mlsanityData to 7 Oct 2026

An Effective Method using Phrase Mechanism in Neural Machine Translation

arXiv 2308.10482 ↗First posted 21 Aug 2023cs.CL cs.LGcited by 1

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Abstract (arXiv)

Machine Translation is one of the essential tasks in Natural Language Processing (NLP), which has massive applications in real life as well as contributing to other tasks in the NLP research community. Recently, Transformer -based methods have attracted numerous researchers in this domain and achieved state-of-the-art results in most of the pair languages. In this paper, we report an effective method using a phrase mechanism, PhraseTransformer, to improve the strong baseline model Transformer in constructing a Neural Machine Translation (NMT) system for parallel corpora Vietnamese-Chinese. Our experiments on the MT dataset of the VLSP 2022 competition achieved the BLEU score of 35.3 on Vietnamese to Chinese and 33.2 BLEU scores on Chinese to Vietnamese data. Our code is available at https://github.com/phuongnm94/PhraseTransformer.

Key facts. Cited by 1 paper in the map (data through 7 Oct 2026). Builds on 14 of its 21 references that are in the map. First posted on arXiv 21 Aug 2023.

Builds on

14 of 21 references.

References · 14

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2 more
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Cited by year (2026 to 7 Oct)

Citing papers per year: 2026: 1.

1 paper.

  1. 2026Direct Image-to-Modern Vietnamese Translation of Han-Nom Manuscripts via Multimodal RLHF Preference Alignmentcited by 0