Understanding which information is encoded in deep models of spoken and
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Artificial learners often behave differently from human learners in the
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We introduce DivEMT, the first publicly available post-editing study of
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Massively multilingual models are promising for transfer learning across...
Identifying factors that make certain languages harder to model than oth...
Natural languages commonly display a trade-off among different strategie...
Recent advances in the field of multilingual dependency parsing have bro...
It is now established that modern neural language models can be successf...
The transformer-based pre-trained language model BERT has helped to impr...
We investigate whether off-the-shelf deep bidirectional sentence
represe...
Recent work has shown that recurrent neural networks (RNNs) can implicit...
Neural Machine Translation (NMT) has been widely used in recent years wi...
Intelligent selection of training data has proven a successful technique...
Distributed word representations are widely used for modeling words in N...
The quality of a Neural Machine Translation system depends substantially...
Within the field of Statistical Machine Translation (SMT), the neural
ap...
Recurrent Neural Networks (RNN) have obtained excellent result in many
n...
Word reordering is one of the most difficult aspects of statistical mach...