{
  "id": 445,
  "url": "https://arxiv.org/abs/2606.30306v1",
  "title": "Always-OnAgents:A Survey of Persistent Memory, State, and Governance in LLMAgents",
  "summary": "Always-on agents are systems whose future behavior depends on durable state accumulated across earlier interactions. We treat them as persistent-state systems: the operative system includes retrievable memories, but also task ledgers, permissions, credentials, commitments, provenance and audit records, shared state, trigger conditions, and externally committed effects linked to those records. The survey reads the literature through six diagnostic axes for each state item, authority, scope, mutab",
  "authors": "Tianyu Ding, Aditya Nannapaneni, Bingfan Liu, Ling Zhang",
  "category": "research",
  "topics": "regulation,healthcare,agents-autonomy,transparency",
  "orgs": null,
  "regions": null,
  "published_at": "2026-06-29T13:47:42.000Z",
  "fetched_at": "2026-07-14T14:14:32.647Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/445",
  "original_url": "https://arxiv.org/abs/2606.30306v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}