Low-resource neural machine translation: A systematic literature review
In this study, a systematic literature review was conducted to examine the significant works
in the literature on low-resource neural machine translation. Within the scope of the study …
in the literature on low-resource neural machine translation. Within the scope of the study …
BERTology for machine translation: What BERT knows about linguistic difficulties for translation
Y Dai, M de Kamps, S Sharoff - Proceedings of the thirteenth …, 2022 - aclanthology.org
Pre-trained transformer-based models, such as BERT, have shown excellent performance in
most natural language processing benchmark tests, but we still lack a good understanding …
most natural language processing benchmark tests, but we still lack a good understanding …
Based on Gated Dynamic Encoding Optimization, the LGE-Transformer method for low-resource neural machine translation
ZZ Xu, SQ Zhan, W Yang, Q Xie - IEEE Access, 2024 - ieeexplore.ieee.org
In current Neural Machine Translation (NMT) research, translating low-resource language
pairs remains a significant challenge. This work proposes an LGE-Transformer method for …
pairs remains a significant challenge. This work proposes an LGE-Transformer method for …