{
  "id": 19034,
  "url": "https://arxiv.org/abs/2608.12138v1",
  "title": "A corpus-specific clinical RAG system matches or outperforms newer frontier LLMs on HealthBench",
  "summary": "General-purpose large language models (LLMs) have recently been reported to match or exceed specialized clinical AI tools on medical benchmarks, but such comparisons draw on a narrow set of systems and on benchmarks developed largely in high-income settings. We evaluate VITA, a retrieval-augmented generation (RAG) system purpose-built for contextual knowledge retrieval in India and other low- and middle-income (LMIC) settings. VITA retrieves from a curated corpus of disease-specific guidelines,",
  "authors": "Praveen Reddy, Charuta Mandke, Suvrankar Datta, Sarah Khan, Siddharth Reddy Anthireddy, Shitij Arora, Vishal Singh",
  "category": "research",
  "topics": "healthcare",
  "orgs": null,
  "regions": "india",
  "published_at": "2026-08-12T14:55:46.000Z",
  "fetched_at": "2026-08-13T05:10:37.786Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/19034",
  "original_url": "https://arxiv.org/abs/2608.12138v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}