Bi-Directional Differentiable Input Reconstruction for Low-Resource Neural Machine Translation

NAACL 2019 Xing NiuWeijia XuMarine Carpuat

We aim to better exploit the limited amounts of parallel text available in low-resource settings by introducing a differentiable reconstruction loss for neural machine translation (NMT). This loss compares original inputs to reconstructed inputs, obtained by back-translating translation hypotheses into the input language... (read more)

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