Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multilingual Document-Level Translation Enables Zero-Shot Transfer From
  Sentences to Documents   Document-level neural machine translation (DocNMT) delivers coherent
translations by incorporating cross-sentence context. However, for most
language pairs there's a shortage of parallel documents, although parallel
sentences are readily available. In this paper, we study whether and how
contextual modeling in DocNMT is transferable from sentences to documents in a
zero-shot fashion (i.e. no parallel documents for student languages) through
multilingual modeling. Using simple concatenation-based DocNMT, we explore the
effect of 3 factors on multilingual transfer: the number of document-supervised
teacher languages, the data schedule for parallel documents at training, and
the data condition of parallel documents (genuine vs. backtranslated). Our
experiments on Europarl-7 and IWSLT-10 datasets show the feasibility of
multilingual transfer for DocNMT, particularly on document-specific metrics. We
observe that more teacher languages and adequate data schedule both contribute
to better transfer quality. Surprisingly, the transfer is less sensitive to the
data condition and multilingual DocNMT achieves comparable performance with
both back-translated and genuine document pairs.

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The categories of this paper are: q-alg
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The categories of this paper are: eess
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The categories of this paper are: bayes-an
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The categories of this paper are: cond-mat
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The categories of this paper are: q-fin
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The categories of this paper are: astro-ph
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The categories of this paper are: stat
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The categories of this paper are: funct-an
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The categories of this paper are: physics
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The categories of this paper are: acc-phys
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The categories of this paper are: hep-ph
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The categories of this paper are: atom-ph
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The categories of this paper are: gr-qc
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The categories of this paper are: math-ph
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The categories of this paper are: chao-dyn
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The categories of this paper are: patt-sol