指向、修订、审查：marimo-lens 在响应式笔记本中的具身智能体分析
Point, Revise, Review: Grounded Agentic Analysis in Reactive Notebooks with marimo-lens
AI总结：
marimo-lens 扩展响应式笔记本，连接人类标记与计算上下文，使智能体基于视觉情境执行分析并返回证据供审查。
摘要：
在计算笔记本中，人类可以指向渲染结果并询问“这个”，而智能体则通过单元格、依赖关系和运行时状态来行动。当人类所见与智能体所操作的内容脱节时，人类必须用剥离了情境化视觉和计算背景的文字来描述其意图并追踪智能体的行为。我们提出了 marimo-lens，这是对响应式 Python 笔记本 marimo 的扩展，用于实现具身的人机智能体分析。Lens 将用户标记的输出和注释与其生成单元格及相关贡献计算相连接，为智能体提供请求的计算上下文。它展示智能体活动，将选定结果返回笔记本，并保留初始选择以供人类审查和重新打开。我们通过对真实世界开放数据集的探索性人机智能体分析来展示这一生命周期，说明视觉情境化问题如何引导计算检查、笔记本操作以及返回供人类审查的证据。
英文摘要：
In a computational notebook, a human can point to a rendered result and ask about "this," while an agent acts through cells, dependencies, and runtime state. When what the human sees and what the agent operates on are disconnected, the human must describe what they mean and trace what the agent did in prose that strips away situated visual and computational context. We present marimo-lens, an extension to the reactive Python notebook marimo for grounded human-agent analysis. Lens connects a human's marked output and note to its producing cell and relevant contributing computation, giving the agent computational context for the request. It surfaces agent activity, returns selected results to the notebook, and preserves the initiating selection for human review and reopening. We illustrate the lifecycle through an exploratory human-agent analysis of a real-world open dataset, showing how visually situated questions lead to computational inspection, notebook action, and returned evidence for human review.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
