Papers by Tran Tai

2 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.
Modeling What-to-ask and How-to-ask for Answer-unaware Conversational Question Generation (2023.acl-long)

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Challenge: Existing methods to generate conversational question are naive and do not account for the answer span.
Approach: They propose a framework for generating a conversational question from a context.
Outcome: The proposed framework achieves state-of-the-art in two different settings compared to existing models . it uses a sentence as the rationale and extracts the answer span from it .

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