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Embedding Word Similarity with Neural Machine Translation
Felix Hill, Kyunghyun Cho, Sebastien Jean +2
Neural language models learn word representations, or embeddings, that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural mach…
Ensemble of Generative and Discriminative Techniques for Sentiment Analysis of Movie Reviews
Grégoire Mesnil, Tomas Mikolov, Marc'Aurelio Ranzato +1
Sentiment analysis is a common task in natural language processing that aims to detect polarity of a text document (typically a consumer review). In the simplest settings, we discr…
On Using Very Large Target Vocabulary for Neural Machine Translation
Sébastien Jean, Kyunghyun Cho, Roland Memisevic +1
Neural machine translation, a recently proposed approach to machine translation based purely on neural networks, has shown promising results compared to the existing approaches suc…
Not All Neural Embeddings are Born Equal
Felix Hill, KyungHyun Cho, Sebastien Jean +2
Neural language models learn word representations that capture rich linguistic and conceptual information. Here we investigate the embeddings learned by neural machine translation…
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
Kyunghyun Cho, Bart van Merrienboer, Dzmitry Bahdanau +1
Neural machine translation is a relatively new approach to statistical machine translation based purely on neural networks. The neural machine translation models often consist of a…
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
Jean Pouget-Abadie, Dzmitry Bahdanau, Bart van Merrienboer +2
The authors of (Cho et al., 2014a) have shown that the recently introduced neural network translation systems suffer from a significant drop in translation quality when translating…