Papers by Laure Merat

1 papers
The Learnability of the Annotated Input in NMT Replicating (Vanmassenhove and Way, 2018) with OpenNMT (2020.lrec-1)

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Challenge: reproducibility of experiments is a key issue in Neural Networks, which are fed with variable samples of training data.
Approach: They reproduce some of the experiments related to neural network training for Machine Translation as reported in . they annotated a sample from the EN-FR and EN-DE Europarl with syntactic and semantic annotations to train neural networks with the Nematus Neural Machine Translation toolkit.
Outcome: The results obtained were lower than the original paper, but on a more limited set of annotations.

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