{
  "id": 4770756,
  "title": "Fine-Grained Multi Image Object Hallucination Benchmark",
  "url": "https://urgent.news/2026/08/31/fine-grained-multi-image-object-hallucination-benchmark",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-31T11:53:03.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.30653v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Multimodal Large Language Models (MLLMs) are increasingly deployed in multi-image scenarios requiring complex reasoning across visual contexts. However, current MLLMs remain fundamentally limited by object hallucination-generating plausible yet factually inconsistent descriptions about objects. Existing benchmarks, designed primarily for single-image settings or providing only high-level…",
  "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."
}