Humanities & Social Sciences

89 items

arXiv Sep 29, 2026
The study introduces NameTrace, measures direct lexical support for names across nearly half a million first names and 12 LLM-associated tokenizers, and, on atomic versus short-fragmented names matched within the same race/ethnicity–gender strata, finds systematically higher task-aligned concept accessibility for atomic names across fellowship, hiring, clinical assessment, and lending; the differences persist in all eight strata, transfer to unseen names, and hidden-state interventions along the measured task directions shift later constrained choices.
The study introduces NameTrace, measures direct lexical support for names across nearly half a million first names and 12 LLM-associated tokenizers, and, on atomic versus short-fragmented names matched within the same race/ethnicity–gender strata, finds systematically higher task-aligned concept accessibility for atomic names across fellowship, hiring, clinical assessment, and lending; the differences persist in all eight strata, transfer to unseen names, and hidden-state interventions along the measured task directions shift later constrained choices.
Across nearly half a million names and 12 tokenizers, whether a name becomes a single token shifts concept accessibility in fellowship, hiring, clinical, and lending judgments
The study introduces NameTrace, measures direct lexical support for names across nearly half a million first names and 12 LLM-associated tokenizers, and, on atomic versus short-fragmented names matched within the same race/ethnicity–gender strata, finds systematically higher task-aligned concept accessibility for atomic names across fellowship, hiring, clinical assessment, and lending; the differences persist in all eight strata, transfer to unseen names, and hidden-state interventions along the measured task directions shift later constrained choices.
The study introduces NameTrace, measures direct lexical support for names across nearly half a million first names and 12 LLM-associated tokenizers, and, on atomic versus short-fragmented names matched within the same race/ethnicity–gender strata, finds systematically higher task-aligned concept accessibility for atomic names across fellowship, hiring, clinical assessment, and lending; the differences persist in all eight strata, transfer to unseen names, and hidden-state interventions along the measured task directions shift later constrained choices.
arXiv Sep 29, 2026
The study builds a curated resource of 1,813 matched American English–British English variant pairs and introduces DiAlign, a training-free method for estimating regional alignment, then uses them to audit six pretraining corpora, 21 post-training datasets, nine tokenizers, ten model checkpoints and generations under two prompting conditions, finding that American English is systematically favored across data exposure, representation and generation, and that British-English prompting only partially shifts this default.
The study builds a curated resource of 1,813 matched American English–British English variant pairs and introduces DiAlign, a training-free method for estimating regional alignment, then uses them to audit six pretraining corpora, 21 post-training datasets, nine tokenizers, ten model checkpoints and generations under two prompting conditions, finding that American English is systematically favored across data exposure, representation and generation, and that British-English prompting only partially shifts this default.
Auditing 1,813 AmE–BrE variant pairs across the pipeline: six pretraining corpora, 21 post-training datasets and ten checkpoints all lean American English
The study builds a curated resource of 1,813 matched American English–British English variant pairs and introduces DiAlign, a training-free method for estimating regional alignment, then uses them to audit six pretraining corpora, 21 post-training datasets, nine tokenizers, ten model checkpoints and generations under two prompting conditions, finding that American English is systematically favored across data exposure, representation and generation, and that British-English prompting only partially shifts this default.
The study builds a curated resource of 1,813 matched American English–British English variant pairs and introduces DiAlign, a training-free method for estimating regional alignment, then uses them to audit six pretraining corpora, 21 post-training datasets, nine tokenizers, ten model checkpoints and generations under two prompting conditions, finding that American English is systematically favored across data exposure, representation and generation, and that British-English prompting only partially shifts this default.
arXiv Sep 29, 2026
In an auction-logic-faithful on-device simulation with 36 campaigns, 50 devices, and 30 paired demand paths, the study examines two economic misalignments created when privacy-preserving ML decisions move onto clients, finding that proportional Even pacing overspends 17.77% after one tick of staleness and 1,669.31% after 50 ticks, that 50-tick overspend remains 106.95% at two-times budget pressure, that a visible-budget no-sale guard makes zero-lag compliance exact yet leaves 11.88% overspend at one tick, and that 98.23% of rival auctions at one tick admit a profitable deviation once the ML/pacing score transformation is allowed to change payment units.
In an auction-logic-faithful on-device simulation with 36 campaigns, 50 devices, and 30 paired demand paths, the study examines two economic misalignments created when privacy-preserving ML decisions move onto clients, finding that proportional Even pacing overspends 17.77% after one tick of staleness and 1,669.31% after 50 ticks, that 50-tick overspend remains 106.95% at two-times budget pressure, that a visible-budget no-sale guard makes zero-lag compliance exact yet leaves 11.88% overspend at one tick, and that 98.23% of rival auctions at one tick admit a profitable deviation once the ML/pacing score transformation is allowed to change payment units.
Moving bidding on device: one tick of sync staleness overspends budgets by 17.77%, and 50 ticks by 1,669.31%
In an auction-logic-faithful on-device simulation with 36 campaigns, 50 devices, and 30 paired demand paths, the study examines two economic misalignments created when privacy-preserving ML decisions move onto clients, finding that proportional Even pacing overspends 17.77% after one tick of staleness and 1,669.31% after 50 ticks, that 50-tick overspend remains 106.95% at two-times budget pressure, that a visible-budget no-sale guard makes zero-lag compliance exact yet leaves 11.88% overspend at one tick, and that 98.23% of rival auctions at one tick admit a profitable deviation once the ML/pacing score transformation is allowed to change payment units.
In an auction-logic-faithful on-device simulation with 36 campaigns, 50 devices, and 30 paired demand paths, the study examines two economic misalignments created when privacy-preserving ML decisions move onto clients, finding that proportional Even pacing overspends 17.77% after one tick of staleness and 1,669.31% after 50 ticks, that 50-tick overspend remains 106.95% at two-times budget pressure, that a visible-budget no-sale guard makes zero-lag compliance exact yet leaves 11.88% overspend at one tick, and that 98.23% of rival auctions at one tick admit a profitable deviation once the ML/pacing score transformation is allowed to change payment units.
Frontiers in Physics Sep 28, 2026
This paper develops a co-evolutionary multilayer potential game in which boundedly rational agents update mixed strategies while market, information, and institutional links adapt to observed compatibility and diffusion signals, and proposes a stability-guarded mirror-replicator (SGMR) dynamic combining entropy-regularized strategy revision, projected link rewiring, and a spectral safeguard; the authors prove that the mirror step recovers replicator dynamics in the small-step limit and establish the exact-potential property, monotone potential improvement, sublinear stationarity, and local input-to-state stability under observation disturbances, with computational experiments on synthetic economic networks showing faster convergence, higher collective welfare, stronger noise resilience, an
This paper develops a co-evolutionary multilayer potential game in which boundedly rational agents update mixed strategies while market, information, and institutional links adapt to observed compatibility and diffusion signals, and proposes a stability-guarded mirror-replicator (SGMR) dynamic combining entropy-regularized strategy revision, projected link rewiring, and a spectral safeguard; the authors prove that the mirror step recovers replicator dynamics in the small-step limit and establish the exact-potential property, monotone potential improvement, sublinear stationarity, and local input-to-state stability under observation disturbances, with computational experiments on synthetic economic networks showing faster convergence, higher collective welfare, stronger noise resilience, an
SGMR co-evolves strategies and multilayer economic links under one dynamic potential, converging faster with higher welfare and stronger noise resilience on synthetic networks
This paper develops a co-evolutionary multilayer potential game in which boundedly rational agents update mixed strategies while market, information, and institutional links adapt to observed compatibility and diffusion signals, and proposes a stability-guarded mirror-replicator (SGMR) dynamic combining entropy-regularized strategy revision, projected link rewiring, and a spectral safeguard; the authors prove that the mirror step recovers replicator dynamics in the small-step limit and establish the exact-potential property, monotone potential improvement, sublinear stationarity, and local input-to-state stability under observation disturbances, with computational experiments on synthetic economic networks showing faster convergence, higher collective welfare, stronger noise resilience, an
This paper develops a co-evolutionary multilayer potential game in which boundedly rational agents update mixed strategies while market, information, and institutional links adapt to observed compatibility and diffusion signals, and proposes a stability-guarded mirror-replicator (SGMR) dynamic combining entropy-regularized strategy revision, projected link rewiring, and a spectral safeguard; the authors prove that the mirror step recovers replicator dynamics in the small-step limit and establish the exact-potential property, monotone potential improvement, sublinear stationarity, and local input-to-state stability under observation disturbances, with computational experiments on synthetic economic networks showing faster convergence, higher collective welfare, stronger noise resilience, an
发表出处待核验 Sep 28, 2026
This conference paper abstract examines the development of reflective competence among economics students in AI-mediated English for Specific Purposes (ESP) learning, but the provided text contains only the title, author information, and the beginning of the abstract, lacking specific research methods, data, or conclusions.
This conference paper abstract examines the development of reflective competence among economics students in AI-mediated English for Specific Purposes (ESP) learning, but the provided text contains only the title, author information, and the beginning of the abstract, lacking specific research methods, data, or conclusions.
How Economics Students Develop Reflective Competence in AI-Mediated ESP Learning: A Conference Paper Abstract
This conference paper abstract examines the development of reflective competence among economics students in AI-mediated English for Specific Purposes (ESP) learning, but the provided text contains only the title, author information, and the beginning of the abstract, lacking specific research methods, data, or conclusions.
This conference paper abstract examines the development of reflective competence among economics students in AI-mediated English for Specific Purposes (ESP) learning, but the provided text contains only the title, author information, and the beginning of the abstract, lacking specific research methods, data, or conclusions.
Studies in Self-Access Learning Journal Sep 28, 2026
In a six-week flipped EFL writing course, 58 second-year student teachers at a Thai university independently selected resources such as textbooks, websites, educational videos, and GenAI tools and synthesized their learning through handwritten notebook summaries; questionnaire responses showed generally positive perceptions of learning preparation, information management, learning responsibility, and writing readiness, while focus group discussions with 30 students revealed four interconnected constraints—limited linguistic and background knowledge, uncertainty without immediate teacher guidance, difficulty evaluating and synthesizing multiple resources, and challenges in negotiating GenAI use—which students navigated through increased effort, planning and self-regulation, use of multiple
In a six-week flipped EFL writing course, 58 second-year student teachers at a Thai university independently selected resources such as textbooks, websites, educational videos, and GenAI tools and synthesized their learning through handwritten notebook summaries; questionnaire responses showed generally positive perceptions of learning preparation, information management, learning responsibility, and writing readiness, while focus group discussions with 30 students revealed four interconnected constraints—limited linguistic and background knowledge, uncertainty without immediate teacher guidance, difficulty evaluating and synthesizing multiple resources, and challenges in negotiating GenAI use—which students navigated through increased effort, planning and self-regulation, use of multiple
58 Thai pre-service teachers chose their own resources and wrote handwritten notes in a six-week flipped writing course: most endorsed preparation and writing readiness, yet 73% struggled with vocabulary and grammar, 66% with judging multiple sources, and 53% with GenAI dependence
In a six-week flipped EFL writing course, 58 second-year student teachers at a Thai university independently selected resources such as textbooks, websites, educational videos, and GenAI tools and synthesized their learning through handwritten notebook summaries; questionnaire responses showed generally positive perceptions of learning preparation, information management, learning responsibility, and writing readiness, while focus group discussions with 30 students revealed four interconnected constraints—limited linguistic and background knowledge, uncertainty without immediate teacher guidance, difficulty evaluating and synthesizing multiple resources, and challenges in negotiating GenAI use—which students navigated through increased effort, planning and self-regulation, use of multiple
In a six-week flipped EFL writing course, 58 second-year student teachers at a Thai university independently selected resources such as textbooks, websites, educational videos, and GenAI tools and synthesized their learning through handwritten notebook summaries; questionnaire responses showed generally positive perceptions of learning preparation, information management, learning responsibility, and writing readiness, while focus group discussions with 30 students revealed four interconnected constraints—limited linguistic and background knowledge, uncertainty without immediate teacher guidance, difficulty evaluating and synthesizing multiple resources, and challenges in negotiating GenAI use—which students navigated through increased effort, planning and self-regulation, use of multiple
Research Square Sep 28, 2026
This study proposes a hybrid framework at the Sultan Qalawun School Complex in Historic Cairo, Egypt, integrating environmental simulation, machine learning techniques using the Hypar.io platform, and heritage conservation principles; through field data collection, geometric modeling, and AI-driven predictive models it examines the impacts of natural ventilation, vegetation, shading systems, and occupancy patterns on outdoor thermal comfort, evaluates interventions using Predicted Mean Vote (PMV), thermal discomfort hours, indoor environmental quality, and heritage preservation criteria, reports that AI-assisted simulation can reduce computational time by approximately 40% while maintaining high predictive accuracy relative to traditional physics-based simulations, and indicates that conse
This study proposes a hybrid framework at the Sultan Qalawun School Complex in Historic Cairo, Egypt, integrating environmental simulation, machine learning techniques using the Hypar.io platform, and heritage conservation principles; through field data collection, geometric modeling, and AI-driven predictive models it examines the impacts of natural ventilation, vegetation, shading systems, and occupancy patterns on outdoor thermal comfort, evaluates interventions using Predicted Mean Vote (PMV), thermal discomfort hours, indoor environmental quality, and heritage preservation criteria, reports that AI-assisted simulation can reduce computational time by approximately 40% while maintaining high predictive accuracy relative to traditional physics-based simulations, and indicates that conse
Team uses Hypar.io machine-learning microclimate simulation at Cairo's Sultan Qalawun complex, reporting about 40% less computation time with high predictive accuracy
This study proposes a hybrid framework at the Sultan Qalawun School Complex in Historic Cairo, Egypt, integrating environmental simulation, machine learning techniques using the Hypar.io platform, and heritage conservation principles; through field data collection, geometric modeling, and AI-driven predictive models it examines the impacts of natural ventilation, vegetation, shading systems, and occupancy patterns on outdoor thermal comfort, evaluates interventions using Predicted Mean Vote (PMV), thermal discomfort hours, indoor environmental quality, and heritage preservation criteria, reports that AI-assisted simulation can reduce computational time by approximately 40% while maintaining high predictive accuracy relative to traditional physics-based simulations, and indicates that conse
This study proposes a hybrid framework at the Sultan Qalawun School Complex in Historic Cairo, Egypt, integrating environmental simulation, machine learning techniques using the Hypar.io platform, and heritage conservation principles; through field data collection, geometric modeling, and AI-driven predictive models it examines the impacts of natural ventilation, vegetation, shading systems, and occupancy patterns on outdoor thermal comfort, evaluates interventions using Predicted Mean Vote (PMV), thermal discomfort hours, indoor environmental quality, and heritage preservation criteria, reports that AI-assisted simulation can reduce computational time by approximately 40% while maintaining high predictive accuracy relative to traditional physics-based simulations, and indicates that conse
Frontiers in Cognition Sep 28, 2026
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.
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.
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.
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.
Studies in Self-Access Learning Journal Sep 28, 2026
The study assigned 70 Omani pre-intermediate English learners to two groups of 35, with a control group receiving face-to-face instruction and an experimental group using NotebookLM AI as the main learning source for 80 target words; both groups improved on the posttest but the experimental group scored higher, the control group's scores dropped on the delayed posttest while the experimental group continued to improve, and the experimental group also outperformed the control group on a self-directed learning questionnaire.
The study assigned 70 Omani pre-intermediate English learners to two groups of 35, with a control group receiving face-to-face instruction and an experimental group using NotebookLM AI as the main learning source for 80 target words; both groups improved on the posttest but the experimental group scored higher, the control group's scores dropped on the delayed posttest while the experimental group continued to improve, and the experimental group also outperformed the control group on a self-directed learning questionnaire.
NotebookLM AI for Omani EFL Vocabulary: Experimental Group Kept Gaining on the Delayed Posttest While the Control Group Declined
The study assigned 70 Omani pre-intermediate English learners to two groups of 35, with a control group receiving face-to-face instruction and an experimental group using NotebookLM AI as the main learning source for 80 target words; both groups improved on the posttest but the experimental group scored higher, the control group's scores dropped on the delayed posttest while the experimental group continued to improve, and the experimental group also outperformed the control group on a self-directed learning questionnaire.
The study assigned 70 Omani pre-intermediate English learners to two groups of 35, with a control group receiving face-to-face instruction and an experimental group using NotebookLM AI as the main learning source for 80 target words; both groups improved on the posttest but the experimental group scored higher, the control group's scores dropped on the delayed posttest while the experimental group continued to improve, and the experimental group also outperformed the control group on a self-directed learning questionnaire.
Frontiers in Applied Mathematics and Statistics Sep 28, 2026
The study models two competing hybrid DC pension fund managers as a stochastic differential game in which liability risk follows a jump-diffusion process with truncated exponential jump amplitudes and the exact asset-to-liability ratio formulation is used, and it derives closed-form Nash equilibrium portfolio strategies and value functions via Hamilton–Jacobi–Bellman dynamic programming, finding that equilibrium weights are independent of liability jump parameters, reduce to K=(μ−r)/σ² and are independent of both managers' risk aversion in the symmetric liability-correlation case, that competition strictly amplifies risk-taking relative to the single-agent benchmark, and that a manager's own liability jumps reduce welfare while the competitor's jumps improve it.
The study models two competing hybrid DC pension fund managers as a stochastic differential game in which liability risk follows a jump-diffusion process with truncated exponential jump amplitudes and the exact asset-to-liability ratio formulation is used, and it derives closed-form Nash equilibrium portfolio strategies and value functions via Hamilton–Jacobi–Bellman dynamic programming, finding that equilibrium weights are independent of liability jump parameters, reduce to K=(μ−r)/σ² and are independent of both managers' risk aversion in the symmetric liability-correlation case, that competition strictly amplifies risk-taking relative to the single-agent benchmark, and that a manager's own liability jumps reduce welfare while the competitor's jumps improve it.
A game between two hybrid pension managers under jump-diffusion liabilities: competition pushes risk-taking to K=(μ−r)/σ², while own liability jumps lower welfare and the rival's jumps raise it
The study models two competing hybrid DC pension fund managers as a stochastic differential game in which liability risk follows a jump-diffusion process with truncated exponential jump amplitudes and the exact asset-to-liability ratio formulation is used, and it derives closed-form Nash equilibrium portfolio strategies and value functions via Hamilton–Jacobi–Bellman dynamic programming, finding that equilibrium weights are independent of liability jump parameters, reduce to K=(μ−r)/σ² and are independent of both managers' risk aversion in the symmetric liability-correlation case, that competition strictly amplifies risk-taking relative to the single-agent benchmark, and that a manager's own liability jumps reduce welfare while the competitor's jumps improve it.
The study models two competing hybrid DC pension fund managers as a stochastic differential game in which liability risk follows a jump-diffusion process with truncated exponential jump amplitudes and the exact asset-to-liability ratio formulation is used, and it derives closed-form Nash equilibrium portfolio strategies and value functions via Hamilton–Jacobi–Bellman dynamic programming, finding that equilibrium weights are independent of liability jump parameters, reduce to K=(μ−r)/σ² and are independent of both managers' risk aversion in the symmetric liability-correlation case, that competition strictly amplifies risk-taking relative to the single-agent benchmark, and that a manager's own liability jumps reduce welfare while the competitor's jumps improve it.

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