{
  "id": 18653,
  "url": "https://arxiv.org/abs/2608.11066v1",
  "title": "Quantum Coordination Advantages in AI State-Tracking Tasks: Semantic Compilation and Latent Memory",
  "summary": "We prove inference-time quantum coordination advantages for specified AI state-tracking tasks. A solver compresses semantic history into a future-accessible boundary state and later answers a query. We count communication $B$, persistent instance-dependent memory $M$, and local work $D$; classical recurrence, caches, tools, and recomputation are allowed and charged. The central result is a boundary-preserving semantic-compilation theorem. It maps a finite one-way, streaming, or adaptive causal t",
  "authors": "Ming Yang",
  "category": "research",
  "topics": "privacy-surveillance",
  "orgs": null,
  "regions": null,
  "published_at": "2026-08-11T15:32:15.000Z",
  "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/18653",
  "original_url": "https://arxiv.org/abs/2608.11066v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}