132 citations · 186 across the 15 of their papers we have counts for
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Selecting Artificially-Generated Sentences for Fine-Tuning Neural Machine Translation
Alberto Poncelas, Andy Way
Neural Machine Translation (NMT) models tend to achieve best performance when larger sets of parallel sentences are provided for training. For this reason, augmenting the training…
Combining SMT and NMT Back-Translated Data for Efficient NMT
Alberto Poncelas, Maja Popovic, Dimitar Shterionov +2
Neural Machine Translation (NMT) models achieve their best performance when large sets of parallel data are used for training. Consequently, techniques for augmenting the training…
Transductive Data-Selection Algorithms for Fine-Tuning Neural Machine Translation
Alberto Poncelas, Gideon Maillette de Buy Wenniger, Andy Way
Machine Translation models are trained to translate a variety of documents from one language into another. However, models specifically trained for a particular characteristics of…
Adaptation of Machine Translation Models with Back-translated Data using Transductive Data Selection Methods
Alberto Poncelas, Gideon Maillette de Buy Wenniger, Andy Way
Data selection has proven its merit for improving Neural Machine Translation (NMT), when applied to authentic data. But the benefit of using synthetic data in NMT training, produce…
ABI Neural Ensemble Model for Gender Prediction Adapt Bar-Ilan Submission for the CLIN29 Shared Task on Gender Prediction
Eva Vanmassenhove, Amit Moryossef, Alberto Poncelas +2
We present our system for the CLIN29 shared task on cross-genre gender detection for Dutch. We experimented with a multitude of neural models (CNN, RNN, LSTM, etc.), more "traditio…