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arXiv:2604.15339v1 Announce Type: new Abstract: Uncertainty, vagueness, and ambiguity are closely related and often confused concepts in human-robot interaction (HRI). In earlier studies, these concepts have been defined in contradictory ways and described using inconsistent terminology. This conceptual confusion and lack of terminological consistency undermine empirical comparability, thereby slowing the accumulation of theory. Consequently, consistent concepts that clarify these challenges, including their definitions, distinctions, and interrelationships, are needed in HRI. To address this lack of clarity, this paper […]

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arXiv:2604.15338v1 Announce Type: new Abstract: Deceptive patterns, dark patterns, and manipulative user interfaces (UI) are a widely used design strategy that manipulates users to act against their own interests in pursuit of shareholder aims. These patterns may particularly affect people with less education, visual impairments, and older adults. Yet, access is a critical feature of the user experience (UX), development standards, and law. We considered whether and how the Web Content Accessibility Guidelines (WCAG) and related legislation, like […]

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arXiv:2604.15337v1 Announce Type: new Abstract: Agender euphoria is a new term representing the powerful feelings of happiness, joy, and contentment derived from experiences in gender-free embodiments, spaces, and activities. People with and without agender and adjacent identities (e.g., genderless, gender-free, non-binary, gender-apathetic) may have such experiences under the right circumstances. Video games can offer gender minorities a safe haven for gender euphoric experiences. However, the possibility of agender euphoric experiences was unexplored. We considered this overlooked frame of […]

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arXiv:2604.15336v1 Announce Type: new Abstract: Large language models (LLMs) enable increasingly capable tutoring-style conversational agents, yet effective tutoring requires sensitivity to learners’ affective and cognitive states beyond text alone. Facial expressions provide immediate and practical cues of confusion, frustration, or engagement, but remain underexplored in LLM-driven tutoring. We investigate whether facial-expression-aware signals can improve empathetic tutoring responses through prompt-level integration, without end-to-end retraining. We build a scalable simulated tutoring environment where a student agent exhibits diverse facial behaviors […]

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arXiv:2604.15335v1 Announce Type: new Abstract: The growing adoption of interactive learning tools in higher education offers new opportunities to enhance student performance and well-being. This study compares the effects of traditional and interactive learning methods on academic performance, engagement, motivation, and emotional well-being among 100 university students enrolled in a computer intrusion detection course. Participants were randomly assigned to either a traditional learning group (lectures and notes) or an interactive learning group utilising tools such as Kahoot, Panopto, […]

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arXiv:2604.15334v1 Announce Type: new Abstract: The exponential growth of AI education has brought millions of learners to online platforms, yet this massive scale has simultaneously exposed critical pedagogical shortcomings. Traditional video-based instruction, while cost-effective and scalable, demonstrates systematic failures in both sustaining learner engagement and facilitating the deep conceptual mastery essential for AI literacy. We present a pilot study evaluating a novel hybrid learning platform that integrates real-time conversational AI tutors with traditional video lectures. Our controlled experiment […]

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arXiv:2604.15333v1 Announce Type: new Abstract: Human-AI romantic relationships are increasingly common, yet little is understood about how public discourse around them emerges and shifts over time. Prior research has examined user experiences and ethical concerns, but lacks longitudinal analyses of user-initiated public discussions. We address this gap by analyzing a high-precision dataset of 3,383 self-disclosed romantic companion AI posts from Reddit (2017-2025), using topic modeling and temporal statistical analysis to identify dominant themes and their evolution over time. […]

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arXiv:2604.15332v1 Announce Type: new Abstract: Crash diagrams are essential tools in transportation safety analysis, yet their manual preparation remains time-consuming and prone to human variability. This study investigates the use of Vision-Language Models (VLMs) to automate crash diagram generation from police crash reports, focusing on multilane roundabouts as a challenging test case. A three-part structured prompt framework was developed to guide model reasoning through interpretation, extraction, and visual synthesis, while a 10-metric evaluation system was designed to assess […]

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arXiv:2604.15331v1 Announce Type: new Abstract: We analyze over 500,000 de-identified health-related conversations with Microsoft Copilot from January 2026 to characterize what people ask conversational AI about health. We develop a hierarchical intent taxonomy of 12 primary categories using privacy-preserving LLM-based classification validated against expert human annotation, and apply LLM-driven topic-clustering for prevalent themes within each intent. Using this taxonomy, we characterize the intents and topics behind health queries, identify who these queries are about, and analyze how usage […]

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arXiv:2604.15330v1 Announce Type: new Abstract: Many HCIxfabrication systems are compelling as prototypes but remain difficult to reuse, extend, or transfer beyond their original publication. A common explanation is that adoption simply takes time. We argue that the issue is more fundamental. The knowledge needed to make fabrication systems transferable, namely how they behave across different materials, machines, and users, usually does not exist at the time of publication because the work required to generate this knowledge is rarely […]

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