PersonaMail: Learning and Adapting Personal Communication Preferences for Context-Aware Email WritingLLM-assisted writing has seen rapid adoption in interpersonal communication, yet current systems often fail to capture the subtle tones essential for effectiveness. Email writing exemplifies this challenge: effective messages require careful alignment with intent, relationship, and context beyond mere fluency. Through formative studies, we identified three key challenges: articulating nuanced communicative intent, making modifications at multiple levels of granularity, and reusing effective tone strategies across messages. We developed PersonaMail, a system that addresses these gaps through structured communication factor exploration, granular editing controls, and adaptive reuse of successful strategies. Our evaluation compared PersonaMail against standard LLM interfaces, and showed improved efficiency in both immediate and repeated use, alongside higher user satisfaction. We contribute design implications for AI-assisted communication systems that prioritize interpersonal nuance over generic text generation.2026RYRui Yao et al.City University of Hong KongHuman-LLM CollaborationAI-Assisted Writing & Text GenerationAI-Assisted Decision-Making & AutomationIUI
LiqMetCraft: A Toolkit for Creating Papercraft with Embedded Electronics By Directly Cutting and Folding Liquid-Metal-Dyed Paper-like FabricCreating interactive papercrafts often involves the processes of craft making (e.g., folding, cutting, gluing, etc.) and fabricating the embedded functional circuitry. These two processes are usually separated in the current practice, making the workflow laborious and affecting the in-paper circuit stability. To address the issue of the separated crafting and circuiting processes, we present LiqMetCraft, a toolkit for creating electronics-embedded papercrafts through an integrated process. The toolkit allows users to construct the craft structure by folding and cutting, and forms the circuit traces simultaneously. This is achieved with liquid-metal-dyed paper-like fabric which partially becomes conductive due to the cutting/folding-induced pressure while the unpressed parts of the paper remain insulated. The toolkit consists of software interfaces for papercraft design and hardware components, mainly the liquid-metal-dyed paper-like fabrics and other off-the-shelf components, for physical prototyping. The user studies shows that the participants quickly learned the toolkit and found the integrated process of circuit assembly and shape formation to be engaging and inspiring.2026QZQi Zhang et al.School of Creative Media, City University of Hong KongShape-Changing Interfaces & Soft Robotic MaterialsCircuit Making & Hardware PrototypingTangible Programming & Physical ComputingCHI
Orality: A Semantic Canvas for Externalizing and Clarifying Thoughts with SpeechPeople speak aloud to externalize thoughts as one way to help clarify and organize them. Although Speech-to-text can capture these thoughts, transcripts can be difficult to read and make sense due to disfluencies, repetitions and potential disorganization. To support thinking through verbalization, we introduce ORALITY, which extracts key information from spoken content, performs semantic analysis through LLMs to form a node-link diagram in an interactive canvas. Instead of reading and working with transcripts, users could manipulate clusters of nodes and give verbal instructions to re-extract and organize the content in other ways. It also provides AI-generated inspirational questions and detection of logical conflicts. We conducted a lab study with twelve participants comparing ORALITY against speech interaction with ChatGPT. We found that ORALITY can better support users in clarifying and developing their thoughts. The findings also identified the affordances of both graphical and conversational thought clarification tools and derived design implications.2026WLWengxi Li et al.City University of Hong KongHuman-LLM CollaborationPrototyping & User TestingAI-Assisted Writing & Text GenerationCHI
Laughing Through the Struggles: Understanding ADHD Experience and Community Engagement Through Memes and Comments on InstagramWhile public discourse often reduces Attention-Deficit Hyperactivity Disorder (ADHD) to stereotypes that overlook the invisible struggles of those who live with it, ADHD people are increasingly using social media to express their experiences on their own terms. On platforms like Instagram, memes have become a powerful and accessible medium for expressing everyday challenges through humor and relatability. This study analyzed 350 ADHD-related memes and over 28,000 associated comments to explore how ADHD was expressed and engaged with in online spaces, and consulted a neurodevelopmental science and clinical researcher. Findings show that memes depict behavioral inconsistencies, internal conflicts, and societal pressures, while comments reveal strong resonance, personal identification, and peer support, including informal self-diagnosis and shared experiences. By combining meme and comment analyses, this study contributes to digital mental health research by demonstrating how memes serve as an interactional mechanism for neurodivergent storytelling and identity formation and informing future platform design.2026FZFan Zhang et al.Independent ResearcherCognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Social Platform Design & User BehaviorMental Health Apps & Online Support CommunitiesCHI
Audience in the Loop: Viewer Feedback-Driven Content Creation in Micro-drama Production on Social MediaThe popularization of social media has led to increasing consumption of narrative content in byte-sized formats. Such micro-dramas contain fast-pace action and emotional cliffs, particularly attractive to emerging Chinese markets in platforms like Douyin and Kuaishou. Content writers for micro-dramas must adapt to fast-pace, audience-directed workflows, but previous research has focused instead on examining writers’ experiences of platform affordances or their perceptions of platform bias, rather than the step-by-step processes through which they actually write and iterative content. In 28 semi-structured interviews with scriptwriters and writers specialized in micro-dramas, we found that the short-turn-around workflow leads to writers taking on multiple roles simultaneously, iteratively adapting to storylines in response to real-time audience feedback in the form of comments, reposts, and memes. We identified unique narrative styles such as AI-generated micro-dramas and audience-responsive micro-dramas. This work reveals audience interaction as a new paradigm for collaborative creative processes on social media.2026GCGengchen Cao et al.Tsinghua - Anta Joint Research CenterCreative Collaboration & Feedback SystemsSocial Platform Design & User BehaviorLive Streaming & Content CreatorsCHI
To Cooperate or Not to Cooperate: A Systematic Review and Meta-Analysis of Human Driving Behavior in Interactions with Autonomous VehiclesCooperation among human-driven vehicles (HVs) is essential for traffic safety and efficiency. However, the emergence of autonomous vehicles (AVs) has prompted a new question: Will HVs still cooperate with AVs? Prior studies and narrative reviews yielded inconsistent findings. To answer this question, we conducted the first systematic review and meta-analysis of HV–AV cooperation, synthesizing evidence from 24 articles, 27 samples, 32 effect sizes, and 5,778 participants. Results revealed that people drive less cooperatively when interacting with AVs than with HVs (Hedges' g = -0.19, 95% CI [-0.31, -0.07]). The meta-regression revealed a significant link between cooperative driving and the year of publication, with more recent studies showing more cooperation; other moderators (e.g., data collection methods) were not significant. We discuss the implications of less cooperation for AV development, traffic regulations, and human–AI cooperation, and current challenges in theory, replicability, and ecological validity, in addition to offering recommendations for future research.2026YKYilin Kou et al.City University of Hong KongAutomated Driving Interface & Takeover DesignExternal HMI (eHMI) — Communication with Pedestrians & CyclistsV2X (Vehicle-to-Everything) Communication DesignCHI
Designing Scaffolding Cards to Facilitate LLM-Based Socratic Instruction: An Exploratory Study of Response Strategies to Support LearningThe overreliance on large language models (LLMs)-generated answers poses risks to the development of learners’ critical thinking. Socratic instruction, which follows “tutor asks, student answers” approach, could mitigate overreliance by engaging learners with LLM-generated questions rather than passively seeking answers from LLMs. However, learners without effective response strategies often produce superficial answers and therefore undermine Socratic instruction. To bridge the gap, we first conducted a formative study (N=20) to analyze learners’ dialogue logs and interviews, deriving 18 Scaffolding Cards as response strategies to guide learners in framing their answers. A subsequent mixed-methods study (N=34) demonstrated that Scaffolding Cards improved critical thinking, optimized cognitive load allocation, and increased learning satisfaction compared to that without scaffolds. Our work reconfigures scaffolding by incorporating state-aware, agency-preserving, and function-transparent support. We further provide actionable implications for designing responsive and personalized scaffolding to facilitate learner-LLM interaction, introducing innovative perspectives for reclaiming learner agency in LLM-driven education.2026LMLujin Mao et al.The Hong Kong Polytechnic UniversityHuman-LLM CollaborationIntelligent Tutoring Systems & Learning AnalyticsParticipatory DesignCHI
PuppetChat: Fostering Intimate Communication through Bidirectional Actions and MicronarrativesAs a primary channel for sustaining modern intimate relationships, instant messaging facilitates frequent connection across distances. However, today's tools often dilute care; they favor single tap reactions and vague emojis that do not support two way action responses, do not preserve the feeling that the exchange keeps going without breaking, and are weakly tied to who we are and what we share. To address this challenge, we present PuppetChat, a dyadic messaging prototype that restores this expressive depth through embodied interaction. PuppetChat uses a reciprocity aware recommender to encourage responsive actions and generates personalized micronarratives from user stories to ground interactions in personal history. Our 10-day field study with 11 dyads of close partners or friends revealed that this approach enhanced social presence, supported more expressive self disclosure, and sustained continuity and shared memories.2026EWEmma Jiren Wang et al.Virginia TechDigital Emotional Expression & TransmissionAffective Human-Computer DialogueEmpathy & Emotional DesignCHI
Bondi: Designing Tangible and Multimodal Interfaces for Continuing Bonds in Pet BereavementPet ownership creates profound human-animal bonds, making pet loss significant. However, compared to human loss, Human- Computer Interaction (HCI) has given pet loss less attention. Addressing this, we conducted an exploratory mixed-methods study. The study began with a large-scale survey (N=611) revealing critical challenges: a strong desire to preserve memories but limited support for continuing bonds. Built upon these findings, our participatory design sessions(N=10) co-designed Bondi, a tangible prototype sup- porting continuing bonds through multimodal and customizable interactions (e.g. touch, sound, and light), evoking pets’ unique sounds, tail movements, and lighting effects. We then conducted a three-week field-deployment study with four participants to eval- uate how Bondi facilitated the maintenance of bonds with their deceased pets. Results showed that the customization and multi- modality evoked vivid recollections, lowering the social barrier for grief sharing. Bondi fostered comforting and non-intrusive connec- tions with pet memories. Furthermore, the study distilled design considerations for future pet bereavement support.2026NXNingchang Xiong et al.City University of Hong KongTangible User Interface DesignPhysical-Digital Hybrid InteractionEmpathy & Emotional DesignCHI
AnkleType: A Hands- and Eyes-free Foot-based Text Entry Technique in Virtual RealityVirtual Reality (VR) emphasizes immersive experiences, while text entry often requires hands or visual attention, which may disrupt the interaction flows in VR. We present \sysName, a hand- and eye-free text-entry technique that leverages ankle-based gestures for both standing and sitting situations. We began with two preliminary studies: one investigated the movement range of users' ankles, and the other elicited user-preferred ankle gestures for text-entry-related operations. The findings of these two studies guided our design of AnkleType. To optimize AnkleType's keyboard layout for eye-free input, we conducted a user study to capture the users’ natural ankle spatial awareness with a computer-simulated language test. Through a pairwise comparison study, we designed a bipedal input strategy for sitting (BPSit) and a unipedal input strategy for standing (UPStand). We further evaluated our design with a 7-day longitudinal study with 12 participants. Participants achieved an average typing speed of 15.05 WPM with UPStand and 16.70 WPM with BPSit in the visual condition, and 11.15 WPM and 12.87 WPM, respectively in the eyes-free condition.2026XLXiyun Luo et al.Shantou UniversityHand Gesture RecognitionEye Tracking & Gaze InteractionSocial & Collaborative VRCHI
Hear You in Silence: Designing for Active Listening in Human Interaction with Conversational Agents Using Context-Aware PacingIn human conversation, empathic dialogue requires nuanced temporal cues indicating whether the conversational partner is paying attention. This type of "active listening" is overlooked in the design of Conversational Agents (CAs), which use the same pacing for one conversation. To model the temporal cues in human conversation, we need CAs that dynamically adjust response pacing according to user input. We qualitatively analyzed ten cases of active listening to distill five context-aware pacing strategies: Reflective Silence, Facilitative Silence, Empathic Silence, Holding Space, and Immediate Response. In a between-subjects study (N=50) with two conversational scenarios (relationship and career-support), the context-aware agent scored higher than static-pacing control on perceived human-likeness, smoothness, and interactivity, supporting deeper self-disclosure and higher engagement. In the career-support scenario, the CA yielded higher perceived listening quality and affective trust. This work shows how insights from human conversation like context-aware pacing can empower the design of more empathic human-AI communication.2026ZJZhihan Jiang et al.The University of Hong KongConversational ChatbotsAffective Human-Computer DialogueAgent Personality & AnthropomorphismCHI
InspirationGraph for Progressive Design Space ExplorationText-to-image (T2I) models demonstrate strong generative capabilities and are increasingly used in design. However, their support for early exploratory ideation remains limited. Their linear, one-shot interaction paradigm aligns more closely with convergent, refinement-oriented stages of design. To address this gap, we present an interaction paradigm supporting early-stage ideation with T2I models, with a particular focus on novice designers. It introduces a dimension–attribute dictionary to guide prompt construction progressively and employs a dynamic, editable tree structure to help users organize and navigate their design space. Based on this paradigm, we developed a prototyping tool named InspirationGraph, focusing on the product design field. The results from a user study involving 24 participants highlight how this structured exploration approach supports divergent thinking and reduces cognitive load. We also uncover varying ideation patterns among designers and offer actionable insights into how T2I systems can be reimagined to better support the early-stage design.2026SLSuxiang Ling et al.School of Design, HUNAN UniversityGenerative AI (Text, Image, Music, Video)Creative Collaboration & Feedback SystemsMotor Impairment Assistive Input TechnologiesCHI
Plotania: Exploring Transparency Trade-offs in AI Co-Writing Through Virtual Readers and Transparent AttributionCurrent AI writing tools aim to enhance authorial capacity yet often diminish authorial control and lack timely audience feedback. Through a formative study with fiction authors (N=10), we uncovered two critical tensions in human–AI co-writing: balancing AI scaffolding with authorial ownership, and the absence of contextual audience perspectives that shape storytelling during drafting. Guided by these insights, we designed Plotania, a co-writing system that combines proactive virtual readers offering real-time audience reactions with transparent attribution layers. A controlled study (N=20) revealed complex and counterintuitive effects: virtual reader feedback increased audience awareness but decreased perceived creative agency, transforming individual authorship into collaborative performance. Transparent attribution raised awareness of AI contributions but triggered identity anxiety and reduced AI usage. These findings reveal fundamental trade-offs in transparency design. We contribute design principles for "agency-preserving transparency" that balance information provision with creative empowerment, informing future transparency design in human-AI creative collaboration.2026YHYufeng Hu et al.Tsinghua UniversityHuman-LLM CollaborationAI-Assisted Writing & Text GenerationCreative Collaboration & Feedback SystemsCHI
Living with Data: Exploring Physicalization Approaches to Sedentary Behavior Intervention for Older Adults in Everyday LifeSedentary behavior is a critical health risk for older adults. Although digital interventions are widely available, they primarily rely on screen-based notifications that can feel clinical or cognitively demanding, and are thus often ignored over time. This paper presents a three-phase Research through Design methodology to explore data physicalization approaches that ambiently represent sedentary data patterns using decor artifacts in older adults’ homes. These artifacts transformed abstract data into aesthetic, evolving forms that became part of the domestic landscape. Our research revealed how these physicalizations fostered self-reflection, family conversations, and encouraged active lifestyles. We demonstrate how qualities like aesthetic ambiguity and slow revelation can empower older adults, fostering a reflective relationship with their well-being. Ultimately, we argue that creating data physicalizations for older adults necessitates a shift from merely informing users to enabling them to live with and through their data.2026SHSiying Hu et al.City University of Hong KongData PhysicalizationElderly Care & Dementia SupportBehavior Change & Reflection TechnologyCHI
Vistoria: A Multimodal System to Support Fictional Story Writing through Instrumental Image-Text Co-EditingHumans think visually—we remember in images, dream in pictures, and use visual metaphors to communicate. Yet, most creative writing tools remain text-centric, limiting how writers plan and translate ideas. We present Vistoria, a system for synchronized image-text co-editing in fictional story writing. A formative Wizard-of-Oz co-design study with 10 story writers revealed how sketches, images, and text serve as essential elements for ideation and organization. Drawing on theories of Instrumental Interaction, Vistoria introduces instrumental operations—Lasso, Collage, Perspective Shift, and Filter that enable seamless narrative exploration across modalities. A controlled study with 12 participants shows that co-editing enhances expressiveness, immersion, and collaboration, opening space for writers to follow divergent story directions and craft more vivid, detailed narratives. While multimodality increased cognitive demand, participants reported stronger senses of ownership and agency. These findings demonstrate how multimodal co-editing expands creative potential by balancing abstraction and concreteness in narrative development.2026KFKexue Fu et al.City University of Hong KongAI-Assisted Creative WritingCreative Collaboration & Feedback SystemsCHI
SketchDynamics: Exploring Free-Form Sketches for Dynamic Intent Expression in Animation GenerationSketching provides an intuitive way to convey dynamic intent in animation authoring (i.e., how elements change over time and space), making it a natural medium for automatic content creation. Yet existing approaches often constrain sketches to fixed command tokens or predefined visual forms, overlooking their free-form nature and the central role of humans in shaping intention. To address this, we introduce an interaction paradigm where users convey dynamic intent to a vision–language model via free-form sketching, instantiated here in a sketch storyboard to motion graphics workflow. We implement an interface and improve it through a three-stage study with 24 participants. The study shows how sketches convey motion with minimal input, how their inherent ambiguity requires users to be involved for clarification, and how sketches can visually guide video refinement. Our findings reveal the potential of sketch–AI interaction to bridge the gap between intention and outcome, and demonstrate its applicability to 3D animation and video generation.2026BLBoyu Li et al.The Hong Kong University of Science and Technology3D Modeling & AnimationCreative Coding & Computational ArtCreative Collaboration & Feedback SystemsCHI
Scaffolding Metacognition with GenAI: Exploring Design Opportunities to Support Task Management for University Students with ADHDFor university students transitioning to an independent and flexible lifestyle, having ADHD poses multiple challenges to their academic task management, which are closely tied to their metacognitive struggles—difficulties in awareness and regulation of one’s own thinking processes. The recently surged Generative AI shows promise to mitigate these gaps with its advanced information understanding and generation capabilities. As an exploratory step, we conducted co-design sessions with 20 university students diagnosed with ADHD, followed by interviews with five experts specialized in ADHD intervention. Adopting a metacognitive lens, we examined participants’ ideas on GenAI-based task management support and experts’ assessments, which led to three design directions: providing cognitive scaffolding to enhance task and self-awareness, promoting reflective task execution for building metacognitive abilities, and facilitating emotional regulation to sustain task engagement. Drawing on these findings, we discuss opportunities for GenAI to support the metacognitive needs of neurodivergent populations, offering future directions for both research and practice.2026ZZZihao Zhu et al.City University of Hong KongGenerative AI (Text, Image, Music, Video)Cognitive Impairment & Neurodiversity (Autism, ADHD, Dyslexia)Mental Health Apps & Online Support CommunitiesCHI
Privacy Control in Conversational LLM Platforms: A Walkthrough StudyLarge language models (LLMs) are increasingly integrated into daily life through conversational interfaces, processing user data via natural language inputs and exhibiting advanced reasoning capabilities, which raises new concerns about user control over privacy. While much research has focused on potential privacy risks, less attention has been paid to the data control mechanisms these platforms provide. This study examines six conversational LLM platforms, analyzing how they define and implement features for users to access, edit, delete, and share data. Our analysis reveals an emerging paradigm of data control in conversational LLM platforms, where user data is generated and derived through interaction itself, natural language enables flexible yet often ambiguous control, and multi-user interactions with shared data raise questions of co-ownership and governance. Based on these findings, we offer practical insights for platform developers, policymakers, and researchers to design more effective and usable privacy controls in LLM-powered conversational interactions.2026ZLZhuoyang LI et al.Eindhoven University of TechnologyExplainable AI (XAI)Privacy by Design & User ControlPrivacy Perception & Decision-MakingCHI
Desirable Unfamiliarity: Insights from Eye Movements on Engagement and Readability of Dictation InterfacesTranscripts displayed on dictation interfaces can be hard to read due to recognition errors and disfluencies. LLM-based text auto-correction could help, but changing the text during production could lead to distraction and unintended phrasing. To understand how to balance readability, attention, and accuracy, we conducted an eye-tracking experiment with 20 participants to compare five dictation interfaces: PLAIN (real-time transcription), AOC (periodic corrections), RAKE (keyword highlights), GP-TSM (grammar-preserving highlights), and SUMMARY (LLM-generated abstractive summary). By analyzing participants’ gaze patterns during speech composition and reviewing processes, we found that during composition, participants spent only 7%-11% of their time in active reading regardless of the interface. Although SUMMARY introduced unfamiliar words and phrasing during composition, it was easier to read and more preferred by participants. Our findings suggest a high user tolerance for altering spoken words in LLM-enabled diction interfaces.2026ZLZhaohui Liang et al.University of Chinese Academy of SciencesLanguage Model-Assisted Text InputAI-Assisted Writing & Text GenerationEye Tracking & Gaze InteractionCHI
CoNode: Visualizing Workflows for Knowledge Reuse and Recombination in Team–AI Collaborative DesignIn early-stage industrial design, teams generate essential but fragile process knowledge—semantic tags, sketches, exploration paths—that is rarely captured or reused but which may be useful at latter design stages, and AI could be used for this purpose. Yet existing AI creativity tools remain outcome-oriented, offering limited support for preserving, tracing, or recombining underlying reasoning. Our formative study (N=6) revealed persistent challenges in team–AI ideation across sessions and collaborators, including semantic–visual fragmentation, context loss, and cross-tool disruption. These insights inspired CoNode, a two-layer system that embeds AI nodes within a shared whiteboard through triplet workflows and augments them with workflow-level consolidation, reuse, and recombination via the CoSense module. We conducted a two-stage evaluation: User Study I (N=12) validates CoNode’s foundational interaction paradigm layer, and User Study II (N=30) evaluates its process-oriented knowledge layer. Results show that CoNode significantly improves knowledge consolidation, reuse, and recombination, effectively facilitating the collaborative processes and demonstrating how generative AI can evolve process knowledge across collaborative rounds.2026YZYang Zhou et al.School of Design, Hunan UniversityHuman-LLM CollaborationCreative Collaboration & Feedback SystemsAI-Assisted Decision-Making & AutomationCHI