NCU-IISR: Enhancing Biomedical Question Answering with GPT-4 and Retrieval Augmented Generation in BioASQ 12b Phase B

Bing Chen Chih, Jen Chieh Han, Richard Tzong Han Tsai

研究成果: 雜誌貢獻會議論文同行評審

1 引文 斯高帕斯(Scopus)

摘要

In this paper, we introduce our system and submissions in BioASQ 12b phase b [1], highlighting a significant improvement with GPT-4 and the integration of Retrieval Augmented Generation (RAG) techniques. We describe our prompt engineering methods and the experimental procedures followed. Because GPT-4 has proven effectiveness in generating answers and its ability in the biological domain, our system utilizes GPT-4 to address biomedical question-answering (QA). Leveraging OpenAI's ChatCompletions API, we refined previous prompt engineering approaches [2] for BioASQ 11b phase b. This year, the addition of RAG techniques significantly improved the information retrieval capabilities of our system. Consequently, our latest submission employed what we experimented to be the most effective prompts and techniques, achieving excellent performance across multiple metrics in the fourth batch.

原文???core.languages.en_GB???
頁(從 - 到)99-105
頁數7
期刊CEUR Workshop Proceedings
3740
出版狀態已出版 - 2024
事件25th Working Notes of the Conference and Labs of the Evaluation Forum, CLEF 2024 - Grenoble, France
持續時間: 9 9月 202412 9月 2024

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