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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 fixedlength vector representation, and the other decodes the representation into another sequence of symbols. The encoder and decoder of the proposed model are jointly trained to maximize the conditional probability of a target sequence given a source sequence. The performance of a statistical machine translationdoi:10.3115/v1/d14-1179 dblp:conf/emnlp/ChoMGBBSB14 fatcat:uiy743kyojcknh7pjgs4x33osa