought to incorporate
both distributional and relational semantics. To this end, we employ the
Alternating Direction Method of Multipliers (ADMM), which flexibly optimizes a
distributional objective on raw text and a relational objective on WordNet.
Preliminary results on knowledge base completion, analogy tests, and parsing
show that word representations trained on both objectives can give improvements
in some cases.

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The categories of this paper are: physics
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The categories of this paper are: q-alg
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The categories of this paper are: cmp-lg
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The categories of this paper are: hep-th
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The categories of this paper are: quant-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: bayes-an
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The categories of this paper are: hep-ph
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The categories of this paper are: mtrl-th
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The categories of this paper are: alg-geom
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The categories of this paper are: dg-ga
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The categories of this paper are: solv-int
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The categories of this paper are: cond-mat
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The categories of this paper are: hep-lat
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The categories of this paper are: nlin
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The categories of this paper are: hep-ex