{"id":246452,"date":"2026-08-31T00:32:25","date_gmt":"2026-08-31T00:32:25","guid":{"rendered":"https:\/\/iui.acm.org\/2027\/?page_id=246452"},"modified":"2026-08-31T00:32:43","modified_gmt":"2026-08-31T00:32:43","slug":"accepted-workshops","status":"publish","type":"page","link":"https:\/\/iui.acm.org\/2027\/program\/accepted-workshops\/","title":{"rendered":"Accepted Workshops"},"content":{"rendered":"\n<h2 class=\"wp-block-heading has-x-large-font-size\" style=\"padding-top:var(--wp--preset--spacing--50);padding-bottom:var(--wp--preset--spacing--50)\">Accepted Workshops<\/h2>\n\n\n\n<h3 class=\"wp-block-heading\">HUMANE-LLM: Workshop on Human-Centered and Responsible LLMs for Agency-Preserving Intelligent User Interfaces &nbsp;<\/h3>\n\n\n\n<p>Noemi Mauro, University of Torino, Italy<br>Julia Neidhardt, CDL-RecSys, TU Wien, Austria<br>Yashar Deldjoo, Polytechnic University of Bari, Italy<br>Ludovico Boratto, University of Cagliari, Italy<br>Dominik Kowald, University of Graz and Know Center Research GmbH, Austria<\/p>\n\n\n\n<p>Large Language Models (LLMs) are reshaping Intelligent User Interfaces by enabling systems that can converse, personalize, recommend, explain, and support decision-making across complex user-facing tasks. Yet, their integration into adaptive interfaces also raises new questions about interaction design, agency, responsibility, transparency, and evaluation. The HUMANE-LLM workshop provides a forum for studying how LLM-based IUIs can be designed, evaluated, and governed in ways that remain human-centered, controllable, accountable, and aligned with users&#8217; needs and values. The workshop brings together researchers and practitioners from IUI, HCI, recommender systems, NLP, responsible AI, and applied domains such as education, healthcare, and decision support. &nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/humanellm.github.io\/2027\">https:\/\/humanellm.github.io\/2027<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">SAMAS: Shaping the Future of AI-Mediated Communication in Asymmetric Scenarios &nbsp;<\/h3>\n\n\n\n<p>Ilhan Aslan, TH K\u00f6ln<br>Matthias Kraus, University of Augsburg<br>Verena Fuchsberger, University of Salzburg<br>Matthias B\u00f6hmer, TH K\u00f6ln<br>Elisabeth Andr\u00e9, University of Augsburg<br>Timothy Merritt, Aalborg University<\/p>\n\n\n\n<p>Human-to-human communication is increasingly technology-mediated. Contemporary societies face growing communication asymmetries driven by language barriers, cultural gaps, and digital divides. While rapid advances in wearables, LLMs, and affective computing offer real-time assistance, current research remains heavily engineering-centric. This interdisciplinary workshop shifts the focus toward human-centered and entanglement perspectives, examining these dynamics across two core scenarios: co-located one-to-one encounters using wearable displays, and one-to-many remote settings like interactive live streaming. Together, we will critically explore how users experience, negotiate, or resist AI augmentation to shape future, socially acceptable communication ecologies. &nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/hcai.eu\/behave-ai\">https:\/\/hcai.eu\/behave-ai<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">MINDXR: Psychological Risks in the Convergence of Extended Reality and AI &nbsp;<\/h3>\n\n\n\n<p>Andrea Bellucci (UC3M)<br>Niklas Ravaja (UH)<br>Giuseppe Riccardi (UniTN)<br>Giulio Jacucci (UH)<\/p>\n\n\n\n<p>XR is becoming a primary interface for intelligent systems as AI migrates from screens into headsets, smart glasses, embodied conversational agents, and always-on multimodal interfaces. This convergence raises psychological risks to identity, autonomy, attachment, perception of reality, and agency. These risks are distinct from those posed by screen-based AI or XR in isolation. Existing work treats trustworthy AI, explainability, and immersive interaction separately, leaving the implications of their intersection underexplored. MINDXR convenes researchers from intelligent user interfaces, XR, psychology, affective computing, and responsible AI to characterize these emerging risks, share empirical evidence, discuss design and governance strategies, and establish a shared research agenda for immersive AI that supports rather than undermines psychological wellbeing.<\/p>\n\n\n\n<p><a href=\"https:\/\/www.mv.helsinki.fi\/home\/jacucci\/mindxr\/#cfp\">https:\/\/www.mv.helsinki.fi\/home\/jacucci\/mindxr\/#cfp<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">HIMAS: Human-Centered Interactive Multimodal AI Systems<\/h3>\n\n\n\n<p>Gon\u00e7alo Marcelino, University of Amsterdam, The Netherlands<br>Melika Ayoughi, University of Amsterdam, The Netherlands<br>Sarah Binta Alam Shoilee, Vrije Universiteit Amsterdam, The Netherlands<br>Omar Shahbaz Khan, IT University of Copenhagen, Denmark<br>Andrea Mauri, Universit\u00e9 Claude Bernard Lyon 1, France<br>Yen-Chia Hsu, University of Amsterdam, The Netherlands<br>Maximilian T. Fischer, University of Konstanz, Germany<br>Senthil Chandrasegaran, TU Delft, The Netherlands<br>Marcel Worring, University of Amsterdam, The Netherlands&#8221;<\/p>\n\n\n\n<p>This workshop brings together researchers from multimedia analytics, information visualization, multimodal AI, and human-computer interaction to advance the design, development, and evaluation of Human-Centered Interactive Multimodal AI Systems (HIMAS). Organized as a full-day mini-conference, the workshop is structured around three themes: integrating multimodal AI with interactive interfaces, designing HIMAS for effective human-AI collaboration, and adapting these systems across domains. Through paper presentations, system demonstrations, and structured discussions, we aim to identify shared challenges, establish a research agenda, and foster a lasting cross-disciplinary research community. &nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/himas-workshop.com\">https:\/\/himas-workshop.com<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">LEXFLOW: Workshop on Agentic Workflows for Human-AI Legal Reasoning<\/h3>\n\n\n\n<p>Sirui Han(HKUST), <br>Yuyao Zhang(HKUST), <br>Yidan Huang(HKUST),<br>Chuxue Cao(HKUST), <br>Yujin Zhou(HKUST), <br>Guoying Lu(HKUST)<\/p>\n\n\n\n<p>LEXFLOW is a full-day workshop on intelligent interfaces for agentic legal reasoning workflows. It brings together researchers from HCI, IUI, AI and Law, and human-centered AI to explore how legal AI systems can better support process-level supervision, including inspection, steering, verification, contestation, and accountability. Through invited talks, paper and demo presentations, workflow mapping, co-design activities, live critique, and collaborative synthesis, participants will develop reusable design patterns, workflow artifacts, evaluation questions, and a shared research agenda for more transparent and accountable human-AI legal reasoning systems. \u00a0 <\/p>\n\n\n\n<p><a href=\"https:\/\/trista-z.github.io\/LEXFLOW\/ \">https:\/\/trista-z.github.io\/LEXFLOW\/ <\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">AI CHAOS! 2nd Workshop on the Challenges for Human Oversight of AI Systems \u00a0<\/h3>\n\n\n\n<p>Dr. Tim Schrills, University of L\u00fcbeck, Germany (primary contact)<br>Dr. Patricia Kahr, University of Zurich, Switzerland<br>Prof. Dr. Markus Langer, University of Freiburg, Germany<br>Prof. Harmanpreet Kaur, PhD, University of Minnesota, USA<br>Prof. Ujwal Gadiraju, PhD, Delft University of Technology, The Netherlands<\/p>\n\n\n\n<p>Human oversight has become the central safeguard between increasingly capable AI systems and the people affected by them. With the EU AI Act&#8217;s high-risk obligations now in force, effective oversight by natural persons \u2014 including appropriate human-machine interface tools \u2014 has moved from regulatory vision to design reality. Yet oversight frequently fails in practice: overseers rubber-stamp outputs, miscalibrate reliance, or lack the visibility and controls to intervene, especially with agentic systems. Whether oversight is meaningful or merely nominal is largely decided at the user interface. AI CHAOS! convenes researchers and practitioners around one question: how do we design, build, and evaluate intelligent user interfaces that make human oversight of AI actually work? \u00a0<\/p>\n\n\n\n<p><a href=\"https:\/\/sites.google.com\/view\/aichaos\/iui-2027?authuser=0\">https:\/\/sites.google.com\/view\/aichaos\/iui-2027?authuser=0<\/a><\/p>\n\n\n\n<h3 class=\"wp-block-heading\">Models in Human-AI Interaction: Methods and Challenges in the Generative and Agentic AI Era<\/h3>\n\n\n\n<p>T\u00e9o Sanchez, LMU Munich<br>Bhada Yun, ETH Z\u00fcrich<br>Prerna Ravi, MIT<br>Laura Sch\u00fctz, TU Munich<br>Anna Neumann, University Duisburg-Essen<br>Robin Chan, ETH Z\u00fcrich<br>April Yi Wang, ETH Z\u00fcrich<br>Qiaosi Wang, CMU HCII<br>Sumit Asthana, Microsoft<\/p>\n\n\n\n<p>The mental model construct is widely used in HCI to refer to the knowledge structure people hold to reason about computing systems. Yet the construct is often used interchangeably with related concepts (e.g. folk theories, sensemaking) and methods of studying it are many and diverse. Generative and agentic AI systems further complicate mental model formation and elicitation as such systems are opaque by design and increasingly act on users&#8217; behalf across files, applications, and on the web. Together, these challenges may hinder the commensurability of research on people\u2019s mental models of AI systems. The MM\/AI workshop calls for a critical reassessment of how we understand and study mental models in human-AI interaction research. It aims to foster theoretical and methodological exchange on mental models in human\u2013AI interaction, identify open challenges, and develop directions for future research. &nbsp;<\/p>\n\n\n\n<p><a href=\"https:\/\/mentalmodelsofai.vercel.app\">https:\/\/mentalmodelsofai.vercel.app<\/a><\/p>\n","protected":false},"excerpt":{"rendered":"<p>Accepted Workshops HUMANE-LLM: Workshop on Human-Centered and Responsible LLMs for Agency-Preserving Intelligent User Interfaces &nbsp; Noemi Mauro, University of Torino, [&hellip;]<\/p>\n","protected":false},"author":9,"featured_media":0,"parent":246379,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"site-sidebar-layout":"default","site-content-layout":"","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-246452","page","type-page","status-publish","hentry"],"_links":{"self":[{"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/pages\/246452","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/pages"}],"about":[{"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/types\/page"}],"author":[{"embeddable":true,"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/users\/9"}],"replies":[{"embeddable":true,"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/comments?post=246452"}],"version-history":[{"count":2,"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/pages\/246452\/revisions"}],"predecessor-version":[{"id":246455,"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/pages\/246452\/revisions\/246455"}],"up":[{"embeddable":true,"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/pages\/246379"}],"wp:attachment":[{"href":"https:\/\/iui.acm.org\/2027\/wp-json\/wp\/v2\/media?parent=246452"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}