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A Framework for Measuring Appropriate Reliance on Set-Valued AI Advice DeliChess: A Multi-party Dialogue Dataset for Deliberation in Chess Puzzle Solving From Explanation to Diagnosis: Next Generation Interactive Video Coach with Misstep Awareness SocialCoach: Personalized Social Skill Learning with RL-based Agentic Tutoring and Practice Formalizing all indexed mathematics as a benchmark for general reasoning, with the example of implementing dilatations of categories Face versus Body Tracking for Human-Robot Interaction: An Egocentric Dataset From Prompt to Service: An SLM-Based Agent Orchestration Gateway for AI-Driven Virtual Worlds What LLMs Must Forget to Teach Effectively: A DIY Approach to Premodern Japanese Language Pedagogy 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 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
CONECT4: Desarrollo de componentes basados en Realidad Mi...
Santiago González, Alvaro García, Ana Núñez · 2021-05-24 · via cs.HC updates on arXiv.org

This work presents the results of project CONECT4, which addresses the research and development of new non-intrusive communication methods for the generation of a human-machine learning ecosystem oriented to predictive maintenance in the automotive industry. Through the use of innovative technologies such as Augmented Reality, Virtual Reality, Digital Twin and expert knowledge, CONECT4 implements methodologies that allow improving the efficiency of training techniques and knowledge management in industrial companies. The research has been supported by the development of content and systems with a low level of technological maturity that address solutions for the industrial sector applied in training and assistance to the operator. The results have been analyzed in companies in the automotive sector, however, they are exportable to any other type of industrial sector. -- -- En esta publicación se presentan los resultados del proyecto CONECT4, que aborda la investigación y desarrollo de nuevos métodos de comunicación no intrusivos para la generación de un ecosistema de aprendizaje hombre-máquina orientado al mantenimiento predictivo en la industria de automoción. A través del uso de tecnologías innovadoras como la Realidad Aumentada, la Realidad Virtual, el Gemelo Digital y conocimiento experto, CONECT4 implementa metodologías que permiten mejorar la eficiencia de las técnicas de formación y gestión de conocimiento en las empresas industriales. La investigación se ha apoyado en el desarrollo de contenidos y sistemas con un nivel de madurez tecnológico bajo que abordan soluciones para el sector industrial aplicadas en la formación y asistencia al operario. Los resultados han sido analizados en empresas del sector de automoción, no obstante, son exportables a cualquier otro tipo de sector industrial.