250 papers
This study reveals that users are highly satisfied with LLM-generated romantic relationship advice, finding it reliable and helpful, which significantly improves their overall trust and positive attitudes toward AI systems.
Through trauma-informed interviews with 18 Western European cybercrime victims, this study identifies four recovery stages and proposes that individual cyber resilience is fostered by a combination of internal factors, social support, and context-sensitive, collaborative strategies.
This paper introduces a simulation-based clinical red teaming framework that pairs AI psychotherapists with dynamic patient agents to evaluate mental health support systems, revealing critical safety gaps such as the validation of delusions and failure to de-escalate suicide risk in AI agents tested against Alcohol Use Disorder scenarios.
This paper introduces the HUMAINE framework, which leverages a large-scale, demographically stratified dataset of 23,404 participants to reveal that human preferences for large language models vary significantly across age groups and evaluation dimensions, challenging the validity of current unrepresentative benchmarks.
This paper argues that traditional user experience frameworks are insufficient for AI-enabled Human-in-the-Loop systems and proposes a new sociotechnical evaluative framework that integrates backend performance, organizational workflows, and governance metrics to redefine UX for complex, decision-critical environments.
This paper proposes a theoretical framework of interface metaphors ranging from "anti-anthropomorphism" to "hyper-anthropomorphism" to reposition anthropomorphism as a design variable that exposes the sociotechnical nature of Large Language Models and encourages critical user engagement over literal delusion.
This paper presents a gamified decision-support framework that integrates game engines with real-time multi-criteria feedback to enable non-expert designers to effectively explore and optimize complex performance-driven design spaces, as demonstrated through a case study on exoskeleton facade retrofitting.
The paper introduces LEGS-POMDP, a modular framework that integrates language, gesture, and visual observations within a Partially Observable Markov Decision Process to effectively handle uncertainty in object identity and location for robust open-world robot search.
This paper argues that the rise of agentic AI necessitates a reconceptualization of Team Situation Awareness to address the structural uncertainty of open-ended agency, distinguishing between continuous alignment mechanisms and emerging tensions to guide future human-AI teaming research.
This paper introduces VizCrit, a visual design tool that generates computational feedback with varying levels of actionability, and presents a study showing that solution-centered feedback helps novices reduce design issues and boost self-perceived creativity compared to textbook-based approaches.
This paper presents a human-centric body-scale NFC networking system for ultra-low-power wearables that utilizes Meander NFC to create stable, surface-confined communication on clothing and picoRing NFC to bridge distance gaps between distributed nodes, thereby enabling robust surface-to-multipoint interactions.
This paper introduces Redo.io, an open-source platform that leverages LLMs to synthesize court-ready statistical evidence of racial sentencing bias from California prison records, demonstrating that AI can effectively assist in generating narratives for Racial Justice Act claims when ethically integrated with traditional statistical methods.
This paper presents SparkTales, an intelligent system designed to alleviate coordinators' workload and enhance children's engagement in cross-language collaborative storytelling by leveraging AI to provide tailored story frameworks, questions, and materials based on a formative study of coordinator needs.
Roomify is a spatially-grounded transformation system that generates themed virtual environments anchored to users' physical rooms by preserving key functional and geometric properties, thereby overcoming the trade-off between full immersion and spatial awareness while enabling personalized design through an interactive authoring tool validated by improved presence and professional workflow value.
Through a multi-stakeholder evaluation in China, this paper identifies significant expectation-willingness gaps and fundamental trade-offs in camera glass privacy mechanisms, proposing a context-adaptive design framework that dynamically adjusts protection strategies based on environmental sensitivity to resolve tensions between wearers and bystanders.
This paper introduces a multi-dimensional design space framework that treats replication experimental design as a pairwise comparison problem, enabling researchers to systematically identify, categorize, and analyze decisions regarding which aspects of a study to preserve or alter for both retrospective characterization and prospective planning.
This randomized study of 164 law students demonstrates that targeted training significantly boosts both the adoption and productive performance of generative AI in legal analysis, whereas untrained access fails to improve outcomes and may even reduce answer quality.
This study presents an auto-generated persona system derived from VR app store reviews that effectively facilitates accessibility requirements elicitation and enhances student empathy in VR design courses.
This exploratory pilot study suggests that while increased kinaesthetic demands (specifically writing pressure) may slightly impair immediate information retention, tactile sensitivity manipulation (glove use) has no clear effect, and neither mental effort nor perceived workload significantly mediates these outcomes.
Jagarin is a three-layer mobile architecture comprising the DAWN urgency engine, ARIA email proxy, and ACE institutional protocol that enables personal AI agents to hibernate until contextually necessary, thereby resolving the conflict between battery efficiency and timely duty fulfillment without compromising privacy or requiring persistent background execution.