Papers with top-most layer

1 papers
Multi-layer Representation Fusion for Neural Machine Translation (C18-1)

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Challenge: Neural machine translation systems require a number of stacked layers for deep models, but the prediction depends on the sentence representation of the top-most layer with no access to low-level representations.
Approach: They propose a multi-layer representation fusion approach to fusing stacked layers to learn a better representation from the stack.
Outcome: The proposed approach yields 0.92 and 0.56 BLEU points over the strong Transformer baseline on IWSLT German-English and NIST Chinese-English MT tasks respectively.

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