Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Style Transfer from Non-Parallel Text by Cross-Alignment   This paper focuses on style transfer on the basis of non-parallel text. This
is an instance of a broad family of problems including machine translation,
decipherment, and sentiment modification. The key challenge is to separate the
content from other aspects such as style. We assume a shared latent content
distribution across different text corpora, and propose a method that leverages
refined alignment of latent representations to perform style transfer. The
transferred sentences from one style should match example sentences from the
other style as a population. We demonstrate the effectiveness of this
cross-alignment method on three tasks: sentiment modification, decipherment of
word substitution ciphers, and recovery of word order.

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The categories of this paper are: solv-int
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The categories of this paper are: adap-org
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The categories of this paper are: hep-ph
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The categories of this paper are: q-bio
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The categories of this paper are: alg-geom
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The categories of this paper are: hep-lat
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The categories of this paper are: nlin
30
The categories of this paper are: q-alg
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The categories of this paper are: chem-ph
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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: funct-an
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The categories of this paper are: cmp-lg
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The categories of this paper are: cond-mat
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The categories of this paper are: econ
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The categories of this paper are: hep-ex