{
  "id": "ai-training-manager",
  "title": "AI Training Manager: Bounded Closed-Loop Control of Adaptive Training Recipes",
  "authors": [
    {
      "given": "Anjali",
      "family": "Rao"
    },
    {
      "given": "Nikhil Kamalkumar",
      "family": "Advani"
    }
  ],
  "year": 2026,
  "venue": "arXiv",
  "paper_url": "https://arxiv.org/abs/2606.29871",
  "pdf_url": "https://arxiv.org/pdf/2606.29871",
  "doi": "10.48550/arXiv.2606.29871",
  "summary": "An asynchronous LLM supervisor observes training telemetry and proposes constrained changes to a running training recipe, with experiments on deliberately induced supervised-learning and reinforcement-learning failure modes.",
  "connection": "Studies an automated controller over active training, complementing Interactive Training’s reusable infrastructure for human and automated controllers.",
  "bibtex_type": "article",
  "citation_key": "rao2026aitrainingmanager",
  "source_urls": [
    "https://arxiv.org/abs/2606.29871",
    "https://arxiv.org/html/2606.29871v3"
  ],
  "arxiv_id": "2606.29871",
  "arxiv_first_posted": "2026-06-29",
  "publication_type": "preprint",
  "container_title": "arXiv",
  "updated_at": "2026-11-10",
  "record_url": "https://yuntiandeng.com/research/papers/ai-training-manager/"
}