Papers with Vietnamese-specific

3 papers
ViGPTQA - State-of-the-Art LLMs for Vietnamese Question Answering: System Overview, Core Models Training, and Evaluations (2023.emnlp-industry)

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Challenge: Large language models (LLMs) and their applications in low-resource languages are limited due to lack of training data and benchmarking datasets.
Approach: They propose a question-response system for Vietnamese that uses LLMs . they propose to open-source the model and train it on benchmark datasets based on Vietnamese data .
Outcome: The proposed question answering system for Vietnamese is open-source and performant . it can learn and capture human-like text, but there is a gap in evaluations for Vietnamese .
PhoBERT: Pre-trained language models for Vietnamese (2020.findings-emnlp)

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Challenge: Experimental results show that PhoBERT outperforms the recent best pre-trained multilingual model XLM-R in multiple Vietnamese-specific NLP tasks.
Approach: They present PhoBERT with two versions, Phobert-base and PhoBRET-large, which are pre-trained for Vietnamese.
Outcome: The proposed model outperforms the best pre-trained model XLM-R and improves the state-of-the-art in multiple Vietnamese-specific NLP tasks including Part-of speech tagging, Dependency parsing, Named-entity recognition and Natural language inference.
Which Works Best for Vietnamese? A Practical Study of Information Retrieval Methods across Domains (2026.findings-eacl)

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Challenge: Existing studies on Large Language Models (LLMs) are limited to single domains or curated datasets.
Approach: They propose a domain-normalized, multi-domain benchmark for Vietnamese IR . they evaluate lexical, neural-sparse, late-interaction, dense, and hybrid paradigms .
Outcome: The proposed benchmarks cover six domains and ten datasets across education, legal, healthcare, customer support, lifestyle reviews, and open-domain knowledge.

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