Jun 3, 2014 ¡¤ In this paper, we propose a novel neural network model called RNN Encoder-Decoder that consists of two recurrent neural networks (RNN).

Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation. In Proceedings of the 2014 Conference on Empirical Methods in ...

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

The proposed RNN Encoder‐Decoder model learns a semantically and syntactically meaningful representation of linguistic phrases.

Learning phrase representations using RNN encoder-decoder for statistical machine translation. / Cho, Kyunghyun; van Merrienboer, B; Gulcehre, Caglar et al.

Tutorials on implementing a few sequence-to-sequence (seq2seq) models with PyTorch and TorchText. - pytorch-seq2seq/2 - Learning Phrase Representations ...

Oct 9, 2021 ¡¤ RNN Encoder-Decoder is able to propose well-formed target phrases without looking at the actual phrase table.

Apr 28, 2022 ¡¤ Learning Phrase Representations Using RNN Encoder–Decoder for Statistical Machine ...
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Posted: Apr 28, 2022

Sep 3, 2014 ¡¤ We evaluated the proposed model with the task of statistical machine translation, where we used the RNN Encoder–Decoder to score each phrase.

Aug 6, 2021 ¡¤ Bibliographic details on Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation.