Papers by Hieu Trinh

3 papers
Enriching Biomedical Knowledge for Low-resource Language Through Large-scale Translation (2023.eacl-main)

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Challenge: Biomedical data and benchmarks are highly valuable but limited in low-resource languages such as English.
Approach: They propose a translation model in Vietnamese that trains a pretrained Encoder-Decoder Transformer model on 20 million translated abstracts.
Outcome: The proposed model can translate and produce both pretrained and supervised biomedical data in two biomedically important domains.
ViT5: Pretrained Text-to-Text Transformer for Vietnamese Language Generation (2022.naacl-srw)

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Challenge: Existing models for the English language have been used to train on large corpus of high-quality texts.
Approach: They present a pretrained Transformer-based encoder-decoder model for the Vietnamese language . they benchmark ViT5 on two downstream text generation tasks .
Outcome: The proposed model outperforms existing models on Vietnamese Abstractive Summarization and Named Entity Recognition tasks.

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