most citedLearning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

3.5k citations · 5.3k across the 5 of their papers we have counts for

collaborators

5 papers

cs.LG2016222 cited

An Actor-Critic Algorithm for Sequence Prediction

Dzmitry Bahdanau, Philemon Brakel, Kelvin Xu +5

We present an approach to training neural networks to generate sequences using actor-critic methods from reinforcement learning (RL). Current log-likelihood training methods are li…

cs.NE2014413 cited

End-to-end Continuous Speech Recognition using Attention-based Recurrent NN: First Results

Jan Chorowski, Dzmitry Bahdanau, Kyunghyun Cho +1

We replace the Hidden Markov Model (HMM) which is traditionally used in in continuous speech recognition with a bi-directional recurrent neural network encoder coupled to a recurre…

cs.CL20141.1k cited

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…

cs.CL2014

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…

cs.CL20143.5k cited

Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation

Kyunghyun Cho, Bart van Merrienboer, Caglar Gulcehre +4

In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN). One RNN encodes a sequence of symbols into a…