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Found 3 papers, 2 papers with code
Overcoming the Curse of Sentence Length for Neural Machine Translation using Automatic Segmentation
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 long sentences, unlike existing phrase-based translation systems.
On the Properties of Neural Machine Translation: Encoder-Decoder Approaches
In this paper, we focus on analyzing the properties of the neural machine translation using two models; RNN Encoder--Decoder and a newly proposed gated recursive convolutional neural network.
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN).
Ranked #47 on
Machine Translation
on WMT2014 English-French
