Do Entropic Measurements of the Diversity of AI-generated Images Match Human Judgement? This paper proposes that the ability to generate diverse outputs in response to a single prompt is necessary for text-to-image models to become more effective creativity support tools. It formalises the problem of measuring the diversity of generated text and images, with an emphasis on interactive, exploratory use in open-ended and creative tasks. It suggests, motivated by research in the psychology of creativity, that diversity should sit alongside image quality and fit-to-prompt as critical measures in this setting. The paper adapts several diversity measures from the literature to this task, then explores how they compare to human diversity ratings. These evaluations show that algorithmic measures of diversity can be a useful proxy for human ratings, with both declining in accuracy as the difficulty of the task increases. The paper concludes with an exploratory qualitative analysis of the factors involved in human diversity judgments to guide future research in this emerging area.2026KGKazjon Grace et al.The University of SydneyGenerative AI (Text, Image, Music, Video)Explainable AI (XAI)Creative Collaboration & Feedback SystemsCHI
Auditorily Embodied Conversational Agents: Effects of Spatialization and Situated Audio Cues on Presence and Social PerceptionEmbodiment can enhance conversational agents, such as increasing their perceived presence. This is typically achieved through visual representations of a virtual body; however, visual modalities are not always available, such as when users interact with agents using headphones or display-less glasses. In this work, we explore auditory embodiment. By introducing auditory cues of bodily presence — through spatially localized voice and situated Foley audio from environmental interactions — we investigate how audio alone can convey embodiment and influence perceptions of a conversational agent. We conducted a 2 (spatialization: monaural vs. spatialized) × 2 (Foley: none vs. Foley) within-subjects study, where participants (n=24) engaged in conversations with agents. Our results show that spatialization and Foley increase co-presence, but reduce users’ perceptions of the agent’s attention and other social attributes.2026YCYi Fei Cheng et al.Carnegie Mellon UniversityAffective Human-Computer DialogueSpatial Audio & 3D SoundAffective Feedback & Emotion Regulation InterfacesCHI
TactDeform: Finger Pad Deformation Inspired Spatial Tactile Feedback for Virtual Geometry ExplorationSpatial tactile feedback can enhance the realism of geometry exploration in virtual reality applications. Current vibrotactile approaches often face challenges with the spatial and temporal resolution needed to render different 3D geometries. Inspired by the natural deformation of finger pads when exploring 3D objects and surfaces, we propose TactDeform, a parametric approach to render spatio-temporal tactile patterns using a finger-worn electro-tactile interface. The system dynamically renders electro-tactile patterns based on both interaction contexts (approaching, contact, and sliding) and geometric contexts (geometric features and textures), emulating deformations that occur during real-world touch exploration. Results from a user study \rr{(N=24)} show that the proposed approach enabled high texture discrimination and geometric feature identification compared to a baseline. Informed by results from a free 3D-geometry exploration phase, we provide insights that can inform future tactile interface designs.2026YDYihao Dong et al.The University of SydneyMid-Air Haptics (Ultrasonic)Haptic WearablesShape-Changing Interfaces & Soft Robotic MaterialsCHI
Envisioning Audio Augmented Reality in Everyday LifeWhile visual augmentation dominates the augmented reality landscape, devices like Meta Ray-Ban audio smart glasses signal growing industry movement toward audio augmented reality (AAR). Hearing is a primary channel for sensing context, anticipating change, and navigating social space, yet AAR’s everyday potential remains underexplored. We address this gap through a collaborative autoethnography (N=5, authoring) and an online survey (N=74). We identify ten roles for AAR, grouped into three categories: task- and utility-oriented, emotional and social, and perceptual collaborator. These roles are further layered with a rhythmic and embodied collaborator framing, mapping them onto micro-, meso-, and macro-rhythms of everyday life. Our analysis surfaces nuanced tensions, such as blocking distractions without erasing social presence, highlighting the need for context-aware design. This paper contributes a foundational and forward-looking framework for AAR in everyday life, providing design groundwork for systems attuned to daily routines, sensory engagement, and social expectations.2026TTTram Thi Minh Tran et al.School of Architecture, Design and Planning, The University of SydneySpatial Audio & 3D SoundContext-Aware ComputingAffective Human-Computer DialogueCHI
SituFont: A Just-in-Time Adaptive Intervention Interface for Enhancing Mobile Readability in Situational Visual ImpairmentsSituational visual impairments (SVIs) hinder mobile readability, causing discomfort and limiting information access. Building on prior work in adaptive typography and accessibility, this paper presents SituFont, a context-aware and human-in-the-loop adaptive typography adjustment approach that enhances smartphone mobile readability by dynamically adjusting font parameters based on real-time contextual changes. Using smartphone sensors and a human-in-the-loop approach, SituFont personalizes text presentation to accommodate personal factors (e.g., fatigue, distraction) and environmental conditions (e.g., lighting, motion, location). To inform its design, we conducted formative interviews (N=15) to identify key SVI factors and controlled experiments (N=18) to quantify their impact on optimal text parameters. A comparative user study (N=12) across eight simulated SVI scenarios demonstrated SituFont's effectiveness in improving smartphone mobile readability in terms of improved efficiency and reduced workload compared with a non-trivial manual adjustment baseline.2026JCJingruo Chen et al.Cornell UniversityMobile Accessibility DesignBehavior Change & Reflection TechnologyContext-Aware ComputingCHI
Understanding the Effects of Interaction on Emotional Experiences in VRVirtual reality has been effectively used for eliciting emotions, yet most research focuses on the intensity of affective responses rather than on how interaction influences those experiences. To address this gap, we advance a validated VR emotion-elicitation dataset through two key extensions. First, we add a new high-arousal, high-valence scene and validate its effectiveness in a within-subject study (N=24). Second, we incorporate interactive elements into each scene, creating both interactive and non-interactive versions to examine the impact of interaction on emotional responses. We evaluate interaction through a multimodal approach combining subjective ratings and physiological signals to capture both conscious and unconscious affective responses. Our evaluation study (N=84) shows that interaction not only amplifies emotions but modulates them in context, supporting coping in negative scenes and enhancing enjoyment in positive scenes. These findings highlight the potential of scene-tailored interaction for different applications, where regulating emotions is as important as eliciting them.2026ZKZheyuan Kuang et al.The University of SydneyImmersion & Presence ResearchAffective Feedback & Emotion Regulation InterfacesSocial & Collaborative VRCHI
Enabling Partial Participation in Remote MeetingsWe propose and explore the concept of Partial Participation, facilitating remote collaborators to contribute to meetings in which they are not able to fully participate via an AI agent acting as a proxy. During the meeting, users can monitor LLM-generated real-time meeting updates and respond to questions posed by other attendees. Through a mixed-methods user study with 24 participants using our prototype, ProxyMe, we investigated how the frequency of updates (high vs. low) and the type of response style (multiple choice vs. text input) impact perceived presence and mental workload. Our findings reveal that no single setup is universally optimal, and the partial participation fosters a moderate level of social presence and attentional mental workload. Our contributions introduce partial participation as a new paradigm for remote collaboration and highlight how AI can mediate participation when full presence is not feasible.2026ZBZhongyi Bai et al.University of SydneyRemote Work Tools & ExperienceDistributed Team CollaborationHuman-LLM CollaborationCHI
Exploring the Impacts of Background Noise on Auditory Stimuli of Audio-Visual eHMIs for Hearing, Deaf, and Hard-of-Hearing PeopleExternal Human-Machine Interfaces (eHMIs) have been proposed to enhance communication between automated vehicles (AVs) and pedestrians, with growing interest in multi-modal designs such as audio-visual eHMIs. Just as poor lighting can impair visual cues, a loud background noise may mask the auditory stimuli. However, its effects within these systems have not been examined, and little is known about how pedestrians --- particularly Deaf and Hard-of-Hearing (DHH) people --- perceive different types of auditory stimuli. We conducted a virtual reality study (Hearing N=25, DHH N=11) to examine the effects of background noise (quiet and loud) on auditory stimuli (baseline, bell, speech) within an audio-visual eHMI. Results revealed that: (1) Crossing experiences of DHH pedestrians significantly differ from Hearing pedestrians. (2) Loud background noise adversely affects pedestrians' crossing experiences. (3) Providing an additional auditory eHMI (bell/speech) improves crossing experiences. We outlined four practical implications for future eHMI design and research.2026WXWenge Xu et al.Birmingham City UniversityExternal HMI (eHMI) — Communication with Pedestrians & CyclistsAudio Accessibility (Captions, Sign Language, Vibration)CHI
Narratives and Perspectives: How AI Summaries Steer Users' Opinions and Engagement on Social MediaAI summaries on social media are reshaping how users form opinions about political topics, yet their influence remains largely unexamined despite their widespread deployment. This paper investigates how two types of AI summaries affect user opinions and engagement: textual summaries of discussion narratives and percentage breakdowns of agreement/disagreement. Through a 144-participant experiment on simulated online discussion threads, we found that displaying commenter agreement percentages amplified social conformity towards the majority views beyond reading comments alone. Conversely, AI narrative summaries created misperceptions of balance in polarised threads, reducing opinion change. While these summaries did not influence participants’ willingness to engage, toxic discussions deterred participation even when participants held majority views. Based on our findings, we provide critical design interventions for industry and researchers to mitigate these tools' polarising effects, paving the way for responsible AI deployment on social media platforms.2026JGJarod Govers et al.University of MelbourneConversational ChatbotsMisinformation & Fact-CheckingAI Ethics, Fairness & AccountabilityCHI
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
Generative AI and Creative Mediums for Youth’s Emotion Regulation: An Interview Study with CliniciansEmotion regulation (ER) is essential to youth well-being, and cognitive-behavioral therapy (CBT) is an established approach for building ER skills. Clinicians often use creative mediums such as visuals and narratives to support ER through CBT, yet access and personalization remain limited. Generative AI (GenAI) shows promise for addressing these limitations, but its benefits and risks in youth ER remain underexplored, underscoring the need for expert perspectives. We interviewed 20 ER specialists--psychotherapists, art therapists, and psychiatrists--using a GenAI technological probe that generated CBT-based visuals and narratives. Clinicians highlighted GenAI’s potential as a “bridge” to help youth concretely identify and express emotions, practice personalized coping skills, and mediate ER conversations between home and clinics. They also cautioned that the vividness and unpredictability of GenAI outputs may trigger trauma or reinforce maladaptive thinking. We propose psychologically grounded design implications for GenAI to foster safe, engaging youth ER as a foundation for lifelong well-being.2026DYDaeun Yoo et al.University of WashingtonGenerative AI (Text, Image, Music, Video)Mental Health Apps & Online Support CommunitiesMental Health Technology for YouthCHI
Animated Public Furniture as an Interaction Mediator: Engaging Passersby In-the-Wild with Robotic BenchesUrban HCI investigates how digital technologies shape human behaviour within the social, spatial, temporal dynamics of public space. Meanwhile, robotic furniture research demonstrates how the purposeful animation of mundane utilitarian elements can influence human behaviour in everyday contexts. Taken together, these strands highlight an untapped opportunity to investigate how animated public furniture could mediate social interaction in urban environments. In this paper, we present the design process and in-the-wild study of mobile robotic benches that reconfigure with a semi-outdoor public space. Our findings show that the gestural performance of the benches manifested three affordances perceived by passersby, they activated engagement as robots, redistributed engagement as spatial elements, and settled engagement as infrastructure. We proposed an Affordance Transition Model (ATM) describing how robotic furniture could proactively facilitate transition between these affordances to engage passersby. Our study bridges robotic furniture and urban HCI to activate human experience with the built environment purposefully.2026XYXinyan Yu et al.School of Architecture, Design and Planning, The University of SydneySmart Cities & Urban SensingSocial Robot InteractionPhysical-Digital Hybrid InteractionCHI
Gaze and Speech in Multimodal Human-Computer Interaction: A Scoping ReviewMultimodal interaction has long promised to make interfaces more intuitive and effective by combining complementary inputs. Among these, gaze and speech form a compelling pairing: gaze provides rapid spatial grounding, while speech conveys rich semantic information. Together, they offer rich cues for understanding user behaviour and intent. Yet despite decades of exploration, the research remains fragmented, making this synthesis timely as these inputs mature and are integrated into consumer-ready devices. This scoping review examined 103 studies published between 1991 and 2025, organised into \emph{explicit}, where users intentionally provide gaze and speech, and \emph{implicit}, where systems leverage users' natural behaviours to support interaction. Across both, we identified recurring ways for combining gaze and speech to resolve ambiguity, ground references, and support adaptivity. We contribute a synthesis of research on their combined use while highlighting challenges of temporal alignment, fusion and privacy, offering guidance for future research toward richer multimodal human-computer interaction.2026AKAnam Ahmad Khan et al.KAISTEye Tracking & Gaze InteractionVoice User Interface (VUI) DesignAffective Human-Computer DialogueCHI
When EmotionTech Causes Harm: The Case of Therapeutic XREmotional harm and discomfort in therapeutic extended realities (XR) remains underexamined, even as immersive tools are increasingly deployed in healthcare contexts. We frame therapeutic XR as EmotionTech and reflect on 12 cases from 9 researchers and designers through interviews and workshops. We locate four concerns for emotional harm and identify ways to address them: how to talk about emotion, when to talk about emotion, whose emotions are centred, and which emotions are valued. Building on these themes and therapeutic XR as one form of EmotionTech, we propose strategies to legitimise concerns for emotional safety in design and research practice, legitimise knowers by recognising diverse perspectives and situated experiences, and leveraging ambiguity in design and training tools that foster reflexivity rather than closure. These strategies together reposition design responsibility in EmotionTech innovation and make visible its potential to cause emotional discomforts and harms.2026TSThida Sachathep et al.The University of SydneyVR Medical Training & RehabilitationEmpathy & Emotional DesignAffective Human-Computer DialogueCHI
SRL Proxemics: Spatial Guidelines for Supernumerary Robotic Limbs in Near-Body InteractionsWearable supernumerary robotic limbs (SRLs) sit at the intersection of human augmentation and embodied AI, promising to function as extensions of the human body. However, their movements within the intimate near-body space raise unresolved challenges for perceived safety, user control, and trust. In this paper, we present results from a Wizard-of-Oz study (n=18), where participants completed near-body collaboration tasks with SRLs to explore these challenges. We collected qualitative data through think-aloud protocols and semi-structured interviews, complemented by physiological signals and post-task ratings. Findings indicate that greater autonomy did not inherently enhance perceived safety or trust. Instead, participants identified near-body zones and paired them with clear coordination rules. They also expressed expectations for how different arm components should behave, shaping preferences around autonomy, perceived safety, and trust. Building on these insights, we introduce SRL Proxemics, a zone- and segment-level design framework showing that autonomy is not monolithic: perceived safety hinges on spatially calibrated, legible behaviors, not on autonomy level alone.2026HZHongyu Zhou et al.The University of SydneyHaptic WearablesHuman-Robot Collaboration (HRC)Teleoperation & TelepresenceCHI
Restoration, Exploration and Transformation: How Youth Engage Character.AI for Fun, Feels and Finding themselvesYoung people are among the fastest adopters of generative AI, yet research emphasises adult-designed tools and experiments rather than playful, self-directed youth use. We analysed discourse from 4,172 users in Character.AI’s official Discord, finding that the most engaged users were predominantly adolescents (50% aged 13–17), female or non-binary (61.9%), with most (59%) creating their own characters. We contribute (1) a descriptive account of how highly-engaged youth on Character.AI's Discord use AI for playful, emotional, and creative practices that push the platform limits; (2) a framework of three engagement intents — Restoration (emotional regulation), Exploration (creative experimentation), and Transformation (identity development); and (3) a taxonomy of seven youth-created character archetypes. Together, these findings reveal how youth invent novel roles for AI, expose critical misalignments between youth use and current AI experiences, and provide frameworks for researchers and practitioners to design youth-centred AI futures.2026ABAnnabel Blake et al.The University of SydneyGenerative AI (Text, Image, Music, Video)Human-LLM CollaborationAI Ethics, Fairness & AccountabilityCHI
FAIR: Framing AI’s Role in Programming Competitions — Understanding How LLMs Are Changing the Game in Competitive ProgrammingThis paper investigates how large language models (LLMs) are reshaping competitive programming. The field functions as an intellectual contest within computer science education and is marked by rapid iteration, real-time feedback, transparent solutions, and strict integrity norms. Prior work has evaluated LLMs performance on contest problems, but little is known about how human stakeholders—contestants, problem setters, coaches, and platform stewards—are adapting their workflows and contest norms under LLMs-induced shifts. At the same time, rising AI-assisted misuse and inconsistent governance expose urgent gaps in sustaining fairness and credibility. Drawing on 37 interviews spanning all four roles and a global survey of 207 contestants, as well as an API-based crawl of Codeforces contest logs (2022–2025) for quantitative analysis, we contribute: (i) an empirical account of evolving workflows, (ii) an analysis of contested fairness norms, and (iii) a chess-inspired governance approach with actionable measures—real-time LLMs checks in online contests, peer co-monitoring and reporting, and cross-validation against offline performance—to curb LLMs-assisted misuse while preserving fairness, transparency, and credibility.2026DPDongyijie Primo PAN et al.Hong Kong University of Science and Technology (Guangzhou)Human-LLM CollaborationAI-Assisted Decision-Making & AutomationAI Ethics, Fairness & AccountabilityCHI
Sensemaking in Multi-Agent LLM Interfaces: How Users Interpret Transparency and Trustworthiness CuesAs multi-agent Large Language Models (LLMs) gain traction, designers must consider how to surface their internal reasoning in ways that foster appropriate trust. We present a design-led, qualitative, comparative structured observation study, exploring how users interpret and evaluate transparency in multi-agent LLMs. Participants interacted with five interface variants, each instantiating different combinations of transparency-related design dimensions, across two task types: information-seeking and logical reasoning. We surface participants’ mental models, the cues they interpret as signals of transparency and trustworthiness, and how they weigh the costs and benefits of increasing process visibility. Transparency needs were dynamic and context-sensitive, with the ideal "Goldilocks" (i.e., "just right" transparency) level shaped jointly by task demands, interface affordances, and user characteristics such as task expertise and dispositional AI trust. We highlight tensions between process visibility, information sufficiency, and cognitive effort, and synthesise these insights into design considerations for aligning transparency with user needs in future multi-agent LLM interfaces.2026SPSaumya Pareek et al.University of MelbourneHuman-LLM CollaborationExplainable AI (XAI)Privacy by Design & User ControlCHI
PerEye: Co-Designing Extended Reality Rendering Attributes for Vision Health Diagnosis and EducationVision health is a critical domain of clinical practice, yet global access to diagnosis, rehabilitation, and education remains uneven due to economic and geographic disparities. Extended reality (XR) offers opportunities to extend clinical services through portable assessments and interactive simulations, but its design for vision health has been constrained by technical and translational challenges. This paper presents three studies within a sustained co-design process examining how immersive rendering tools can support vision care across clinical and educational contexts. First, we worked with clinicians to map rendering attributes to clinically meaningful functions, identifying opportunities for diagnostic and training use. Second, we evaluated a prototype visual field assessment, demonstrating feasibility in a diagnostic setting. Third, we applied vision simulations in orthoptic training, enhancing empathy and understanding in an educational setting. Together, these studies show how engaging domain experts advances XR tools for vision health, informing diagnosis, patient–clinician communication, and professional education.2026HZHowe Yuan Zhu et al.University of SydneyVR Medical Training & RehabilitationImmersion & Presence ResearchMental Health Apps & Online Support CommunitiesCHI
Toward Pluralizing Reflection in HCI through DaoismReflection is fundamental to how people make sense of everyday life, helping them navigate moments of growth, uncertainty, and change. Yet in HCI, existing frameworks of designing technologies to support reflection remain narrow, emphasizing cognitive, rational problem-solving, and individual self-improvement. We introduce Daoist philosophy as a non-Western lens to broaden this scope and reimagine reflective practices in interactive systems. Combining insights from Daoist literature with semi-structured interviews with 18 Daoist priests, scholars, and practitioners, we identified three key dimensions of everyday reflection: \emph{Stillness}, \emph{Resonance}, and \emph{Emergence}. These dimensions reveal emergent, embodied, relational, and ethically driven qualities often overlooked in HCI research. We articulate their potential to inform alternative frameworks for interactive systems for reflection, advocating a shift from reflection toward \emph{reflecting-with}, and highlight the potential of Daoism as an epistemological resource for the HCI community.2026PZPengyu Zhu et al.National University of SingaporeTechnology Ethics & Critical HCIParticipatory DesignUser Research Methods (Interviews, Surveys, Observation)CHI