Zero-Shot Dual Machine Translation

arXiv: Computation and Language, Volume abs/1805.10338, 2018.

Cited by: 9|Views24
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Abstract:

Neural Machine Translation (NMT) systems rely on large amounts of parallel data. This is a major challenge for low-resource languages. Building on recent work on unsupervised and semi-supervised methods, we present an approach that combines zero-shot and dual learning. The latter relies on reinforcement learning, to exploit the duality of...More

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