Bài báo quốc tế
Applying Large Language Model in Survey Extraction
Nguyễn Quang Hưng
The world of AI has been increasingly relevant, especially
the matter of Large Language Models (LLM), reaching across multiple aspects of work, including business and data analysis. This study
explores the capability of LLMs to extract meaningful insights from textual survey data using three established methods: Few-Shot Prompting,
Chat Completion, and Fine-tuning. Each approach was systematically
assessed for accuracy and cost-effectiveness. Our experiments on a synthetic corpus feedback of students revealed that costs are closely tied
to the performance of each method, offering valuable insights into their
practical applications and trade-offs.
Xuất bản trên:
Applying Large Language Model in Survey Extraction
Ngày đăng:
2025
Nhà xuất bản:
Địa điểm:
Từ khoá:
Large Language Model, Few-Shot prompt, Chat Completion, Fine-tuning, Survey extraction, Data analysis