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MTet: Multi-domain Translation for English and Vietnamese

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arxiv 2210.05610 v2 pith:EVGD7UQ4 submitted 2022-10-11 cs.CL cs.AI

Chinh Ngo , Trieu H. Trinh , Long Phan , Hieu Tran , Tai Dang , Hieu Nguyen , Minh Nguyen , Minh-Thang Luong This is my paper · ORCID
classification cs.CLcs.AI
keywords translationmtetvietnamesecombiningenglishenglish-vietnamesemodelmulti-domain
verification ladder T0 review T1 audit T2 compute T3 formal
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We introduce MTet, the largest publicly available parallel corpus for English-Vietnamese translation. MTet consists of 4.2M high-quality training sentence pairs and a multi-domain test set refined by the Vietnamese research community. Combining with previous works on English-Vietnamese translation, we grow the existing parallel dataset to 6.2M sentence pairs. We also release the first pretrained model EnViT5 for English and Vietnamese languages. Combining both resources, our model significantly outperforms previous state-of-the-art results by up to 2 points in translation BLEU score, while being 1.6 times smaller.

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Cited by 2 Pith papers

Reviewed papers in the Pith corpus that reference this work. Sorted by Pith novelty score. Full citation record

  1. VN-MTEB: Vietnamese Massive Text Embedding Benchmark

    cs.CL 2025-07 conditional novelty 6.0 of 10

    VN-MTEB is a new 41-dataset Vietnamese benchmark for text embeddings, built by machine-translating MTEB datasets with embedding-based and LLM-based quality filters.

  2. An Efficient Approach for Machine Translation on Low-resource Languages: A Case Study in Vietnamese-Chinese

    cs.CL 2025-01 conditional novelty 4.0 of 10

    Fine-tuning mBART with TF-IDF-selected back-translated monolingual sentences raises test BLEU from 38.22 to 38.97 for Vietnamese-to-Chinese and from 35.58 to 38.90 for Chinese-to-Vietnamese.

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