[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-83489-en":3,"doc-seo-83489-105":30,"detail-sidebar-cat-0-en-105":83},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":20,"is_deleted":4,"is_public":21,"is_downloadable":21,"audit_status":21,"page_count":22,"language":23,"language_code":24,"site_id":25,"html_lang":24,"table_of_contents":26,"faqs":27,"seo_title":13,"seo_description":14,"update_tm":28,"read_time":29},83489,687197100911,"Himbo","https://ap-avatar.wpscdn.com/avatar/a000239b6f1da00475?x-image-process=image/resize,m_fixed,w_180,h_180&k=1782698725881665579",8,"Research & Report","Gaze-Informed Proactive AI Assistance for Children’s Picture Exploration","Proactive assistance from large language models (LLMs) is increasingly studied in HCI, yet prior work largely targets adults and explicit, task-driven requests. This study examines proactive support for children during picture exploration, focusing on when to assist and what to describe using children’s gaze and nonverbal behavior. Ollie, a gaze-informed assistant, estimates attention, identifies visual focus, selects a related picture region, and generates short narrative descriptions. In a within-subject experiment, gaze-informed assistance sustained attention longer and guided children more effectively than random prompting.","arXiv :2607 .00445v 1 [ cs .HC] 1 Jul 2026  \nGaze-Informed Proactive AI Assistance for Children’s Picture Exploration  \nZEKUN WU, Saarland University, Saarland Informatics Campus, Germany  \nMAN SU, Tübingen Digital Teaching Lab (TüDiLab) , Leibniz-Institut für Wissensmedien (IWM Tübingen), Germany HUIYONG LI, Research Institute for Information Technology, Kyushu University, Japan  \nTOMOHIRO NAGASHIMA, Saarland University, Saarland Informatics Campus, Germany ANNA MARIA FEIT, Saarland University, Saarland Informatics Campus, Germany  \nProactive assistance with large language models (LLMs) has received growing attention in the human computer interaction (HCI) community. However, most past work on proactive LLMs’ assistance has focused on adult users and task-oriented settings, leaving open how such systems could support children, whose interests and needs are often expressed through gaze and other nonverbal behaviors rather than explicit requests. In this study, we focus on two key challenges of proactive assistance in children’s picture exploration: when to provide assistance and what assistance to provide based on children’s nonverbal behaviors. To address these challenges, we introduce Ollie, a gaze-informed proactive artificial intelligence (AI) assistant that offers short narrative descriptions based on where a child is looking. Ollie uses children’s gaze to estimate their attention, identify their current visual focus, and select a related picture region for the LLM to verbally describe. In a within-subject experiment, we compared gaze-informed assistance with random assistance. Results show that gaze-informed assistance kept children’s attention on their current focus for a longer period of time, and guided them more effectively to related picture regions. Children, parents, and a participating kindergarten teacher viewed Ollie positively and consider that it better matched children’s interests when compared with the random assistance. This work shows the feasibility of using gaze as an implicit input for proactive AI assistance for children and provides design implications for future child-centered AI systems.  \nCCS Concepts: • Do Not Use This Code → Generate the Correct Terms for Your Paper; Generate the Correct Terms for Your Paper; Generate the Correct Terms for Your Paper; Generate the Correct Terms for Your Paper.  \nAdditional Key Words and Phrases: Do, Not, Us, This, Code, Put, the, Correct, Terms, for, Your, Paper  \nACM Reference Format:  \nZekun Wu, Man Su, Huiyong Li, Tomohiro Nagashima, and Anna Maria Feit. 2018. Gaze-Informed Proactive AI Assistance for Children’s Picture Exploration. In Proceedings of Make sure to enter the correct conference title from your rights confirmation email (Conference acronym ’XX). ACM, New York, NY, USA, 24 pages. [https://doi.org/XXXXXXX.XXXXXXX](https://doi.org/XXXXXXX.XXXXXXX)  \n1 Introduction  \nThe advance of large language models (LLMs) has created new opportunities to use AI as a proactive partner that offers timely, context-aware assistance by anticipating users’ needs in a wide range of activities [39, 71] . While reactive  \nAuthors’ Contact Information: Zekun Wu, [wuzekun@cs.uni-saarlaned.de](wuzekun@cs.uni-saarlaned.de), Saarland University, Saarland Informatics Campus, Saarbrücken, Saarland, Germany; Man Su, [m.su@iwm-tuebingen.dee](m.su@iwm-tuebingen.dee), Tübingen Digital Teaching Lab (TüDiLab) , Leibniz-Institut für Wissensmedien (IWM Tübingen), Tübingen, Baden-Württembergs, Germany; Huiyong Li, [li.huiyong.194@m.kyushu-u.ac.jp](li.huiyong.194@m.kyushu-u.ac.jp), Research Institute for Information Technology, Kyushu University, Fukuoka, Japan; Tomohiro Nagashima, [nagashima@cs.uni-saarland.de](nagashima@cs.uni-saarland.de), Saarland University, Saarland Informatics Campus, Saarbrücken, Germany; Anna Maria Feit, [feit@cs.uni-saarland.de](feit@cs.uni-saarland.de), Saarland University, Saarland Informatics Campus, Saarbrücken, Germany.  \nPermission to make digital or hard","cbCaiqg32NnHuTpD","https://ap.wps.com/l/cbCaiqg32NnHuTpD","pdf",4286868,2,1,24,"English","en",105,"# Introduction\n## Proactive assistance and limitations for children\n## Ollie: gaze-informed proactive assistant","[{\"question\":\"What were the main results compared with random assistance?\",\"answer\":\"Gaze-informed assistance kept children’s attention on the current focus longer and guided them more effectively to related picture regions, and children, parents, and a kindergarten teacher viewed Ollie more positively than the random condition.\"}]",1784188377,60,{"code":4,"msg":31,"data":32},"ok",{"site_id":25,"language":24,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":78,"head_meta":80,"extra_data":82,"updated_unix":28},"gaze-informed-proactive-ai-assistance-for-childrens-picture-exploration","",{"@graph":36,"@context":77},[37,53,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,47,50],{"item":41,"name":42,"@type":43,"position":21},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":20},"https://docshare.wps.com/document/","Document",{"item":48,"name":12,"@type":43,"position":49},"https://docshare.wps.com/document/research-report/",3,{"item":51,"name":13,"@type":43,"position":52},"https://docshare.wps.com/document/gaze-informed-proactive-ai-assistance-for-childrens-picture-exploration/83489/",4,{"url":51,"name":13,"@type":54,"author":55,"headline":13,"publisher":57,"fileFormat":60,"inLanguage":24,"description":14,"dateModified":61,"datePublished":62,"encodingFormat":60,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":56},"Person",{"url":41,"name":58,"@type":59},"DocShare","Organization","application/pdf","2026-07-25","2026-07-16",true,{"@type":65,"interactionType":66,"userInteractionCount":20},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71],{"name":72,"@type":73,"acceptedAnswer":74},"What were the main results compared with random assistance?","Question",{"text":75,"@type":76},"Gaze-informed assistance kept children’s attention on the current focus longer and guided them more effectively to related picture regions, and children, parents, and a kindergarten teacher viewed Ollie more positively than the random condition.","Answer","https://schema.org",{"og:url":51,"og:type":79,"og:title":13,"og:site_name":58,"og:description":14},"article",{"robots":81,"canonical":51},"index,follow",{"doc_id":7,"site_id":25},{"code":4,"msg":5,"data":84},[85,89,93,97,101,106,111,114,119,122,126],{"id":21,"doc_module":4,"doc_module_name":46,"category_name":86,"show_sort_weight":87,"slug":88},"Story & Novel",90,"story-novel",{"id":20,"doc_module":4,"doc_module_name":46,"category_name":90,"show_sort_weight":91,"slug":92},"Literature",80,"literature",{"id":52,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Exam",70,"exam",{"id":98,"doc_module":4,"doc_module_name":46,"category_name":99,"show_sort_weight":29,"slug":100},5,"Comic","comic",{"id":102,"doc_module":4,"doc_module_name":46,"category_name":103,"show_sort_weight":104,"slug":105},6,"Technology",50,"technology",{"id":107,"doc_module":4,"doc_module_name":46,"category_name":108,"show_sort_weight":109,"slug":110},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":112,"slug":113},30,"research-report",{"id":115,"doc_module":4,"doc_module_name":46,"category_name":116,"show_sort_weight":117,"slug":118},9,"Religion & Spirituality",20,"religion-spirituality",{"id":117,"doc_module":4,"doc_module_name":46,"category_name":120,"show_sort_weight":117,"slug":121},"World Cup","world-cup",{"id":123,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":123,"slug":125},10,"Lifestyle","lifestyle",{"id":127,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":98,"slug":129},19,"General","general"]