MTet: Multi-domain Translation for English and Vietnamese
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Abstract (arXiv)
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.
Key facts. Cited by 5 papers in the map (data through 14 Oct 2026). Builds on 24 of its 37 references that are in the map. First posted on arXiv 11 Oct 2022.
Builds on
24 of 37 references.
References · 24
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12 more
- 2020WikiLingua: A New Benchmark Dataset for Cross-Lingual Abstractive Summarizationcited by 154
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Built on by
Citing papers per year: 2023: 1; 2024: 2; 2025: 0; 2026: 2.
5 papers.
- 2024Improving Vietnamese-English Medical Machine Translationcited by 5
- 2023Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generationcited by 0
- 2024Utilize Transformers for translating Wikipedia category namescited by 0
- 2026PiDA: Phonetically-Informed Data Augmentation for Robust Vietnamese Speech Translationcited by 0
- 2026Towards Efficient Simultaneous Inverse Text Normalization with Pretrained Text-to-Text Language Model and Read-Tag-Write Policycited by 0
- 2026Towards Efficient Simultaneous Inverse Text Normalization with Pretrained Text-to-Text Language Model and Read-Tag-Write Policy14 Oct 2026
- 2026PiDA: Phonetically-Informed Data Augmentation for Robust Vietnamese Speech Translation11 Jun 2026
- 2024Utilize Transformers for translating Wikipedia category names12 Aug 2024
- 2024Improving Vietnamese-English Medical Machine Translation28 Mar 2024
- 2023Data-Driven Approach for Formality-Sensitive Machine Translation: Language-Specific Handling and Synthetic Data Generation26 Jun 2023