[论文] Data Journalist Agent: Transforming Data into Verifiable Multimodal St...

论文概要

研究领域: NLP
作者: Kevin Qinghong Lin, Batu EI, Yuhong Shi, Pan Lu, Philip Torr, James Zou
发布时间: 2026-06-09
arXiv: 2606.11176

中文摘要

Data2Story是一个多智能体数据新闻框架，将专业角色编排为虚拟新闻编辑部。两大创新：1）每个声明都有证据支撑，检查员将数字、角度和素材链接回数据、代码或外部参考；2）文章是多模态生成的，部署交互式地图、音频等多模态工具。在18篇文章上评估，在透明度和可审计性方面表现突出，定位为记者的协作者。

原文摘要

Data tells stories that shape society; the data journalist's job is to turn raw information into stories non-experts can trust. A high-quality news feature takes a newsroom team weeks: hunting for context, running statistics, choosing an angle, and designing visuals. Recent agents handle individual steps well: data-science agents close the analysis loop, while design agents synthesize beautiful websites. But can an agent serve as a data journalist end to end? We introduce Data Journalist Agent (Data2Story), a multi-agent framework that orchestrates specialized roles into a single virtual newsroom. Data2Story contributes two innovations. (i) Claims are evidence-grounded: an Inspector links every number, angle, and asset back to data, code, or an external reference. (ii) Articles are multimo...

自动采集于 2026-06-11

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