Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Extracting Parallel Sentences with Bidirectional Recurrent Neural
  Networks to Improve Machine Translation   Parallel sentence extraction is a task addressing the data sparsity problem
found in multilingual natural language processing applications. We propose a
bidirectional recurrent neural network based approach to extract parallel
sentences from collections of multilingual texts. Our experiments with noisy
parallel corpora show that we can achieve promising results against a
competitive baseline by removing the need of specific feature engineering or
additional external resources. To justify the utility of our approach, we
extract sentence pairs from Wikipedia articles to train machine translation
systems and show significant improvements in translation performance.

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The categories of this paper are: cmp-lg
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The categories of this paper are: adap-org
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The categories of this paper are: chem-ph
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The categories of this paper are: math
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The categories of this paper are: q-fin
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The categories of this paper are: math-ph
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The categories of this paper are: hep-th
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The categories of this paper are: q-bio
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The categories of this paper are: astro-ph
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The categories of this paper are: comp-gas
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The categories of this paper are: bayes-an
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The categories of this paper are: alg-geom
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The categories of this paper are: supr-con
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The categories of this paper are: ao-sci
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The categories of this paper are: q-alg
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The categories of this paper are: hep-lat