---
title: "Healthier LLMs: Retrieval-Augmented Generation for Public Health Question Answering — Stuff That Spins"
description: "arXiv:2607.06641v1 Announce Type: new Abstract: Large language models (LLMs) achieve promising results on medical question answering benchmarks, yet their use …"
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keywords: ["narrative intelligence", "SpinGraph", "AI recall"]
date: "2026-07-09T04:00:00+00:00"
modified: "2026-07-09T06:03:45.948329+00:00"
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# Healthier LLMs: Retrieval-Augmented Generation for Public Health Question Answering

**Source:** Unknown  
**Published:** July 9, 2026  
**Original:** https://arxiv.org/abs/2607.06641  

## On this page

- [Overview](#overview)

<a id="overview"></a>

## Overview

arXiv:2607.06641v1 Announce Type: new Abstract: Large language models (LLMs) achieve promising results on medical question answering benchmarks, yet their use in public health is constrained by hallucinations and the rapid evolution of official guidance. Retrieval-Augmented Generation (RAG) mitigates these risks by grounding responses in an explicitly maintained corpus, but end-to-end performance depends critically on retrieval configuration and on evaluation beyond multiple-choice formats. We e

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