{
  "id": 5527,
  "url": "https://arxiv.org/abs/2604.20904v1",
  "title": "Reinforcing privacy reasoning in LLMs via normative simulacra from fiction",
  "summary": "Information handling practices of LLM agents are broadly misaligned with the contextual privacy expectations of their users. Contextual Integrity (CI) provides a principled framework, defining privacy as the appropriate flow of information within context-relative norms. However, existing approaches either double inference cost via supervisor-assistant architectures, or fine-tune on narrow task-specific data. We propose extracting normative simulacra (structured representations of norms and infor",
  "authors": "Matt Franchi, Madiha Zahrah Choksi, Harold Triedman, Helen Nissenbaum",
  "category": "research",
  "topics": "safety-alignment,privacy-surveillance,agents-autonomy",
  "orgs": null,
  "regions": null,
  "published_at": "2026-04-21T19:16:22.000Z",
  "fetched_at": "2026-07-14T16:31:48.875Z",
  "source_slug": "arxiv-ethics",
  "source_name": "arXiv",
  "source_homepage": "https://arxiv.org",
  "ethics_ai_record_url": "https://ethics.ai/record/5527",
  "original_url": "https://arxiv.org/abs/2604.20904v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}