Enhancing Large Language Model for QA system in Vietnamese Traffic Law Domain

Abstract

Large language models (LLMs) have showcased impressive capabilities by effectively executing natural language instructions without fine-tuning for specific tasks or datasets. However, leveraging LLMs for domain-specific question answering encounters significant constraints. The generated answer tends to hallucinate due to the training data collection time.