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108

arXiv:2512.16457v1 Announce Type: new
Abstract: The relationship between socioeconomic background, academic performance, and post-secondary educational outcomes remains a significant concern for policymakers and researchers globally. While the literature often relies on self-reported or aggregate d…
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212

arXiv:2512.15824v1 Announce Type: new
Abstract: Circular economy (CE) triage is the assessment of products to determine which sustainable pathway they can follow once they reach the end of their usefulness as they are currently being used. Effective CE triage requires adaptive decisions that balanc…
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220

arXiv:2507.03558v3 Announce Type: replace
Abstract: Brain stroke is a leading cause of mortality and long-term disability worldwide, underscoring the need for precise and rapid prediction techniques. Computed Tomography (CT) scan is considered one of the most effective methods for diagnosing brain …
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218

arXiv:2507.00788v2 Announce Type: replace
Abstract: [Context] AI assistants, like GitHub Copilot and Cursor, are transforming software engineering. While several studies highlight productivity improvements, their impact on maintainability requires further investigation. [Objective] This study inves…
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122

arXiv:2509.24639v2 Announce Type: replace
Abstract: This paper explores stability properties of periodic solutions of (nonlinear) fractional-order differential equations (FODEs). As classical Caputo-type FODEs do not admit exactly periodic solutions, we propose a framework of Liouville-Weyl-type FO…
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227

arXiv:2512.16148v1 Announce Type: new
Abstract: Disaggregated memory (DM) is a promising data center architecture that decouples CPU and memory into independent resource pools to improve resource utilization. Building on DM, memory-disaggregated key-value (KV) stores are adopted to efficiently mana…
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120

arXiv:2512.15728v1 Announce Type: cross
Abstract: The Federal Open Market Committee (FOMC) sets the federal funds rate, shaping monetary policy and the broader economy. We introduce \emph{FedSight AI}, a multi-agent framework that uses large language models (LLMs) to simulate FOMC deliberations and…
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120

arXiv:2512.16414v1 Announce Type: new
Abstract: Democracy relies on making collective decisions through voting. In addition, voting procedures have further applications, for example in the training of artificial intelligence. An essential criterion for determining the winner of a fair election is t…
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230

arXiv:2512.15675v2 Announce Type: replace
Abstract: This paper proposes a training data augmentation pipeline that combines synthetic image data with neural style transfer in order to address the vulnerability of deep vision models to common corruptions. We show that although applying style transfe…
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109

arXiv:2512.16345v1 Announce Type: new
Abstract: This paper provides conditions to ensure contractive behavior of Filippov solutions generated by multi-modal piecewise smooth (PWS) systems. These conditions are instrumental in analyzing the asymptotic behavior of PWS systems, such as convergence tow…
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110

arXiv:2512.15944v1 Announce Type: new
Abstract: The growing adoption of generative AI (GenAI) is reshaping how user experience (UX) research teams conduct qualitative research in software development, creating opportunities to streamline the production of qualitative insights. This paper presents f…
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111

arXiv:2512.16001v1 Announce Type: cross
Abstract: Measuring the statistical dependence between observed signals is a primary tool for scientific discovery. However, biological systems often exhibit complex non-linear interactions that currently cannot be captured without a priori knowledge or large…
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213

arXiv:2512.16763v1 Announce Type: new
Abstract: A complex system comprises multiple interacting entities whose interdependencies form a unified whole, exhibiting emergent behaviours not present in individual components. Examples include the human brain, living cells, soft matter, Earth's climate, e…
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329

arXiv:2512.15742v1 Announce Type: new
Abstract: Kolmogorov-Arnold Networks (KANs) face a fundamental memory wall: their learned basis functions create parameter counts that impose extreme bandwidth demands, hindering deployment in memory-constrained environments. We show that Vision KANs exhibit a …
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