{
  "id": 18418,
  "url": "https://arxiv.org/abs/2608.10679v1",
  "title": "ENTLORE: A Graph-Grounded Benchmark for Latent Organizational Reasoning in Enterprise Question Answering",
  "summary": "Enterprise question answering is framed as retrieving internal documents and generating grounded answers. Routine enterprise records, however, are work by-products in which required organizational relations remain implicit across heterogeneous sources. Existing benchmarks provide realistic multi-source evidence, but often materialize a predefined answer path and therefore test the composition of stated facts rather than recovery of a target relation absent from the corpus. We call the latter cap",
  "authors": "Akrin Zheng, Alexander Wu, Alaia Liu",
  "category": "research",
  "topics": null,
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T09:00:43.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/18418",
  "original_url": "https://arxiv.org/abs/2608.10679v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}