Penquiry：利用大语言模型的笔式交互原位问答系统

Computer Science > Human-Computer Interaction arXiv:2609.19870 (cs) [Submitted on 17 Sep 2026] Title:Penquiry: A Pen-based Interactive In-situ Q&A System Leveraging LLMs Authors:Jeongmin Rhee, Changhee Lee, Hyunwoo Kim, Kiroong Choe, Bohyoung Kim, Sungahn Ko, Jinwook Seo View a PDF of the paper titled Penquiry: A Pen-based Interactive In-situ Q&A System Leveraging LLMs, by Jeongmin Rhee and 6 other authors View PDF HTML (experimental) Abstract:Pen-based digital devices remain a preferred medium for active, cognitively engaging study. Concurrently, Large Language Models (LLMs) have become indispensable for self-directed learning, enabling students to clarify concepts. However, a fundamental interaction gap exists between the fluid, spatial nature of pen-based workflows and the discrete, keyboard-heavy requirements of LLMs. We present Penquiry, an in-situ question-and-answer system that bridges this gap by enabling learners to pose questions directly on digital study materials via a pen. We characterize two primary interaction challenges in this multimodal transition: a Referential Barrier, which hinders grounding fine-grained visual elements into the query context, and an Expressive Barrier, which forces learners to translate diverse, non-textual intents--such as equations and diagrams--into rigid, typed sentences. To resolve these, Penquiry introduces a mediation layer featuring Content Snapping for unambiguous referencing and Question Autocompletion to expand sparse ink keywords into rich semantic queries. Through two iterative user studies (N = 16 per study), we demonstrate that Penquiry significantly reduces the cognitive and physical overhead of inquiry compared to traditional interfaces, providing a new blueprint for pen-based, in-situ AI interaction Comments: Subjects: Human-Computer Interaction (cs.HC) Cite as: arXiv:2609.19870 [cs.HC] (or arXiv:2609.19870v1 [cs.HC] for this version) https://doi.org/10.48550/arXiv.2609.19870 Focus to learn more arXiv-issued DOI via DataCite (pending registration) Related DOI: https://doi.org/10.1145/3830398.3830637 Focus to learn more DOI(s) linking to related resources Submission history From: Changhee Lee [view email] [v1] Thu, 17 Sep 2026 08:22:54 UTC (13,113 KB) Full-text links: Access Paper: View a PDF of the paper titled Penquiry: A Pen-based Interactive In-situ Q&A System Leveraging LLMs, by Jeongmin Rhee and 6 other authors View PDF HTML (experimental) TeX Source view license Current browse context: cs.HC new | recent | 2026-09 Change to browse by: cs References & Citations NASA ADS Google Scholar Semantic Scholar export BibTeX citation Loading... BibTeX formatted citation × loading... Data provided by: Bookmark Bibliographic Tools Bibliographic and Citation Tools Bibliographic Explorer Toggle Bibliographic Explorer (What is the Explorer?) Connected Papers Toggle Connected Papers (What is Connected Papers?) Litmaps Toggle Litmaps (What is Litmaps?) scite.ai Toggle scite Smart Citations (What are Smart Citations?) Code, Data, Media Code, Data and Media Associated with this Article alphaXiv Toggle alphaXiv (What is alphaXiv?) Links to Code Toggle CatalyzeX Code Finder for Papers (What is CatalyzeX?) DagsHub Toggle DagsHub (What is DagsHub?) GotitPub Toggle Gotit.pub (What is GotitPub?) Huggingface Toggle Hugging Face (What is Huggingface?) ScienceCast Toggle ScienceCast (What is ScienceCast?) Demos Demos Replicate Toggle Replicate (What is Replicate?) Spaces Toggle Hugging Face Spaces (What is Spaces?) Spaces Toggle TXYZ.AI (What is TXYZ.AI?) Related Papers Recommenders and Search Tools Link to Influence Flower Influence Flower (What are Influence Flowers?) Core recommender toggle CORE Recommender (What is CORE?) Author Venue Institution Topic About arXivLabs arXivLabs: experimental projects with community collaborators arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website. Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them. Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs. Which authors of this paper are endorsers? | Disable MathJax (What is MathJax?)