{
  "id": 13697,
  "url": "https://arxiv.org/abs/2607.22385v1",
  "title": "Agentic Root Cause Analysis through Evidence-Grounded Reasoning",
  "summary": "Diagnosing the root cause of anomalies is essential for safe industrial operation. Despite extensive sensor instrumentation, formulating hypotheses and gathering evidence remains a manual process, creating a major operational bottleneck. While existing data-driven approaches aim to automate this, two critical limitations restrict their deployment: their operate as black boxes unable to justify their diagnosis, and they require scarce labeled examples of faulty operation. To address this gap, we",
  "authors": "Amaury Wei, Olga Fink",
  "category": "research",
  "topics": "healthcare,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-24T15:10:41.000Z",
  "fetched_at": "2026-07-27T05:10:06.638Z",
  "source_slug": "x-arxiv-cs-ai",
  "source_name": "arXiv cs.AI",
  "source_homepage": "https://arxiv.org/list/cs.AI/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/13697",
  "original_url": "https://arxiv.org/abs/2607.22385v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}