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• W2964022663 abstract "Recognizing that even correct translations are not always semantically equivalent, we automatically detect meaning divergences in parallel sentence pairs with a deep neural model of bilingual semantic similarity which can be trained for any parallel corpus without any manual annotation. We show that our semantic model detects divergences more accurately than models based on surface features derived from word alignments, and that these divergences matter for neural machine translation." @default.
• W2964022663 created "2019-07-30" @default.
• W2964022663 creator A5008851653 @default.
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• W2964022663 date "2018-01-01" @default.
• W2964022663 modified "2023-10-10" @default.
• W2964022663 title "Identifying Semantic Divergences in Parallel Text without Annotations" @default.
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• W2964022663 doi "https://doi.org/10.18653/v1/n18-1136" @default.
• W2964022663 hasPublicationYear "2018" @default.
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