{
  "id": 12644,
  "url": "https://arxiv.org/abs/2607.19949",
  "title": "SenWorld: A Digital-Twin Simulation for Generating Context-Rich Evaluation Data",
  "summary": "arXiv:2607.19949v1 Announce Type: cross Abstract: Smartphone personal assistants reason over longitudinal personal data, yet evaluating them requires context-rich evaluation data whose correct answers are known, and real device traces are too privacy-sensitive to share. To address this challenge, we present SenWorld, a physically grounded, deterministic, event-sourced digital-twin simulation that generates such data with ground truth fixed by construction. In SenWorld, personas live through a fu",
  "authors": "Zenghui Zhou, Xiaoyang Li, Xiaoxuan Qiao, Zhilang Wei, Tianming Lei",
  "category": "research",
  "topics": "privacy-surveillance",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-23T04:00:00.000Z",
  "fetched_at": "2026-07-23T05:10:49.458Z",
  "source_slug": "arxiv-cscy",
  "source_name": "arXiv cs.CY",
  "source_homepage": "https://arxiv.org/list/cs.CY/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/12644",
  "original_url": "https://arxiv.org/abs/2607.19949",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}