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格式版本: 2
标题: "IO Factory: Simulating AI-Enabled Influence Campaigns at Scale"
原文链接: "https://arxiv.org/abs/2608.10920"
发布日期: "2026-08-11"
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---

## Computer Science > Artificial Intelligence

## Title:IO Factory: Simulating AI-Enabled Influence Campaigns at Scale

[View PDF](https://arxiv.org/pdf/2608.10920) [HTML (experimental)](https://arxiv.org/html/2608.10920v1)

> Abstract:We introduce IO Factory, an AI-driven framework for simulating information and influence campaigns as fully integrated, traceable processes. The threat of digital manipulation now extends beyond persuasive text from individual language models to AI swarms, i.e., persistent groups of coordinated agents that adapt to platform feedback and disguise organized campaigns as ordinary social interaction. Because such campaigns cannot be identified from isolated messages alone, they must be analyzed across a continuous spectrum of planning, platform action, exposure, interpretation, measurement, and adaptation. IO Factory represents this process inside a controlled simulated platform, linking actor roles, platform actions, exposure records, structured model-based evaluations, and configured changes in the simulated population. We implement the architecture and evaluate it across configurations of up to 100,000 agents. The results show that IO Factory executes campaign timelines at scale and produces inspectable evidence of exposure and measured movement in configured belief variables. By recording the actors, objectives, action constraints, exposure paths, and measurement rules used in each run, IO Factory supports reproducible research and red-team analysis of coordinated influence.

| Subjects: | Artificial Intelligence (cs.AI) |
| --- | --- |
| Cite as: | [arXiv:2608.10920](https://arxiv.org/abs/2608.10920) \[cs.AI\] |
|  | (or [arXiv:2608.10920v1](https://arxiv.org/abs/2608.10920v1) \[cs.AI\] for this version) |
|  | [https://doi.org/10.48550/arXiv.2608.10920](https://doi.org/10.48550/arXiv.2608.10920) |

## Submission history

From: Jonas R. Kunst PhD \[[view email](https://arxiv.org/show-email/c199b353/2608.10920)\]  
**\[v1\]** Tue, 11 Aug 2026 13:43:48 UTC (548 KB)

[Which authors of this paper are endorsers?](https://arxiv.org/auth/show-endorsers/2608.10920) | Disable MathJax ([What is MathJax?](https://info.arxiv.org/help/mathjax.html))
