6 days ago ¡¤ This paper introduces a novel neural network architecture called RNN Encoder-Decoder for improving phrase-based Statistical Machine Translation (SMT). The model ...

Oct 4, 2024 ¡¤ Learning phrase representations using rnn encoder-decoder for statistical ma- chine translation. In EMNLP, 2014. Shmuel Bar David, Itamar Zimerman, Eliya ...

Sep 21, 2024 ¡¤ In this work, we evaluate two approaches that use neural networks to generate obfuscated texts. The first approach uses Generative Adversarial Networks.

Oct 2, 2024 ¡¤ In this section, we review recurrent neural networks (RNNs). RNNs are recurrent sequence models that maintain a hidden state across time steps, capturing ...

Sep 16, 2024 ¡¤ Schwenk, and Y. Bengio, Learning phrase representations using RNN encoder-decoder for statistical machine translation, arXiv preprint 1406.1078, 2014. Crossref.

5 days ago ¡¤ The Encoder-Decoder architecture enabled flexible processing of these sequences, making it effective for tasks like machine translation, where input and output ...

Oct 2, 2024 ¡¤ The encoder RNN processes an input sequence into a sequence of hidden vectors, and the decoder RNN processes the sequence of hidden vectors to an output ...

Sep 15, 2024 ¡¤ Deep learning allows computational models that are composed of multiple processing layers to learn representations of data with multiple levels of abstraction.

Sep 19, 2024 ¡¤ proposed gated recurrent unit (GRU) in their paper "Learning Phrase Representations using ...
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Posted: Sep 19, 2024

Sep 30, 2024 ¡¤ Learning phrase representations using RNN encoder-decoder for statistical machine translation. ChungJ. et al.