{
  "id": 6523620,
  "title": "GANDR: Claim Auditing for Verifiable Legal Answer Generation",
  "url": "https://urgent.news/2026/09/09/gandr-claim-auditing-for-verifiable-legal-answer-generation",
  "topic": "ai",
  "section": "AI",
  "published": "2026-09-09T15:08:09.000Z",
  "source": {
    "name": "arXiv cs.AI",
    "slug": "arxiv-cs-ai",
    "url": "https://arxiv.org/abs/2609.10293v1"
  },
  "original_language": "en",
  "account": null,
  "summary": "In high-stakes domains such as legal practice, a language-model answer is only useful to the extent that a reader can verify each claim against the source the system cites. Current grounded-generation pipelines score the answer as a whole, so a correct conclusion can rest on fabricated or loosely matched citations and still score well. Closing this gap requires both a system built for per-claim…",
  "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."
}