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arXiv preprints from January 1, 2026 through September 19, 2026 — 20:10:26 EST

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Posted in math.AG · 2026-01-19 · Antonio Carbone, José F. Fernando

Nash approximation of differentiable semialgebraic maps

Let $T\subset{\mathbb R}^n$ be a semialgebraic set and let $μ\ge0$ be a non-negative integer. We say that $T$ is a {\em Nash $μ$-approximation target space} (or a $({\mathcal N},μ)$-${\tt ats}$ for short) if it has the following universal approximation property: {\em For each $m\in{\mathbb N}$ and each locally compact semialgebraic...

💬 0 commentsarXiv:2601.13164v1PDF
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Posted in cond-mat.soft · 2026-01-19 · Andrea Bonato

Counting unlabelled multigraphs with three nodes

Unlabeled multigraphs have diverse applications across scientific fields, from transportation and social networks to polymer physics. In particular, multigraphs are essential for studying the relationship between the spatial organization and biological function of chromatin, which is often folded into complex polymer networks whose...

💬 0 commentsarXiv:2601.13163v1PDF
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Posted in cs.LG · 2026-01-19 · Ali Shafiee Sarvestani, Jason Schmidt, Arman Roohi

NeuroShield: A Neuro-Symbolic Framework for Adversarial Robustness

Adversarial vulnerability and lack of interpretability are critical limitations of deep neural networks, especially in safety-sensitive settings such as autonomous driving. We introduce \DesignII, a neuro-symbolic framework that integrates symbolic rule supervision into neural networks to enhance both adversarial robustness and...

💬 0 commentsarXiv:2601.13162v1PDF
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Posted in math.DS · 2026-01-19 · Tom Meyerovitch

A new notion of dimension for dynamical systems and shift embeddability

A dynamical system $(X,T)$ is \emph{shift embeddable} if $(X,T)$ embeds continuously and equivariantly in the shift over $[0,1]^d$ for some finite $d$. Refuting a major conjecture in the field, in a recent result of Dranishnikov and Levin it was shown that Gromov's mean dimension and Lebesgue covering dimension of finite orbits are...

💬 0 commentsarXiv:2601.13161v3PDF
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Posted in cs.LG · 2026-01-19 · Zhipeng Zhang, Zhenjie Yao, Kai Li, Lei Yang

Training instability in deep learning follows low-dimensional dynamical principles

Deep learning systems achieve remarkable empirical performance, yet the stability of the training process itself remains poorly understood. Training unfolds as a high-dimensional dynamical system in which small perturbations to optimization, data, parameters, or learning signals can induce abrupt and irreversible collapse, undermining...

💬 0 commentsarXiv:2601.13160v1PDF
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Posted in math.MG · 2026-01-19 · Tom Baumbach

On the discrete logarithmic Minkowski problem in the plane

The paper characterizes the convex hull of the closure of the cone-volume set $C_\cv(U)$, consisting of all cone-volume vectors of polygons with outer unit normals vectors contained in $U$, for any finite set $U \subseteq \R^2, \pos(U) = \R^2$. We prove that this convex hull has finitely many extreme points by providing both a vertex...

💬 0 commentsarXiv:2601.13159v1PDF
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Posted in math.PR · 2026-01-19 · Robert E. Gaunt

On the characteristic function of the asymmetric Student's $t$-distribution and an integral involving the sine function

We obtain a new closed-form formula for the characteristic function of the asymmetric Student's $t$-distribution. As part of our analysis, we derive a new closed-form formula for the integral $\int_0^\infty \sin(ax)/(b^2+x^2)^n\,\mathrm{d}x$, for $a,b>0$, $n\in\mathbb{Z}^+$, expressed in terms of the exponential integral function. As...

💬 0 commentsarXiv:2601.13158v2PDF
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Posted in eess.SP · 2026-01-19 · Hang Zou, Bohao Wang, Yu Tian, Lina Bariah, Chongwen Huang, Samson Lasaulce, Mérouane Debbah

Seeing Radio: From Zero RF Priors to Explainable Modulation Recognition with Vision Language Models

Current RF machine-learning pipelines rely on task-specific deep networks for modulation classification and related tasks, but these models require custom architectures and labeled datasets for each problem, generalize poorly across channel conditions and SNRs, and offer little interpretability. In contrast, modern multimodal large...

💬 0 commentsarXiv:2601.13157v2PDF
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Posted in cond-mat.mtrl-sci · 2026-01-19 · Ryan Trice, Mingyu Yu, Eric Welp, Morgan Applegate, Wesley Reinhart, Stephanie Law

Machine Learning Guided Polymorph Selection in Molecular Beam Epitaxy of In2Se3

Indium selenide (In2Se3), a layered chalcogenide with multiple polymorphs, is a promising material for optoelectronic and ferroelectric applications. However, achieving polymorph-pure thin films remains a major challenge due to the complex growth space. In this work, Bayesian optimization (BO) is successfully leveraged to guide the...

💬 0 commentsarXiv:2601.13156v2PDF
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Posted in cs.CL · 2026-01-19 · Zimeng Wu, Donghao Wang, Chaozhe Jin, Jiaxin Chen, Yunhong Wang

Probe and Skip: Self-Predictive Token Skipping for Efficient Long-Context LLM Inference

Long-context inference enhances the reasoning capability of Large Language Models (LLMs), but incurs significant computational overhead. Token-oriented methods, such as pruning and skipping, have shown great promise in reducing inference latency, yet still suffer from inherently insufficient structure optimization, outdated selection...

💬 0 commentsarXiv:2601.13155v2PDF
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Posted in cond-mat.mtrl-sci · 2026-01-19 · Krystof Chrappova, Jeremiah P. Tidey, Christopher Bell, Simon R. Hall

Magnetism and 3D Electron Diffraction Solution of Hydrated Rubidium-Ruthenium Oxide Rb$_2$Ru$_2$O$_7$.H$_2$O

The crystal structure of Rb$_2$Ru$_2$O$_7$.H$_2$O was determined by three-dimensional electron diffraction from the individual crystallites of a solid-state powder product. Rb$_2$Ru$_2$O$_7$.H$_2$O crystallizes in space group \textit{C}2/\textit{c} ($a=7.841(3)$ Å, $b=12.500(3)$ Å, $c=8.392(2)$ Å, $β=93.57(4)^\circ$, Z=4). The...

💬 0 commentsarXiv:2601.13154v1PDF
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Posted in hep-ex · 2026-01-19 · Diego Baron

Recent measurements from the ATLAS experiment of Multi-Boson production processes at the LHC

The high-energy proton-proton collisions at the Large Hadron Collider provide the ideal conditions to study the rare processes predicted by the Standard Model (SM) such as the production of multiple electroweak bosons. These processes involve the self-interactions of the gauge bosons through triple and quartic gauge couplings (TGCs...

💬 0 commentsarXiv:2601.13153v1PDF
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Posted in math.RT · 2026-01-19 · Bim Gustavsson

Character degrees in $2$-blocks of $\mathfrak{S}_n$ and $\mathfrak{A}_n$

Let $p$ be an odd prime. We show that for sufficiently large $n$, every $2$-block of $\mathfrak{S}_n$ and $\mathfrak{A}_n$ contains an ordinary irreducible character of degree divisible by $p$. For almost all $2$-blocks of $\mathfrak{A}_n$, we classify whether it contains a rational valued ordinary irreducible character of degree...

💬 0 commentsarXiv:2601.13152v1PDF
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Posted in math.AG · 2026-01-19 · Seung-Jo Jung, Morihiko Saito

Factoriality of normal projective varieties

For a normal projective variety $X$, the $\bf Q$-factoriality defect $σ(X)$ is defined to be the rank of the quotient of the group of Weil divisors by the subgroup of Cartier ones. We prove a slight improvement of a topological formula of S.G. Park and M. Popa asserting that $σ(X)=h^{2n-2}(X)-h^2(X)$ by assuming only...

💬 0 commentsarXiv:2601.13151v5PDF
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Posted in cs.LG · 2026-01-19 · Takato Yasuno

Distributional Reinforcement Learning for Condition-Based Maintenance of Multi-Pump Equipment

Condition-Based Maintenance (CBM) signifies a paradigm shift from reactive to proactive equipment management strategies in modern industrial systems. Conventional time-based maintenance schedules frequently engender superfluous expenditures and unanticipated equipment failures. In contrast, CBM utilizes real-time equipment condition...

💬 0 commentsarXiv:2602.00051v1PDF
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Posted in stat.ME · 2026-01-19 · Siyu Heng, Yanxin Shen, Zijian Guo

Propensity Score Propagation: A General Framework for Design-Based Inference with Unknown Propensity Scores

Design-based inference, also known as randomization-based or finite-population inference, provides a principled framework for trustworthy statistical inference. It attributes randomness solely to the design mechanism, such as treatment assignment, survey sampling, or missingness, without imposing super-population distributional or...

💬 0 commentsarXiv:2601.13150v4PDF
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Posted in math.OC · 2026-01-19 · Matko Grbac, Ivan Ivec, Marko Vrdoljak

Classical Optimal Designs for Stationary Diffusion with Multiple Phases

We study optimal design problems for stationary diffusion involving one or more state equations and mixtures of an arbitrary number of anisotropic materials. Since such problems typically do not admit classical solutions, we adopt a homogenization-based relaxation framework. The objective considered is the maximization of a weighted...

💬 0 commentsarXiv:2601.13149v1PDF
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Posted in cs.CV · 2026-01-19 · Richard Shaw, Youngkyoon Jang, Athanasios Papaioannou, Arthur Moreau, Helisa Dhamo, Zhensong Zhang, Eduardo Pérez-Pellitero

ICo3D: An Interactive Conversational 3D Virtual Human

This work presents Interactive Conversational 3D Virtual Human (ICo3D), a method for generating an interactive, conversational, and photorealistic 3D human avatar. Based on multi-view captures of a subject, we create an animatable 3D face model and a dynamic 3D body model, both rendered by splatting Gaussian primitives. Once merged...

💬 0 commentsarXiv:2601.13148v1PDF
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Posted in hep-ph · 2026-01-19 · Jaydeb Das, Saurabh Niyogi, Tripurari Srivastava

Revisiting Singlet Fermion Dark Matter with a Scalar Portal: Connecting Higgs Phenomenology and Strong Electroweak Phase Transition

We investigate a minimal extension of the Standard Model with a real singlet scalar and a singlet Dirac fermion acting as dark matter. Unlike a conventional singlet scalar setup, we assume that the singlet scalar does not acquire a vacuum expectation value at zero temperature. This decouples the scalar mixing angle from the...

💬 0 commentsarXiv:2601.13147v4PDF
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Posted in cs.DC · 2026-01-19 · Nicolas Nicolaou, Kishori M. Konwar, Moritz Grundei, Aleksandr Bezobchuk, Muriel Médard, Sriram Vishwanath

OPTIMUM-DERAM: Highly Consistent, Scalable, and Secure Multi-Object Memory using RLNC

This paper introduces OPTIMUM-DERAM, a highly consistent, scalable, secure, and decentralized shared memory solution. Traditional distributed shared memory implementations offer multi-object support by multi-threading a single object memory instance over the same set of data hosts. While theoretically sound, the amount of resources...

💬 0 commentsarXiv:2601.13146v1PDF
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Posted in astro-ph.SR · 2026-01-19 · Spiridon Kasapis, Eren Dogan, Irina N. Kitiashvili, Alexander G. Kosovichev, John T. Stefan, Jake D. Butler, Jonas Tirona, Sarang Patil, Mengjia Xu

SolARED: Solar Active Region Emergence Dataset for Machine Learning Aided Predictions

The development of accurate forecasts of solar eruptive activity has become increasingly important for preventing potential impacts on space technologies and exploration. Therefore, it is crucial to detect Active Regions (ARs) before they start forming on the solar surface. This will enable the development of early-warning...

💬 0 commentsarXiv:2601.13145v1PDF
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Posted in astro-ph.SR · 2026-01-19 · Jonas Tirona, Sarang Patil, Spiridon Kasapis, Eren Dogan, John Stefan, Irina N. Kitiashvili, Alexander G. Kosovichev, Mengjia Xu

Forecasting Continuum Intensity for Solar Active Region Emergence Prediction using Transformers

Early and accurate prediction of solar active region (AR) emergence is crucial for space weather forecasting. Building on established Long Short-Term Memory (LSTM) based approaches for forecasting the continuum intensity decrease associated with AR emergence, this work expands the modeling with new architectures and targets. We...

💬 0 commentsarXiv:2601.13144v1PDF
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Posted in cs.LG · 2026-01-19 · Chaeyoung Jung, Youngjoon Jang, Seungwoo Lee, Joon Son Chung

FastAV: Efficient Token Pruning for Audio-Visual Large Language Model Inference

In this work, we present FastAV, the first token pruning framework tailored for audio-visual large language models (AV-LLMs). While token pruning has been actively explored in standard large language models (LLMs) and vision-language models (LVLMs), its application to AV-LLMs has received little attention, even though multimodal...

💬 0 commentsarXiv:2601.13143v1PDF
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Posted in cs.CV · 2026-01-19 · Zhantao Ma, Quanfeng Lu, Shuai Zhong, Dahai Yu, Ping Luo, Michael K. Ng

TVWorld: Foundations for Remote-Control TV Agents

Recent large vision-language models (LVLMs) have demonstrated strong potential for device control. However, existing research has primarily focused on point-and-click (PnC) interaction, while remote-control (RC) interaction commonly encountered in everyday TV usage remains largely underexplored. To fill this gap, we introduce...

💬 0 commentsarXiv:2601.13142v1PDF
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Posted in astro-ph.GA · 2026-01-19 · Timur Grigorev, Yuhang Dai, Max Potter, Xiaoyu Xiang, Keyu Zhang, Jonathan Tennyson

MARVEL Analysis of the Measured High-resolution Spectra of CO Isotopologues

Carbon monoxide is thought to be the second most abundant molecule in the Universe. This makes observation of both its parent isotopologue ($^{12}$C$^{16}$O) and its stable isotopologues, $^{13}$C$^{16}$O, $^{12}$C$^{18}$O, $^{12}$C$^{17}$O, $^{13}$C$^{18}$O and $^{13}$C$^{17}$O, important in variety of objects. Here the MARVEL...

💬 0 commentsarXiv:2601.13141v1PDF