发表机构
Politecnico di Torino（都灵理工大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
GROB是一种多智能体架构，可在无特权遥测时通过公开互联网轨迹调查候选自主智能体活动，实验显示稀疏公开轨迹可支持后续重建，但无法确定组织归属，智能体身份连续性仍是研究问题。
AI 中文摘要
我们提出了GROB，一种在无法获取特权遥测数据时，通过公开互联网轨迹调查候选自主智能体活动的多智能体架构。该系统执行受控的只读公开轨迹收集，并保留选定的观测结果以供后续解析。在2026年9月的冻结语料库中，随着更多公开证据的出现，部分收集到的轨迹变得更具信息量。最有力的结果涉及9月9日捕获的人口普查局标记标识符，公开修订记录随后将这些标识符解析为6月16日至17日的特定人口普查请求。其他结果显示，GROB收集的轨迹与后续重建或报告的证据之间的关联较弱，这些关联强度各异，仅部分可与特定公开记录关联。结果表明，稀疏的公开轨迹在其重要性被完全理解前仍可保持有用，此类证据可支持后续重建，但仅靠公开轨迹无法确定组织归属。执行身份是一个独立问题，因为自主语言模型智能体的身份连续性仍是一个活跃的研究问题。
英文摘要
We present GROB, a multi-agent architecture for investigating candidate autonomous-agent activity through public Internet traces when privileged telemetry is unavailable. The system performs controlled, read-only collection of public traces and preserves selected observations for later resolution. In a frozen September 2026 corpus, several collected traces became more informative as additional public evidence emerged. The strongest result concerns Census-labelled identifiers captured on 9 September. Public revision records later resolved these identifiers to specific Census requests from 16 - 17 June. Other results show weaker links between traces collected by GROB and evidence reconstructed or reported later. These links vary in strength, and only some can be tied to specific public records. The results show that sparse public traces can remain useful even before their significance is fully understood. Such evidence can support later reconstruction, but public traces alone do not establish organizational attribution. Execution identity presents a separate problem, as continuity of agent identity remains an active research question for autonomous language-model agents.
