Purpose This study aims to examines whether generative artificial intelligence (AI) and virtual reality (VR) function as equalizers or reproduce existing interpretive asymmetries in digital heritage interpretation among visitors with varying levels of cultural proximity. Design/methodology/approach A quasi-experimental...
Y. Xiong, Aoran Zheng· Journal of Hospitality and T...· 0 citations
The article proposes the Human-Supervised Generative AI Framework for Physical Education and Sport, which classifies tasks by consequence and requires source grounding, data minimization, professional review, disclosure, and outcome monitoring.
Original version 1.1 description (planned methods): Prespecified protocol for a systematic review and meta-analysis of child-facing technology-mediated interventions for gross motor skill learning in typically developing children aged 3–12 years. The review distinguishes immediate acquisition from delayed retention and...
Hiroo Shimizu· Zenodo (CERN European Organi...· 0 citations
OMANISHA (Online Misogynistic Annotated Natural-language Instances for Sentiment and Hate Analysis) is a Bengali dataset developed to support the automatic detection of misogynistic discourse in online spaces. Misogynistic content on online platforms has serious psychological, social, and institutional consequences for...
Fatama Jannat Tisha, Bibhas Roy Chowdhury Piyas, Nurjahan Afrose et al.· Mendeley Data· 0 citations
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A previous case study of the Hugging Face AI collective closed with a prediction: a population of large language models, organised as a multi-agent system, could in principle sustain its own existence (generating and maintaining the conditions of its continued operation) while being nonconscious. This paper asks what t...
Maurice I. Yolles· Zenodo (CERN European Organi...· 0 citations
This chapter introduces the fundamental purpose of scientific research and explains the scientific method as a systematic approach to knowledge generation. The author outlines each step of the scientific method, emphasizing its logical and empirical structure. The chapter also explores the interrelationship between sci...
Humberto Vega-Mercado· Development of Scientific Re...· 0 citations
This chapter focuses on the systematic review of existing scholarly information relevant to a research topic. It discusses strategies for locating, evaluating, and organizing scientific sources, including journals, textbooks, conference proceedings, and theses. The chapter also explains proper bibliographic formatting...
Humberto Vega-Mercado· Development of Scientific Re...· 0 citations
Human oversight of artificial intelligence is often justified by having a person who can reject the system's recommendation. Yet AI may already have shaped what that person sees, notices, and thinks. This article brings together terms from several disciplines to classify these influences and examine their ethical impli...
Stanley Clark Newhall· Zenodo (CERN European Organi...· 0 citations
A popular-science explainer (not a scientific contribution in its own right) on the research programme "Necessary Conditions for Primary Interoceptive Sentience in Continuous Substrates: A Falsifiable Programme" (doi:10.5281/zenodo.22895484). It covers the No-Go Theorem for Consciousness on a Chip as heuristic motivati...
Francesco Iavarone· Zenodo (CERN European Organi...· 2 citations
A scoping review analyzes 53 HCI studies and offers a framework explaining how LLM capabilities become organized through family participation, using activity theory and AODM to relate participants and educational objects to mediation, labour, and rules.
Comparison of SHAP and Grad-CAM attribution maps confirms clinically coherent disease-specific localisation, and reveals monotonic performance degradation, identifying minimal regularisation as optimal for multi-label medical imaging.
S. Arumugam, A. Sindhu, M. N. Saroja et al.· Machine-mediated learning· 0 citations
Exploring how generative AI could make machine vision more accessible to businesses. The post GenEye in a Box: Making Machine Vision Something You Can Just Ask For appeared first on GPT-Lab.
MIT News · Artificial Intelligence· news.mit.eduOct 8, 2026
Training AI agents with reinforcement learning can be challenging because their tools, context, and decision-making are managed by complex frameworks. Agent Lightning connects existing agents to RL training, making it easier to improve them without rebuilding them. The post Agent Lightning v1.0: A 3,500-Line Lightweight Agentic RL Framework for Training Agents with Real Harnesses appeared first on Microsoft Research.
MIT News · Artificial Intelligence· news.mit.eduOct 6, 2026
Jennifer Neville did not want to go into computer science—but that’s exactly where she landed. Neville discusses the starts and stops that led to her professional sweet spot and her work identifying “surprising failures” making it hard for AI to handle complexity. The post What AI gets wrong and what failure teaches us appeared first on Microsoft Research.
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