generative ai

BurnSight: code for a feasibility framework for generative short-term forecasting of burn wound images from sequential clinical photographs

Code accompanying the manuscript "BurnSight, a feasibility framework for generative short-term forecasting of burn wound images from sequential clinical photographs." BurnSight forecasts the next-day appearance of a burn wound from a short sequence of clinical photographs, using a K-conditioned ConvLSTM Creator with re...

Intellectual Property in the Age of Generative Materials Design: Ownership of AI-Discovered Compounds

Research and Practice on Teaching Reform of Software Engineering Directed by AI Empowerment and Industry-Academia Integration

With the rapid evolution of artificial intelligence (AI) and modern software architecture, traditional software engineering education faces severe challenges, including disconnected theory and practice, outdated curriculum design, and insufficient focus on practical AI-assisted development tools. This paper proposes a...

Governança e Aplicação de Inteligência Artificial Generativa no Ensino de Filosofia: Modelo de Inovação Pedagógica e Formação Docente

PERGUNTA DE PESQUISA E TESE CENTRAL Pergunta de Pesquisa: Em que medida um modelo de linguagem de grande escala (LLM de 8B parâmetros) executado localmente em hardware de baixo custo, associado a um protocolo pedagógico de auditoria hermenêutica em três camadas, é capaz de identificar e refutar erros conceituais no ens...

Conservation, symmetry, and nonlinear exchange in a shearing self-gravitating magnetofluid

This deposit presents “Conservation, symmetry, and nonlinear exchange in a shearing self-gravitating magnetofluid,” together with supplementary material and compact supporting evidence.The study connects conservation accounting, symmetry-dependent observability, and controlled nonlinear evolution in an eight-component...

Supplemental Tables for "Evaluating Generative AI in Civil Engineering Mechanics Education: Modeling, Free-Body Diagram Construction, and Spatial Reasoning in Statics and Dynamics"

The supplemental materials consist of Tables S1–S6, which provide summary observations and detailed problem-level evaluation results for 13 undergraduate engineering mechanics problems: eight statics problems, including a custom two-dimensional truss problem, and five dynamics problems. The tables document the performa...

Preregistration: Purposes of Generative AI Use and Computational Problem-Solving Process — A 62-Country Analysis of PISA 2025 Learning-in-a-Digital-World Log Data

Preregistration for a confirmatory analysis of PISA 2025 Learning-in-a-Digital-World (LDW) log data, deposited before the researcher had access to any unmasked estimate for the confirmatory sample. RESEARCH QUESTION. Are the purposes for which 15-year-olds use generative AI for schoolwork (summarising, preliminary rese...

E089 Quantified-Chunk New-Post Cohort: Pre-registration with In-Flight Amendments (v1.2). Primary analysis re-scoped to P3; primary contribution a query-validity and namespace-drift taxonomy.

E089 is a pre-registered field study testing how generative AI search engines cite cold, newly published content. The study used 12 posts arranged as six topic-matched A/B pairs. One page in each pair opened with a quantified-chunk template: a front-loaded definition, named entities and at least one hard number already...

Reimagined worlds: Sociotechnical imaginaries of generative AI within an educational institution

Educational institutions are undergoing transition, as students, and educators increasingly adopt generative AI. Therefore, it is important to examine stakeholders' perspective and their interpretations of safe, ethical, and responsible AI. Undertaking a micro-ethnographic case study, this study contributes to the lite...

Overview of PAN 2026: Voight-Kampff Generative AI Detection, Text Watermarking, Multi-author Writing Style Analysis, Generative Plagiarism Detection, and Reasoning Trajectory Detection

Phase Transition & Acid-Base Equilibrium Model] Dynamic Phase Transition Model of Outcome Creation under Human-AI Co-Creation — Critical Boundary Formalization of Depth of Thought (D_k) via Acid-Base Equilibrium Buffer Curves —

Abstract This paper introduces an acid-base equilibrium (titration curve) model from biochemistry as an analogy and dynamic mathematical framework to explain the non-linear jump phenomenon in outcome creation during interaction with Generative AI. Traditional project management and business performance metrics have rel...

Conceptual Study on the Depth of Thought Model (D = O \times A \times U) and Outcome Creation Capacity in the Generative AI Era

Abstract This paper presents a conceptual approach to capturing the tectonic shift in individual outcome-creation structures driven by the widespread adoption of Generative AI. Human cognition is defined at its core as the "Depth of Thought (D)," modeled as the multiplicative product of three factors: Observation (O),...