Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Practical Comparable Data Collection for Low-Resource Languages via
  Images   We propose a method of curating high-quality comparable training data for
low-resource languages with monolingual annotators. Our method involves using a
carefully selected set of images as a pivot between the source and target
languages by getting captions for such images in both languages independently.
Human evaluations on the English-Hindi comparable corpora created with our
method show that 81.1% of the pairs are acceptable translations, and only 2.47%
of the pairs are not translations at all. We further establish the potential of
the dataset collected through our approach by experimenting on two downstream
tasks - machine translation and dictionary extraction. All code and data are
available at https://github.com/madaan/PML4DC-Comparable-Data-Collection.

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The categories of this paper are: math-ph
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The categories of this paper are: q-fin
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The categories of this paper are: hep-ex
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The categories of this paper are: patt-sol
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The categories of this paper are: econ
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The categories of this paper are: chem-ph
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The categories of this paper are: acc-phys
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The categories of this paper are: quant-ph
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The categories of this paper are: hep-th
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The categories of this paper are: hep-ph
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The categories of this paper are: stat
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The categories of this paper are: q-alg
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The categories of this paper are: cond-mat
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The categories of this paper are: nucl-ex
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The categories of this paper are: chao-dyn
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The categories of this paper are: comp-gas