{
  "id": 1844084,
  "title": "Evaluating the Diversity of AI-Generated Content with Diversity Profiles",
  "url": "https://urgent.news/2026/08/18/evaluating-the-diversity-of-ai-generated-content-with-diversity",
  "topic": "ai",
  "section": "AI",
  "published": "2026-08-18T12:57:03.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2608.17731v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "Diversity is a fundamental criterion for evaluating generative artificial intelligence (AI) systems, yet its measurement remains inherently ambiguous. Existing approaches typically represent generated samples in an embedding space, compute pairwise distances or similarities, and aggregate them into a single scalar score. Such scalar summaries are convenient, but they often encode different…",
  "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."
}