AI is supporting, accelerating, and automating scientific discovery across a diverse set of fields. However, AI adoption in historical research remains limited due to the lack of solutions designed for historians. In this technical progress report, we introduce the first module of Chronos, an AI Historian under development. This module enables historians to convert image scans of primary sources into data through natural-language interactions. Rather than imposing a fixed extraction pipeline powered by a vision-language model (VLM), it allows historians to adapt workflows for heterogeneous source corpora, evaluate the performance of AI models on specific tasks, and iteratively refine workflows through natural-language interaction with the Chronos agent. The module is open-source and ready to be used by historical researchers on their own sources.

翻译：人工智能正加速并自动化着多个领域的科学发现过程。然而，由于缺乏为历史学家设计的解决方案，人工智能在历史研究中的应用仍十分有限。在本技术进展报告中，我们介绍了正在开发的AI历史学家Chronos系统的首个模块。该模块使历史学家能够通过自然语言交互，将原始文献的影像扫描件转化为结构化数据。不同于依赖视觉语言模型（VLM）的固定提取流程，该模块允许历史学家为异构文献语料库定制工作流程，评估AI模型在特定任务上的表现，并通过与Chronos智能体的自然语言交互来迭代优化工作流程。本模块已开源，可供历史研究人员直接应用于其自有文献。