{
  "id": 3647635,
  "title": "Multi-Granularity Context-Enhanced RAG over Multimodal Knowledge Graphs",
  "url": "https://urgent.news/2026/08/26/multi-granularity-context-enhanced-rag-over-multimodal-knowledge",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-26T16:38:02.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.25986v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Retrieval-augmented generation (RAG) is widely used to mitigate hallucination issues in large language models (LLMs) and multimodal large language models (MLLMs). In particular, knowledge graph (KG)-based RAG leverages structured knowledge to provide (M)LLMs with high-quality external information. Building on these works, recent studies have explored multimodal knowledge graphs (MMKGs) as…",
  "key_points": [],
  "editors_take": null,
  "illustration": null,
  "coverage": {
    "outlets": 1,
    "also_reported_by": []
  },
  "ai_generated": true,
  "disclaimer": "Summaries, key points and the editor’s take are written by software from other outlets’ reporting and may contain errors — always check the linked original."
}