In the present study, we propose novel sequence-to-sequence pre-training objectives for
low-resource machine translation (NMT): Japanese-specific sequence to sequence (JASS) …

Massively multilingual sentence representation models, eg, LASER, SBERT-distill, and
LaBSE, help significantly improve cross-lingual downstream tasks. However, the use of a …

More than 13 million people suffer a stroke each year. Aphasia is known as a language
disorder usually caused by a stroke that damages a specific area of the brain that controls …

Neural machine translation (NMT) models are typically trained using a softmax cross-
entropy loss where the softmax distribution is compared against smoothed gold labels. In …

Neural machine translation (NMT) models are typically trained using a softmax cross-
entropy loss where the softmax distribution is compared against the gold labels. In low …

本文提出了一种基于汉字简繁转换的神经机器翻译(Neural Machine Translation, NMT)
数据增强方法, 旨在通过利用简繁转换表将源端文字替换为目标端文字, 从而融合汉字简繁转换 …

In neural machine translation (NMT), sequence distillation (SD) through creation of distilled
corpora leads to efficient (compact and fast) models. However, its effectiveness in extremely …

In a diverse linguistic landscape where over 7,100 languages are spoken, vast swathes of
digital content remain isolated within language silos, creating significant barriers to global …

Neural machine translation (NMT)[1] is known to give state-of-the-art translations for a
variety of language pairs. Sub-word segmentation [2, 3] is one of the key reasons behind it …