{
  "id": 10926,
  "url": "https://arxiv.org/abs/2607.13465v1",
  "title": "DevicesWorld: Benchmarking Cross-Device Agents in Heterogeneous Environments",
  "summary": "LLM-based agents have rapidly improved at operating individual digital environments such as mobile applications, desktop systems, and smart homes. However, real-world user goals often span multiple devices: information may come from a phone, be processed on a desktop, and the result may need to appear on another device. Most existing benchmarks center on a single dominant execution environment, making it difficult to evaluate whether agents can acquire and integrate information across heterogene",
  "authors": "Huatao Li, Xinwei Geng, Yuheng Wang, Yutong Li, Runde Yang, Hantao Chen, Shu Yao, Jingru Fan, Xuhui Ren, Yuanyuan Zhao, Fei Huang, Chen Qian",
  "category": "research",
  "topics": "agents-autonomy,environment",
  "orgs": null,
  "regions": null,
  "published_at": "2026-07-15T05:53:27.000Z",
  "fetched_at": "2026-07-16T05:10:56.605Z",
  "source_slug": "x-arxiv-cs-hc",
  "source_name": "arXiv cs.HC",
  "source_homepage": "https://arxiv.org/list/cs.HC/recent",
  "ethics_ai_record_url": "https://ethics.ai/record/10926",
  "original_url": "https://arxiv.org/abs/2607.13465v1",
  "evidence_status": "source-only",
  "attribution": "via ethics.ai"
}