"Enhancing Accuracy in Biomedical Question-Answering with LLMs"

Large language models (LLMs) excel at answering questions but often falter in accuracy, especially in biomedicine. This paper presents a system that boosts reliability by integrating PubMed abstracts into LLM responses. Each answer cites its source, allowing verification. The system outperforms PubMed search by 23%. Fine-tuned models match GPT-4 Turbo's performance in referencing abstracts. Datasets and models are publicly available.

Explanation:

• LLMs: Advanced computer programs designed to understand and generate human-like text.
• PubMed: A database of medical research articles.
• Fine-tuned LLM: A language model adjusted for specific tasks, like medical question-answering.