arXiv AI
Jun 11
Designing AI-Supported Focus Groups: A Role x Modality Playbook
arXiv:2606. 11835v1 Announce Type: cross Abstract: Collecting participants' lived experiences is central to design research.
Generative Experiences for Digital Mental Health Interventions: Evidence from a Randomized Study
arXiv:2604. 07558v3 Announce Type: replace-cross Abstract: Digital mental health (DMH) tools have extensively explored personalization of interventions to users' needs and contexts.
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arXiv AI
Jun 17
Talking to Your Data: Exploring Embodied Conversation as an Interface for Personal Health Reflection
arXiv:2606. 17767v1 Announce Type: cross Abstract: Personal health data from wearables are typically presented through dashboards of charts and summary statistics, requiring users to actively interpret patterns and implications.
arXiv AI
Jun 15
Thinking Outside the [Chat]Box: Bridging Computer Science and Industrial Design for Cognitive-Inclusive Generative AI
arXiv:2606. 14306v1 Announce Type: cross Abstract: Current Generative AI (GenAI) interfaces remain largely constrained to chatbox interaction, which can impose high cognitive demands on users and create substantial barriers for people with intellectual disabilities (ID), including prompt formulation difficulties, response overload, and limited mechanisms to assess information reliability.
Hugging Face Trending Papers
Jul 28
From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation
Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfaces for rehabilitation. How can patients and caregivers articulate preferences about algorithmic transparency when they lack conceptual frameworks for explainability, and when standard elicitation approaches are structurally inadequate for users with acquired communication disorders?
arXiv AI
Jul 29
From Dyad to Triad: Eliciting XAI Requirements in Stroke Rehabilitation
arXiv:2607. 25423v1 Announce Type: cross Abstract: Eliciting explainable AI (XAI) requirements from stroke survivors presents a methodological challenge with direct implications for the design of trustworthy brain-computer interfaces for rehabilitation.
arXiv AI
Jul 17
From Stateless to Situated: Building a Psychological World for LLM-Based Agents
arXiv:2603. 25031v2 Announce Type: replace Abstract: In psychological support and emotional companionship scenarios, the core limitation of large language models (LLMs) lies not merely in response quality, but in their reliance on local next-token prediction, which prevents them from maintaining the temporal continuity, stage awareness, and user consent boundaries required for multi-turn intervention.
arXiv AI
1d ago
Large Language Models in Mental Health: A Systematic Review of Applications, Innovations, and Ethical Challenges
arXiv:2608. 18080v1 Announce Type: new Abstract: We present a review on the applications of large language models (LLMs) in health, e.
arXiv AI
Jun 3
From 'What' to 'How' and 'Why': Sharing LLM-Generated Retrospective Summaries of Older Adults' Passive Tracking Data with Remote Family Members
arXiv:2606. 03876v1 Announce Type: cross Abstract: With the growing prevalence of modern ubiquitous computing technologies, multi-modal tracking systems hold promise for providing timely awareness and reassurance to stakeholders such as remote family members (RFMs) of older adults, who play a central role in care coordination.
arXiv AI
Jul 28
Design Theater: A Benchmark for Generative UI
arXiv:2607. 22928v1 Announce Type: new Abstract: Generative UI tools promise to democratize UI design by turning natural language descriptions into complete interfaces.
arXiv AI
Jun 24
Navigating User Behavior toward Personalized Multimodal Generation
arXiv:2606. 24196v1 Announce Type: new Abstract: Modern AIGC pipelines deliver high-fidelity images and videos but presuppose a well-formed creation instruction, while end users rarely articulate visual details, leaving generators misaligned with user demand.
arXiv AI
Aug 14
PatientAct: Theory-Grounded Mental Health Client Simulation
arXiv:2608. 12750v1 Announce Type: cross Abstract: LLM-based simulated clients are increasingly used to train novice counselors, evaluate LLM therapists, and generate synthetic data.
arXiv AI
Aug 5
From Wearable Data to Personalized and Actionable Health Insights
arXiv:2608. 03251v1 Announce Type: cross Abstract: Commercial wearable devices continuously capture rich physiological data (e.