Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Multilingual Unsupervised Neural Machine Translation with Denoising
  Adapters   We consider the problem of multilingual unsupervised machine translation,
translating to and from languages that only have monolingual data by using
auxiliary parallel language pairs. For this problem the standard procedure so
far to leverage the monolingual data is back-translation, which is
computationally costly and hard to tune.
  In this paper we propose instead to use denoising adapters, adapter layers
with a denoising objective, on top of pre-trained mBART-50. In addition to the
modularity and flexibility of such an approach we show that the resulting
translations are on-par with back-translating as measured by BLEU, and
furthermore it allows adding unseen languages incrementally.

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The categories of this paper are: q-bio
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The categories of this paper are: nlin
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The categories of this paper are: hep-th
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The categories of this paper are: adap-org
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The categories of this paper are: cmp-lg
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The categories of this paper are: math
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The categories of this paper are: hep-lat
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The categories of this paper are: cond-mat
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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: gr-qc
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The categories of this paper are: plasm-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: alg-geom
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The categories of this paper are: bayes-an