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cs.HC updates on arXiv.org

Quantitative Movement Testing: Measuring Patient Movements from a Single Smartphone Video Vision-Language Models Suppress Female Representations Under Ambiguous Input The New Social Image: How AI Competency and AI Proactivity Influence Self- and Peer-Perceptions in the Workplace TUX: Measuring Human--AI Tacit Understanding LLUMI: Improving LLM Writing Assistance for Mental Health Support with Online Community Feedback VideoFDB: Evaluating Full-Duplex Vision-Speech Capabilities in Conversational Agents Label Over Logic? How Source Cues Bias Human Fallacy Judgments More Than LLMs Inform, Coach, Relate, Listen: Auditing LLM Caregiving Support Roles How Coding Agents Fail Their Users: A Large-Scale Analysis of Developer-Agent Misalignment in 20,574 Real-World Sessions MetaRanker: Human-in-the-loop Active Ranking for Metalens Image Quality Analyzing Persona Effects in Generated Explanations from Multimodal LLM Agents in Urban Perception First head-to-head comparison of agentic AI applied to the analysis of simulated data of the Einstein Telescope Granuscore: A Reference-Free Measure of Granularity for Text Analysis and Question Answering The Timing Dependencies of Trust: Speed, Accuracy, and cBCI Neuro-Decoupling in Human-AI Teams Bayesian Distributional Models of Executive Functioning Visual Matters: Connecting Aesthetic Appeal and Production Quality of Photos, Infographics and Data Visualizations to Credibility of Social Media Posts Data-driven Head Motion Generation through Natural Gaze-Head Coordination Agreement Metrics for LLM-as-Judge Evaluation: What to Report and Why Perceptually Lossless Tactile Texture Synthesis with Compact Spectral Envelope Models MambaGaze: Bidirectional Mamba with Explicit Missing Data Modeling for Cognitive Load Assessment from Eye-Gaze Tracking Data CogAdapt: Transferring Clinical ECG Foundation Models to Wearable Cognitive Load Assessment via Lead Adaptation Augmented Analytics and Decision Quality: The Role of Trust among Non-Technical BI Users Faster Completion, Less Learning: Generative AI Reduced Study Time on Math Problems and the Knowledge They Build PaintCopilot: Modeling Painting as Autonomous Artistic Continuation Personality Engineering with AI Agents: A New Methodology for Negotiation Research PULSE: Agentic Investigation with Passive Sensing for Proactive Intervention in Cancer Survivorship Access Timing as Scaffolding: A Reinforcement Learning Approach to GenAI in Education Conversations in Space: Structuring Non-Linear LLM Interactions on a Canvas MAPLE: Self-Supervised Learning-Enhanced Nonlinear Dimensionality Reduction for Visual Analysis nASR: An End-to-End Trainable Neural Layer for Channel-Level EEG Artifact Subspace Reconstruction in Real-Time BCI
Design Frameworks for Hyper-Connected Social XRI Immersiv...
Jie Guan, Alexis Morris · 2023-06-10 · via cs.HC updates on arXiv.org

The metaverse refers to the merger of technologies for providing a digital twin of the real world and the underlying connectivity and interactions for the many kinds of agents within. As this set of technology paradigms - involving artificial intelligence, mixed reality, the internet-of-things and others - gains in scale, maturity, and utility there are rapidly emerging design challenges and new research opportunities. In particular is the metaverse disconnect problem, the gap in task switching that inevitably occurs when a user engages with multiple virtual and physical environments simultaneously. Addressing this gap remains an open issue that affects the user experience and must be overcome to increase overall utility of the metaverse. This article presents design frameworks that consider how to address the metaverse as a hyper-connected meta-environment that connects and expands multiple user environments, modalities, contexts, and the many objects and relationships within them. This article contributes to i) a framing of the metaverse as a social XR-IoT (XRI) concept, ii) design Considerations for XRI metaverse experiences, iii) a design architecture for social multi-user XRI metaverse environments, and iv) descriptive exploration of social interaction scenarios within XRI multi-user metaverses. These contribute a new design framework for metaverse researchers and creators to consider the coming wave of interconnected and immersive smart environments.