{
  "id": 13792,
  "url": "https://arxiv.org/abs/2607.23931",
  "title": "State-dependent error correlations shape voting thresholds in committees of AI agents",
  "summary": "arXiv:2607.23931v1 Announce Type: new Abstract: The aggregation benefit of a committee of artificial intelligence (AI) agents comes from complementary information across members. Classical voting guarantees assume independent errors. Language-model errors often co-occur on the same cases. We combine Sah-Stiglitz screening with error dependence that can differ between good and bad cases. In a homogeneous exchangeable Gaussian-copula model, shared errors create a positive asymptotic error floor fo",
  "authors": "Haifeng Li, Mo Hai",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-28T04:00:00.000Z",
  "fetched_at": "2026-07-28T05:10:12.325Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/13792",
  "original_url": "https://arxiv.org/abs/2607.23931",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}