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Multi-Reward based Reinforcement Learning for Neural Machine Translation
Reinforcement learning (RL) has made remarkable progress in neural machine translation (NMT).
Syntactic Relevance XLNet Word Embedding Generation in Low-Resource Machine Translation
Semantic understanding is an important factor affecting the quality of machine translation of low resource agglutination language.
A Simple and General Strategy for Referential Problem in Low-Resource Neural Machine Translation
This paper aims to solve a series of referential problems in sequence decoding caused by data sparsity and corpus scarce in low-resource Neural Machine Translation (NMT), including pronoun missing, reference error, bias and so on.
Improving Mongolian-Chinese Neural Machine Translation with Morphological Noise
In this game, the added screener plays the role of emphasizing that the discriminator pays attention to the added Mongolian morphological noise in the form of pseudo-data and improving the training efficiency.
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