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Domain Differential Adaptation for Neural Machine Translation

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Figure

Figure 1:Mean log probabilities of NMT modelsand LMs trained on law and medical domains forthe words (”needle”, ”hepatic”, ”complete”, ”justify”,”suspend”)
Table 1: Translation accuracy (BLEU; Papineni et al. (2002)) under different settings
Table 2: Performance of DDA-Deep when fusing dif-ferent parts of models on the law and medical datasets.
Table 3: Translation examples under the law to medi-cal adaptation setting.
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