arXiv preprints from January 1, 2026 through September 30, 2026 — 05:33:12 EST
Combinatorial optimization augmented machine learning (COAML) has recently emerged as a powerful paradigm for integrating predictive models with combinatorial decision-making. By embedding combinatorial optimization oracles into learning pipelines, COAML enables the construction of policies that are both data-driven and...
Deploying Python-based AI agents on resource-constrained edge devices presents a critical runtime optimization challenge: high thread counts are needed to mask I/O latency, yet Python's Global Interpreter Lock (GIL) serializes execution. We demonstrate that naive thread pool scaling causes a "saturation cliff": a performance...
Comprehending genomic information is essential for biomedical research, yet extracting data from complex distributed databases remains challenging. Large language models (LLMs) offer potential for genomic Question Answering (QA) but face limitations due to restricted access to domain-specific databases. GeneGPT is the current...
Intrinsic evaluation metrics for conditional language models, such as perplexity or bits-per-character, are widely used in both mono- and multilingual settings. These metrics are rather straightforward to use and compare in monolingual setups, but rest on a number of assumptions in multilingual setups. One such assumption is that...
We present new Hubble Space Telescope (HST) UV spectra of the K2 V star HD 166620, the first star clearly recognized to be in a "magnetic grand minimum" state analogous to the Sun's "Maunder Minimum" in the late 1600's. The stellar H I Lyman-alpha surface fluxes are extremely low, about a factor of two below fluxes observed during...
Fascination with the concept of superconducting (SC) {\it superfluid density} $ρ_s$ has persisted since the beginning of superconductivity theory, with numerical values of an actual density rarely provided. Over time $ρ_s$, addressed mostly in cuprate and following high temperature superconductors, has become synonymous with the...
Instantaneous noise-based logic (INBL) is a novel computing approach that encodes binary information using stochastic processes. It uses 2M orthogonal stochastic reference noises for M noise-bits to construct an exponentially large Hilbert space (hyperspace) of dimension 2^M. INBL offers a classical alternative to quantum-style...
Image segmentation plays a central role in computer vision. However, widely used evaluation metrics, whether pixel-wise, region-based, or boundary-focused, often struggle to capture the structural and topological coherence of a segmentation. In many practical scenarios, such as medical imaging or object delineation, small inaccuracies...
Massive multiple-input multiple-output (MIMO) is esteemed as a critical technology in 6G communications, providing large degrees of freedom (DoF) to improve multiplexing gain. This paper introduces characteristic mode analysis (CMA) to derive the achievable DoF. Unlike existing works primarily focusing on the DoF of the wireless...
Modeling wireless channels accurately remains a challenge due to environmental variations and signal uncertainties. Recent neural networks can learn radio frequency~(RF) signal propagation patterns, but they process each voxel on the ray independently, without considering global context or environmental factors. Our paper presents a...
This letter considers 3d $\mathcal{N}=4$ (unitary-)orthosymplectic quiver gauge theories originating from Type IIA and Type IIB brane systems with $\mathrm{ON}^0$ planes. Such theories lie outside the scope of present combinatorial techniques for Coulomb branch symmetry and symplectic stratification. It turns out that the correct...
Large language models have achieved remarkable capabilities across domains, yet mechanisms underlying sophisticated reasoning remain elusive. Recent reasoning models outperform comparable instruction-tuned models on complex cognitive tasks, attributed to extended computation through longer chains of thought. Here we show that enhanced...
Social robots hold promise for reducing job interview anxiety, yet designing agents that provide both psychological safety and instructional guidance remains challenging. Through a three-phase iterative design study (N = 8), we empirically mapped this tension. Phase I revealed a "Safety-Guidance Gap": while a Person-Centered Therapy...
Value level parallelism (VLP) has been proposed to improve the efficiency of large-batch, low-precision general matrix multiply (GEMM) between symmetric activations and weights. In transformer based large language models (LLMs), there exist more sophisticated operations beyond activation-weight GEMM. In this paper, we explore how VLP...
We introduce a framework that integrates both analytical and machine-learning approaches for calculating observables optimal for EFT and broader applications at the LHC. A new metric for evaluating the performance of these approaches has been introduced. In addition, we demonstrate how the majority of relevant information can be...
Superparamagnetic magnetic tunnel junctions (sMTJs) are promising components for true random number generation and probabilistic computing. Achieving high-frequency fluctuation while maintaining reliable control over output level is critical for applications. In this work, we systematically investigate the role of magnetic damping in...
Let $R$ be a finite local ring. We prove a quantitative universality statement for the cokernel of random matrices with i.i.d. entries valued in $R$. Rather than use the moment method, we use the Lindeberg replacement technique. This approach also yields a universality result for several invariants that are finer than the cokernel,...
Recent advances in code generation models have unlocked unprecedented opportunities for automating feature engineering, yet their adoption in real-world ML teams remains constrained by critical challenges: (i) the scarcity of datasets capturing the iterative and complex coding processes of production-level feature engineering, (ii)...
Accurate 3D object perception and multi-target multi-camera (MTMC) tracking are fundamental for the digital transformation of industrial infrastructure. However, transitioning "inside-out" autonomous driving models to "outside-in" static camera networks presents significant challenges due to heterogeneous camera placements and extreme...
High-resolution total solar eclipse (TSE) white light (WL) images are the only observations at present to capture coronal structures over an uninterrupted field of view (FoV) of at least 10 solar radii (Rs) starting from the solar limb. They were the first to report the presence of vortex rings originating within the prominence-corona...
We present a comprehensive reanalysis of the dynamical state of the high-redshift galaxy cluster SPT-CL J2215-3537 (z = 1.16), using the full set of available Chandra observations to characterize the thermodynamic and morphological properties of the intracluster medium. Although previously identified as one of the most distant...
Natural organisms have evolved integrated Latch-Mediated Spring Actuation systems (LaMSA) that consist of multiple latches and springs to enhance power output and adapt to diverse environmental conditions. Similar designs are appealing yet largely unexplored in engineered materials due to the complexity of integrating multiple...
We deform block triangular Jacobi matrices appearing in geometry, look at multi-scale Barycentric limits of geometries and droplet boundary manifolds in Potts networks.
Localization and mapping are core perceptual capabilities for underwater robots. Stereo cameras provide a low-cost means of directly estimating metric depth to support these tasks. However, despite recent advances in stereo depth estimation on land, computing depth from image pairs in underwater scenes remains challenging. In...
Progress towards quantum utility in chemistry requires not only algorithmic advances, but also the identification of chemically meaningful problems whose electronic structure fundamentally challenges classical methods. Here, we introduce a curated hierarchy of chemically decisive benchmark systems designed to probe distinct regimes of...