ViGPTQA - State-of-the-Art LLMs for Vietnamese Question Answering: System Overview, Core Models Training, and Evaluations
Minh Thuan Nguyen, Khanh Tung Tran, Nhu Van Nguyen, Xuan-Son Vu · 2023
Large language models (LLMs) and their applications in low-resource languages (such as in Vietnamese) are limited due to lack of training data and benchmarking datasets.This paper introduces a practical real-world implementation of a question answering system for Vietnamese, called ViGPTQA, leveraging the power of LLM.Since there is no effective LLM in Vietnamese to date, we also propose, evaluate, and open-source an instruction-tuned LLM for Vietnamese, named ViGPT.ViGPT demonstrates exceptional performances, especially on real-world scenarios.We curate a new set of benchmark datasets that encompass both AIand human-generated data, providing a comprehensive evaluation framework for Vietnamese LLMs.By achieving state-of-the-art results and approaching other multilingual LLMs, our instruction-tuned LLM underscores the need for dedicated Vietnamese-specific LLMs.Our open-source model supports customized and privacy-fulfilled Vietnamese language processing systems.