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Which Words Matter in Defining Phrase Reordering Behavior in Statistical Machine Translation?
Lexicalized and hierarchical reordering models use relative frequencies of fully lexicalized phrase pairs to learn phrase reordering distributions.
An empirical analysis of phrase-based and neural machine translation
We investigate the extent to which syntactic and lexical-semantic information from the source side is captured by hidden state representations of different neural MT architectures.
Classifying Wikipedia in a fine-grained hierarchy: what graphs can contribute
Wikipedia is a huge opportunity for machine learning, being the largest semi-structured base of knowledge available.
An Intrinsic Nearest Neighbor Analysis of Neural Machine Translation Architectures
We compare transformer and recurrent models in a more intrinsic way in terms of capturing lexical semantics and syntactic structures, in contrast to extrinsic approaches used by previous works.
What does Attention in Neural Machine Translation Pay Attention to?
Thus, the question still remains that how attention is similar or different from the traditional alignment.
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