During complex knowledge work, people engage in iterative sensemaking: interpreting information, connecting ideas, and refining their understanding. Yet in current human-AI collaboration, these cognitive processes are difficult to share and organize for AI. They arise in situ and are rarely captured without interrupting the task, and even when expressed, remain scattered or reduced to system-generated summaries that fail to reflect users' cognitive processes. We address this challenge by enabling AI context that is grounded in users' cognitive traces and can be directly inspected and revised by the user. We first explore this through a probe system that supports in-situ snippet memoing, allowing users to easily share their cognitive moves. Our study (N=10) highlights the value of capturing such context and the challenge of organizing it once accumulated. We then present Contexty, which supports users in inspecting and refining these contexts to better reflect their understanding of the task. Our evaluation (N=12) showed that Contexty improved task awareness, thought structuring, and users' sense of authorship and control, with participants preferring snippet-grounded AI responses over non-grounded ones (78.1%). We discuss how capturing and organizing users' cognitive context enables AI as a context-aware collaborator while preserving user agency.

翻译：摘要：在复杂的知识工作过程中，人们会进行迭代式的意义建构（sensemaking）：诠释信息、关联想法并精炼理解。然而，在当前的人机协作中，这些认知过程难以被AI共享与组织。它们产生于情境之中，若不中断任务则难以被捕捉；即便被表达出来，也常零散分布或沦为无法反映用户认知过程的系统生成摘要。我们通过构建植根于用户认知痕迹、且可供用户直接审视与修正的AI上下文来应对这一挑战。我们首先通过一个支持情境化片段备忘录的探测系统展开探索，使用户得以轻松分享其认知行为。研究（N=10）凸显了捕捉此类上下文的价值，以及当内容积累后对其进行组织的挑战。为此我们提出Contexty——该系统支持用户审视并精炼这些上下文，使其更贴合用户对任务的认知。评估（N=12）表明，Contexty提升了任务感知、思维结构化以及用户的作者身份与掌控感，参与者更偏好基于片段生成的AI回应（78.1%）。我们探讨了如何通过捕捉与组织用户的认知上下文，使AI成为具备上下文感知能力的协作者，同时保留用户自主性。