Sep 1, 2014 ， The neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance.
Oct 15, 2021 ， Attention Decoder is designed to ; automatically (soft-)search for parts of a source sentence that are relevant to predicting a target word.
May 19, 2016 ， In this paper, we show that the proposed approach of jointly learning to align and translate achieves significantly improved translation ...
Dec 17, 2022 ， Part 1: neural machine translation by jointly learning to align and translate ... JOINTLY ...
Duration: 18:24
Posted: Dec 17, 2022
Duration: 18:24
Posted: Dec 17, 2022
It is conjecture that the use of a fixed-length vector is a bottleneck in improving the performance of this basic encoder-decoder architecture, and it is ...
Missing: Explained | Show results with:Explained
Jul 11, 2024 ， NMT focuses on maximizing the probability of a correct translation given a source sentence through a neural network. Existing models often use a ...
Sep 1, 2014 ， The neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance.
In neural machine translation we have an encoder and a decoder. The encoder extracts information from an entire source sentence, while the decoder decodes the ...
Missing: Explained | Show results with:Explained
Mar 18, 2022 ， This article explains the recursive neural network based language to language translation model that introduced the attention mechanism for the first time.
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What is neural machine translation by learning to jointly align and translate?
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Sep 1, 2024 ， The paper introduces an innovative approach to neural machine translation (NMT) that aims to improve the translation of long sentences.
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