Article

Retrieval-Augmented Generation for Reducing Hallucinations in Drug-Related Question Answering Systems

2026-08-05

Abstract excerpt

<title>Abstract</title> <p>Large Language Models (LLMs) deployed in pharmaceutical question-answering applications frequently generate clinically dangerous hallucinations — factually incorrect outputs that pose serious patient-safety risks. We propose and evaluate a Retrieval-Augmented Generation (RAG) pipeline that grounds LLM responses in a curated, citation-verified pharmaceutical knowledge base. The system co...

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Literature Corpus work: 0d4a0ae4-4db0-5ef1-b220-15d7e8dd3945
DOI: 10.21203/rs.3.rs-10186581/v1

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