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  1. Before diffusion models generalize, they grow spurious attractors absent from training data but repeated in samples

    As the training set grows, diffusion models move from memorizing training samples to generalizing, and between these phases an intermediate kind of attractor appears that matches no training image yet recurs in generated samples. Reading generation as retrieval in a dense associative memory predicts such spurious states once storage capacity is exceeded; on MNIST, FASHION-MNIST, CIFAR-10 and LSUN-CHURCH the spurious fraction rises and then falls at the memorization-to-generalization boundary, with basin volumes between those of memorized and generalized samples.

  2. A TAM-based survey and structural equation model show that AI application significantly and positively affects leather product designers' curiosity, imagination, risk-taking, and challenge, while perceived usefulness does not significantly mediate the risk-taking dimension.

    Framed by the Technology Acceptance Model (TAM), this study treats perceived ease of use and perceived usefulness as mediators and, following Williams' creativity theory, divides professional creativity into curiosity, imagination, risk-taking, and challenge; using a structured questionnaire with leather product designers and testing via confirmatory factor analysis and structural equation modeling, it finds that AI application has a significant positive influence on all four creativity dimensions, that both perceived ease of use and perceived usefulness significantly mediate the curiosity, imagination, and challenge dimensions, and that for risk-taking only perceived ease of use is a significant mediator while the effect of perceived usefulness is not statistically significant.

  3. Neroni reframes creativity's unit of explanation from isolated factors to cross-level dynamic configurations, offering four mechanisms—constraint, affordance, regulation, feedback/selection—and testable propositions

    In this Perspective in Frontiers in Cognition, Neroni integrates biopsychosocial, systemic, sociocultural, and interactionist approaches to reconceptualize creativity as a multilevel, developmentally situated, sociotechnically mediated phenomenon emerging from interactions among biological, psychological, developmental, sociocultural, and technological processes, arguing that no single factor is inherently creative and that its contribution depends on how it combines with other factors under particular conditions, and proposing four cross-level mechanisms—constraint, affordance, regulation, and feedback/selection—along with four testable propositions: configurational dependence, temporal specificity, cross-level divergence, and developmental reconfiguration.

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