arXiv preprints from January 1, 2026 through September 26, 2026 — 03:56:09 EST
In this paper, we extend distance correlation to categorical data with general encodings, such as one-hot encoding for nominal variables and semicircle encoding for ordinal variables. Unlike existing methods, our approach leverages the spacing information between categories, which enhances the performance of distance correlation. Two...
Explaining numerical physics problems often requires more than text-based solutions; clear visual reasoning can substantially improve conceptual understanding. While large language models (LLMs) demonstrate strong performance on many physics questions in textual form, their ability to generate long, high-quality visual explanations...
This document presents a comprehensive simulation framework designed to model urban incidents involving pedestrians and vehicles. Using a multiagent systems approach, two types of agents (pedestrians and vehicles) are introduced within a 2D grid based urban environment. The environment encodes streets, sidewalks, buildings, zebra...
This paper introduces a novel framework for robotic vision-based navigation that integrates Hybrid Neural Networks (HNNs) with Spiking Neural Network (SNN)-based filtering to enhance situational awareness for unmodeled obstacle detection and localization. By leveraging the complementary strengths of Artificial Neural Networks (ANNs)...
We present the analysis of four microlensing events, KMT-2020-BLG-0202, KMT-2022-BLG-1551, KMT-2023-BLG-0466, and KMT-2025-BLG-0121, which exhibit extended and complex anomalies in their light curves. These events were identified through a systematic reanalysis of KMTNet data aimed at detecting planetary signals that deviate from the...
Differential item functioning (DIF) is a widely used statistical notion for identifying items that may disadvantage specific groups of test-takers. These groups are often defined by non-manipulable characteristics, e.g., gender, race/ethnicity, or English-language learner (ELL) status. While DIF can be framed as a causal fairness...
Despite their promise, fair machine learning methods often yield Pareto-inefficient models, in which the performance of certain groups can be improved without degrading that of others. This issue arises frequently in traditional in-processing approaches such as fairness-through-regularization. In contrast, existing Pareto-efficient...
We discuss the most recent observations made with the Southern Connecticut Stellar Interferometer (SCSI), which is a three-station stellar intensity interferometer located on the campus of Southern Connecticut State University, in New Haven, Connecticut. Two different kinds of observations are presented. We first analyze observations...
In this paper, we study possibly non-closed big (1, 1)-forms on a compact Hermitian manifold satisfying the bounded mass property. We propose several criteria for the existence of rooftop envelopes. As applications, we establish the existence of solutions to complex Monge-Ampere type equations with prescribed singularities, allowing...
Generative AI has emerged as a transformative paradigm in engineering design, enabling automated synthesis and reconstruction of complex 3D geometries while preserving feasibility and performance relevance. This paper introduces a domain-specific implicit generative framework for turbine blade geometry using DeepSDF, addressing...
We establish, for the first time, explicit a priori and regularity estimates for solutions of the Dirichlet problem for Hamilton-Jacobi-Bellman operators from stochastic control, whose principal half-eigenvalues have opposite signs. In addition, if the negative eigenvalue is not too negative, the problem can have exactly two, one or...
The rapid adoption of large language models (LLMs) has enabled new forms of AI-assisted reasoning across scientific, technical, and organizational domains. However, prevailing modes of LLM use remain cognitively unstructured: problem framing, knowledge exploration, retrieval, methodological awareness, and explanation are typically...
OBJECTIVES: The grandmother hypothesis proposes that ancestral women ceased reproduction midlife to instead provision their grandchildren. An alternative two-sex account proposes that the high energetic burden of caring for slow-developing offspring was met with biparental investment. Menopause evolved because the physiological costs...
Signatures of new physics at the LHC are varied and, by nature, often very different from those of Standard Model processes. Novel experimental techniques, including dedicated data streams, are exploited to enhance the sensitivity of the CMS Experiment to search for such signatures. This report highlights the CMS results obtained...
Vision-Language Models (VLMs), particularly CLIP, have revolutionized anomaly detection by enabling zero-shot and few-shot defect identification without extensive labeled datasets. By learning aligned representations of images and text, VLMs facilitate anomaly classification and segmentation through natural language descriptions of...
We report magnetic susceptibility, isothermal magnetization, and specific-heat measurements on the rare-earth hexaaluminate SmMgAl$_{11}$O$_{19}$, where Sm$^{3+}$ realizes a strongly quenched Kramers doublet on a triangular lattice with an exceptionally weak net exchange scale. The Curie--Weiss analysis yields strongly reduced...
We present a novel tunnel architecture for the Einstein Telescope that departs from the traditional large-cavern approach and reduces the excavated volume by an order of magnitude. In the proposed design, all seismic isolation systems are housed in raise-bore wells drilled upward from the main tunnel toward an upper service tunnel....
Open-set learning and discovery (OSLD) is a challenging machine learning task in which samples from new (unknown) classes can appear at test time. It can be seen as a generalization of zero-shot learning, where the new classes are not known a priori, hence involving the active discovery of new classes. While zero-shot learning has...
Electron paramagnetic resonance (EPR) is a valuable tool for physics, chemistry, biology and medicine, providing complementary spectroscopic information to NMR. It has long been known that EPR at high magnetic fields offers greater spectral resolution, but limitations in the THz instrumentation have prevented the full realization of...
Linearly parametrized models are widely used in control and signal processing, with the least-squares (LS) estimate being the archetypical solution. When the input is insufficiently exciting, the LS problem may be unsolvable or numerically unstable. This issue can be resolved through regularization, typically with ridge regression....
Learning profitable intraday trading policies from financial time series is challenging due to heavy noise, non-stationarity, and strong cross-sectional dependence among related assets. We propose \emph{WaveLSFormer}, a learnable wavelet-based long-short Transformer that jointly performs multi-scale decomposition and return-oriented...
In this work, we investigate $CO_{2}$ activation on ZnS using Near Ambient-Pressure X-ray photoelectron spectroscopy measurements (NAP-XPS) and density functional theory calculations (DFT). Our NAP-XPS experiments reveal that $CO_{2}$ adsorbs onto a defective ZnS surface upon heating above $473 \ K$ in a $CO_{2}$ atmosphere (up to...
Prior research demonstrates that performance of language models on reasoning tasks can be influenced by suggestions, hints and endorsements. However, the influence of endorsement source credibility remains underexplored. We investigate whether language models exhibit systematic bias based on the perceived expertise of the provider of...
We show that the homotopy type of the independence complex of the generalized Mycielskian of a graph $G$ is determined by the homotopy type of the independence complex of $G$ and the homotopy type of the independence complex of the Kronecker double cover of $G$. As an application we calculate the homotopy type for paths, cycles and...
We study the local evolution of the Universe around galaxy formation sites in the EAGLE50 large-volume reference simulation. Using the reduced inertia tensor (r-TOI), we followed the anisotropic evolution of initially spherical Lagrangian volumes (LVs) centred at galaxy formation sites, both in dark matter (DM) and in cold baryons...