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Remote-sensing multimodal large language models (MLLMs) often assert facts that imagery cannot establish, such as a facility's identity or function. Coordinate-keyed geographic retrieval can supply this missing knowledge, improving fMoW…

XR sports viewing enables spectators to follow play from immersive, spatially anchored perspectives while accessing contextual analytics directly within the scene. In such settings, speech offers a practical interaction modality because…

Microphones mounted on UAVs enable aerial acoustic scene analysis applications such as search-and-rescue, wildlife monitoring, and industrial inspection. However, drone rotor noise often dominates the mixture signal at SNRs well below -10…

We investigate the production of Dark Matter (DM) within the warm Higgs--Starobinsky (HS) inflation. By adopting the ultraviolet (UV) freeze--in mechanism -- where the DM number density is initially negligible but is populated over time…

We study long-memory continuous-time moving-average processes driven by a Levy process and observed at random renewal times. The sampling scheme introduces an additional source of randomness through irregular observation times. We establish…

Federated Learning (FL) enables collaborative training of machine learning models across multiple institutions without sharing sensitive data, making it particularly suitable for medical imaging applications. However, heterogeneous data…

Non-relativistic spin-splitting (NRSS) antiferromagnets have recently emerged as an important class of magnetic materials that combine compensated magnetism with momentum-dependent spin splitting, offering new opportunities for spintronic…

Panoptic crop mapping requires both delineating individual agricultural parcels and assigning a crop type to each parcel from satellite image time series. Existing approaches typically rely on dense parcel-level annotations and…

Internet of Medical Things (IoMT) networks are hard to protect: devices are heterogeneous, computing resources are scarce, and traffic must be analyzed in real time. We present an intrusion detection system that addresses these constraints…

Many open educational resources are lacking in accessibility, especially in-depth image descriptions. In subjects like Science and Mathematics, however, it can be particularly difficult to write image descriptions since there can be many…

Graphics processing unit (GPU) architectures are growing in size to meet the increasing compute and memory requirements. As GPU sizes increase, intra-socket wire transfer delay increases significantly. While previous research has optimized…

We determine the small-oscillation period of a simple pendulum in Schwarzschild spacetime. After transients decay, the displaced rope coincides with a geodesic of the induced spatial metric. This determines the radial lift of the bob to…

We perturb one-dimensional Dirac operators on a bounded interval subject to Dirichlet boundary conditions by potentials with Fourier coefficients exhibiting power-decay. As a consequence of Paley-Zygmund theorem, this broad family of…

Currently, there exist only three strongly invertible L-space knots that are known to admit no Khovanov thin surgery. In this article, we give the first infinite family of such knots.

This work is concerned with weighted Geometric Rigidity Estimates and Korn's first inequalities in bulk and thin domains. We consider weights, that are a nonnegative power of the distance function to part of the boundary of the domain. For…

The purpose of this paper is to contribute to the further study of Loday algebroids by introducing, first, the concept of action Loday algebroid and clarifying the notion of a (co)morphism of Loday algebroids. We then focus on the study of…

A family of subsets of $[n]$ is called intersecting if it contains no pair of disjoint sets. It is called trivial if all its members contain a common element. Frankl and Kupavskii, and independently Balogh, Das, Liu, Sharifzadeh, and Tran,…

The cost of storing and transmitting a trained neural network scales with its parameter count, a bottleneck for over-the-air updates, on-device libraries, and other bandwidth-bound deployments. We study an extreme form of model compression…

Kolmogorov--Arnold Networks (KANs) replace scalar edge weights with learnable univariate functions parameterized by multiple basis coefficients. This introduces a source of redundancy that conventional neural-network compression does not…

We introduce data-driven measures of high-frequency trading (HFT) that distinguish between liquidity-supplying and liquidity-demanding strategies. We train machine learning models on a proprietary dataset with observed HFT activity, then…