{
  "id": 18649,
  "url": "https://arxiv.org/abs/2608.11195v1",
  "title": "Long-Horizon AI Research for Grothendieck Constant: A Case Study in Human-AI Mathematical Collaboration",
  "summary": "AI agents are increasingly used in mathematics research, but it is often unclear how to use them effectively. Towards this, we present an extensive case study of how AI was used to improve bounds on the Grothendieck constant $K_G$, which captures the hardness between combinatorial problems and their continuous relaxations. Specifically, while the precise value of $K_G$ is not known, we recently tightened the best known bounds to \\[ \\frac{6π}{11} \\;\\le\\; K_G \\;\\le\\; \\fracπ{2\\log(1+\\sqrt2)} - 10^{",
  "authors": "Alan Li, Rahul Saha, Anton Xue, Swarat Chaudhuri, Adam Klivans, Pravesh K Kothari, Raghu Meka",
  "category": "research",
  "topics": "agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T17:53:48.000Z",
  "fetched_at": "2026-08-12T05:10:43.828Z",
  "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/18649",
  "original_url": "https://arxiv.org/abs/2608.11195v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}