December 2025 arXiv papers — page 37

Yuanshuang Fu, Qianyao Wang, Qihao Wang, Bonan Zhang

Unmanned Aerial Vehicle (UAV) spectral remote sensing technology is widely used in water quality monitoring. However, in dynamic environments, varying illumination conditions, such as shadows and specular reflection (sun glint), can cause severe spectral distortion, thereby reducing data availability. To maximize the acquisition of high-quality data while en

Niyousha Ghiasi, Bahare Kiumarsi, Hamidreza Modares

This paper presents an elastic tube-based model predictive control (MPC) framework for unknown discrete-time linear systems subject to disturbances. Unlike most existing elastic tube-based MPC methods, we do not assume perfect knowledge of the system model or disturbance realizations bounds. Instead, a conservative zonotopic disturbance set is initialized an

Menno H. Jansen, Cauê M. Kersul, Ewold Verhagen

In micro- and nanoscale optomechanical systems, radiation pressure interactions are often complemented or impeded by photothermal forces arising from thermal strain induced by optical heating. We show that the sign and magnitude of the photothermal force can be engineered through deterministic nanoscale structural design, by considering the overlap of temper

Nick Dawes

A modified dynamic programming algorithm rapidly and accurately solves large 0/1 knapsack problems. It has computational O(nlogn), space O(nlogn) and predictable maximum error. Experimentally it's accuracy increases faster than linearly with the solution size k. Problems with k=1e3 are solved with an average maximum fractional error of 1e-4 and problems with

Brigitta Malagurski Törtei, Yasser Dahou, Ngoc Dung Huynh, Wamiq Reyaz Para

Vision-Language Models (VLMs) have achieved remarkable progress across tasks such as visual question answering and image captioning. Yet, the extent to which these models perform visual reasoning as opposed to relying on linguistic priors remains unclear. To address this, we introduce VisRes Bench, a benchmark designed to study visual reasoning in naturalist

Brani Vidakovic

Kolmogorov complexity of a finite binary word reflects both algorithmic structure and the empirical distribution of symbols appearing in the word. Words with symbol frequencies far from one half have smaller combinatorial richness and therefore appear less complex under the standard definition. In this paper an entropy-normalized complexity measure is introd

Sarah Auster, Yeon-Koo Che

This paper revisits the classic Pandora's box problem, studying a decision-maker (DM) who seeks to minimize her maximal ex-post regret. The DM decides how many options to explore and in what order, before choosing one or taking an outside option. We characterize the regret-minimizing search rule and show that the likelihood of opting out often increases

Ze-Kun Liu, Ying Li, Biao-Feng Hou, Qin Chang

Current dark matter direct detection experiments have low sensitivity to sub-GeV dark matter. In this work, we demonstrate that rare $B$ and $K$ meson decays with missing energy in the final state can serve as efficient probes in this mass range. We analyze a generic $Z^{\prime}$ portal dark matter model and derive upper limits on its parameters from experim

Qaasim Shafi, Calla Tschanz

We construct the first examples of good type III degenerations of hyperk\"ahler varieties in dimension greater than 2. These are presented as moduli of 0-dimensional subschemes on expansions of a degeneration of K3 surfaces. We prove projectivity for our expanded degenerations and compute the dual complexes of the special fibre for two specific degenerations

Andrei A. Kugut, Grigoriy S. Mazhorin, Ilya A. Simakov

Fluxonium qubits demonstrate exceptional potential for quantum processing; yet, realizing scalable architectures using them remains challenging. We propose a fluxonium-based square-grid design with fast $\sim63$~ns controlled-Z (CZ) gates, achieving coherent errors below $10^{-4}$, activated via microwave-driven transmon couplers. A central difficulty in suc

Jean-Marie Hameury

The disc instability model successfully reproduces many of the observed properties of cataclysmic variables. However, additional ingredients such as mass-transfer variations, disc irradiation, stream-disc overflow, or inner-disc truncation must be included to explain certain systems. The physics underlying these processes is often poorly constrained, and our

Haoling Xiang

We study the inhomogeneous kinetic Fermi-Pasta-Ulam (FPU) equation, a nonlinear transport equation describing the evolution of phonon density distributions with four-phonon interactions. The equation combines free transport in physical space with a nonlinear collision operator acting in momentum space and exhibiting structural degeneracies. We develop a func

Tieguang Zi, Chang-Qing Ye

We compute the gravitational wave signal from eccentric extreme-mass-ratio inspirals (EMRIs) embedded within beyond-vacuum environments, where the secondary object carries a scalar charge and evolves in the presence of both an accretion disk and a dark matter halo. The waveform modification is derived by incorporating the scalar charge correcting the fluxes

Tanghui Jia, Dongyu Yan, Dehao Hao, Yang Li

In this report, we introduce UltraShape 1.0, a scalable 3D diffusion framework for high-fidelity 3D geometry generation. The proposed approach adopts a two-stage generation pipeline: a coarse global structure is first synthesized and then refined to produce detailed, high-quality geometry. To support reliable 3D generation, we develop a comprehensive data pr

Daniyal Ganiuly, Nurzhau Bolatbek, Assel Smaiyl

Smart home IoT systems rely on authentication mechanisms to ensure that only authorized entities can control devices and access sensitive functionality. In practice, these mechanisms must balance security with usability, often favoring persistent connectivity and minimal user interaction. This paper presents an empirical analysis of authentication enforcemen

A. Galoyan, A. Ribon, V. Uzhinsky

The total yield of neutral D-mesons (4$\pi$) in central Xe+La interactions at 150 GeV per nucleon has been calculated within the Geant4 FTF model. Our calculation is close to predictions of Monte Carlo models that do not account for quark-gluon plasma formation. As the predictions, our calculation substantially underestimates preliminary experimental data. T

Chenghao Xu, Guangtao Lyu, Qi Liu, Jiexi Yan

Physical motions are inherently continuous, and higher camera frame rates typically contribute to improved smoothness and temporal coherence. For the first time, we explore continuous representations of human motion sequences, featuring the ability to interpolate, inbetween, and even extrapolate any input motion sequences at arbitrary frame rates. To achieve

Sebastián Saavedra-Pino, Ricardo Quispe-Mendizábal, Gabriel Alvarado Barrios, Enrique Solano

We introduce a novel quantum optimization paradigm: the Fixed-Parameter-Count Quantum Approximate Optimization Algorithm (FPC-QAOA). It is a scalable variational framework that maintains a constant number of trainable parameters regardless of the number of qubits, Hamiltonian complexity, or circuit depth. By separating schedule function optimization from cir

Nikita Moriakov, Efstratios Gavves, Jonathan H. Mason, Carmen Seller-Oria

Cone Beam CT (CBCT) is an important imaging modality nowadays, however lower image quality of CBCT compared to more conventional Computed Tomography (CT) remains a limiting factor in CBCT applications. Deep learning reconstruction methods are a promising alternative to classical analytical and iterative reconstruction methods, but applying such methods to CB

Ming-Xin Li, Jin Pu, Yi Ling, Guo-Ping Li

We establish a direct connection between the interior curvature structure of nonsingular black holes (BHs) with a Minkowski core and their observable optical signatures. By classifying these spacetimes into three fundamental types, Type I (Kretschmann scalar K_max increasing with mass M), Type II (mass-independent K_max), and Type III (K_max decreasing with

Hai-Liang Wu, Hao Pan

In this paper, using some arithmetic properties of Jacobi sums, we investigate some products involving Jacobi sums and reveal the connections between these products and certain cyclotomic matrices. In particular, as an application of our main results, we confirm a conjecture posed by Z.-W. Sun in 2019, and obtain a stronger result.

Chenghao Xu, Qi Liu, Jiexi Yan, Muli Yang

Few-shot image generation aims to effectively adapt a source generative model to a target domain using very few training images. Most existing approaches introduce consistency constraints-typically through instance-level or distribution-level loss functions-to directly align the distribution patterns of source and target domains within their respective laten

V. V. Marchenkov, V. Yu. Irkhin, Yu. A. Perevozchikova

The review treats Heusler alloys that display distinctive functional properties, including shape-memory behavior and magnetocaloric effects. Particular emphasis is placed on Heusler systems in which half-metallic ferromagnetism and spin-gapless semiconductor state are realized. Although these compounds are crystallographically rather "ordinary", peculiaritie

Yogesh Kumar, Vrushank Ahire, M. A. Ganaie

The paper presents novel Universum-enhanced classifiers: the Universum Generalized Eigenvalue Proximal Support Vector Machine (U-GEPSVM) and the Improved U-GEPSVM (IU-GEPSVM) for EEG signal classification. Using the computational efficiency of generalized eigenvalue decomposition and the generalization benefits of Universum learning, the proposed models addr

Hermès Lajoinie-Dodel

We construct a strongly bolic metric for a certain class of relatively hyperbolic groups, which includes those with CAT(0) parabolics and virtually abelian parabolics. If we further assume that the parabolics satisfy (RD), applying a theorem of Lafforgue, we deduce the Baum-Connes conjecture for these groups. One of the key ingredients in our construction is

Tony J. Puthenpurakal, Samarendra Sahoo

Let $A$ be a non Gorenstein Cohen Macaulay ring of dimension $d\geq 1$, $I$ an ideal of $A$, and suppose $\omega_A$ is a canonical $A$-module. Set $$r(I,\omega_A) = \bigcup_{n \geq 0} (I^{n+1} \omega_A : I^{n} \omega_A) \subseteq A .$$ We show that the ideal $r(I,-)$ is $\omega_A$ invariant. Motivated by this property, we introduce a new class of rings, whic

Lei Wang, Darong Lai

Although Graph Neural Networks (GNNs) have become the dominant approach for graph representation learning, their performance on link prediction tasks does not always surpass that of traditional heuristic methods such as Common Neighbors and Jaccard Coefficient. This is mainly because existing GNNs tend to focus on learning local node representations, making

Qizhi Wang

Randomized election timeouts are a simple and effective liveness heuristic for Raft, but they become brittle under long-tail latency, jitter, and partition recovery, where repeated split votes can inflate unavailability. This paper presents BALLAST, a lightweight online adaptation mechanism that replaces static timeout heuristics with contextual bandits. BAL

Jifeng Ge, Bastien Vieublé, Juan Zhang

In this article, we introduce a three-precision formulation of the General Alternating-Direction Implicit method (GADI) designed to accelerate the solution of large-scale sparse linear systems $Ax=b$. GADI is a framework that can represent many existing Alternating-Direction Implicit (ADI) methods. These methods are a class of linear solvers based on a split

Affan Safeer, Oktay Güleryüz, Guangyao Miao, Wouter Jolie

Single-layer transition metal dihalides grown on conducting substrates were shown to host stable polarons. Here, we investigate polarons in insulating single-layer MnBr$_2$ grown by molecular beam epitaxy on three different substrates, namely graphene on Ir(110), graphene on Ir(111), and Au(111). The number densities and species of polarons observed vary str

Yongjun Hou

Fix an integer $n\geq 2$, an exponent $1<p<\infty$, and a domain $\Omega\subseteq\mathbb{R}^{n}$. Let $\Omega^{*}\triangleq\Omega\setminus\{\hat{x}\}$ where $\hat{x}\in\Omega$. Under some further conditions, we construct optimal Hardy-weights for the Finsler $p$-Dirichlet integral $$Q_{0}[\phi;\Omega^{*}]\triangleq\int_{\Omega^{*}}H(x,\nabla \phi)^{p}\,\math

Qi Wu, Zhong-Quan Sun, Dian-Yong Chen, Shi-Dong Liu

In this work, we investigate the dipion transition processes $X(3872)\to \pi \pi \chi_{cJ} (J=0,1,2)$ within the framework of heavy hadron chiral perturbation theory, treating $X(3872)$ as a molecular state composed of $D\bar{D}^*$+ H.c. components. By analyzing the box and triangle loop diagrams with the nonrelativistic effective field theory power-counting

Lingyan Cheng, Caihong Gu, Wei Liu, Fengwu Zhu

By using the weak convergence method, we establish the large and moderate deviation principles for the multivalued McKean-Vlasov SDEs with non-Lipschitz coefficients driven by L\'{e}vy noise in this paper. The Bihari's inequality is used to overcome the challenges arising from the non-Lipschitz conditions on the coefficients.

Yutao Liang, Yan-Xia Ren, Quan Shi, Fan Yang

We study a class of multitype branching L\'evy processes, where particles move according to type-dependent L\'evy processes, switch types via an irreducible Markov chain, and branch according to type-dependent laws. This framework generalizes multitype branching Brownian motions. Using techniques of Markov additive processes, we develop a spine decomposition

Ashish Bawalia, Zdzisław Brzeźniak, Manil T. Mohan, Piotr Rybka

We establish the global well-posedness of the $D(A)-$valued strong solution to a nonlinear heat equation with constraints on a \textit{Poincar\'e domain} $\bO\subset \R^d$ whose boundary is of class $C^2$. Consider the following nonlinear heat equation \begin{align*} \frac{\partial u}{\partial t} - \Delta u + |u|^{p-2}u = 0, \end{align*} projected onto the t

Yangyang Ge, Haoyu Zhou, Wen Zheng, Xiang-Min Yu

Quantum sensing promises measurement precision beyond classical limits, but its practical realization is often hindered by decoherence and the challenges of generating and stabilizing entanglement in large-scale systems. Here, we experimentally demonstrate a scalable, scrambling-enhanced quantum sensing protocol, referred to as butterfly metrology, implement

Kiyoshi Sogo

Many identities written by $P=S=C$ are obtained, where $P$ infinite products, $S$ infinite series, and $C$ continued fractions. Such equality is called {\it triplicity}, and it can be used to compute the values of infinite series. It is applied even to obtain sums of divergent series. Many examples of such infinite series are shown, including $1-2+2^3-2^6+\c

Chen Chen, Daniela Kaufmann, Chenhui Deng, Zhan Song

We present ReVEAL, a graph-learning-based method for reverse engineering of multiplier architectures to improve algebraic circuit verification techniques. Our framework leverages structural graph features and learning-driven inference to identify architecture patterns at scale, enabling robust handling of large optimized multipliers. We demonstrate applicabi

N. Kalntis, G. Kanwar, M. Petschlies, S. Romiti

We present updated results for the hadronic light-by-light (HLbL) contribution to the muon anomalous magnetic moment. The calculations are based on ETMC's $N_f=2+1+1$ Wilson-clover twisted-mass ensembles at the physical point. We perform continuum extrapolations for the strange- and charm-quark connected contributions and report on our results for the light-

Nikita Kalinin, Mikhail Shkolnikov

In this note, we introduce equi-affine invariants by averaging over the space of tropical structures of fixed covolume. Applied to the tropical distance series, this construction produces a family of equi-affine invariant functions associated with convex domains which are expected to satisfy a number of remarkable properties. We conjecture a limiting descrip

Zhe Su, Giacomo Indiveri

In this paper, we present ElfCore, a 28nm digital spiking neural network processor tailored for event-driven sensory signal processing. ElfCore is the first to efficiently integrate: (1) a local online self-supervised learning engine that enables multi-layer temporal learning without labeled inputs; (2) a dynamic structured sparse training engine that suppor

Hannes Rosenbusch

LLM_annotate is a Python package for analyzing the personality of fiction characters with large language models. It standardizes workflows for annotating character behaviors in full texts (e.g., books and movie scripts), inferring character traits, and validating annotation/inference quality via a human-in-the-loop GUI. The package includes functions for tex

Tanmoy Mukherjee, Pierre Marquis, Zied Bouraoui

We present Mode(Multi-Objective adaptive Data Efficiency), a framework that dynamically combines coreset selection strategies based on their evolving contribution to model performance. Unlike static methods, \mode adapts selection criteria to training phases: emphasizing class balance early, diversity during representation learning, and uncertainty at conver

Devesh Saraogi, Rohit Singhee, Dhruv Kumar

The integration of Large Language Models (LLMs) into the scientific ecosystem raises fundamental questions about the creativity and originality of AI-generated research. Recent work has identified ``smart plagiarism'' as a concern in single-step prompting approaches, where models reproduce existing ideas with terminological shifts. This paper investigates wh

Zhuan Ning, Zi-Yan Yuwen, Xiang-Xi Zeng, Rong-Gen Cai

Standard perturbative calculations of scalar-induced gravitational waves (SIGWs) have neglected nonperturbative effects in the large-amplitude regime. We develop a hybrid numerical framework to signify nonperturbative effects on the stochastic gravitational wave (GW) background sourced by primordial curvature perturbations, focusing on the acoustic channel (

Yuk-Kwan Wong, Haixin Liang, Zeyu Ma, Yiwei Chen

Marine visual understanding is essential for monitoring and protecting marine ecosystems, enabling automatic and scalable biological surveys. However, progress is hindered by limited training data and the lack of a systematic task formulation that aligns domain-specific marine challenges with well-defined computer vision tasks, thereby limiting effective mod

Luca De Gennaro Aquino, Sascha Desmettre, Yevhen Havrylenko, Mogens Steffensen

We study a continuous-time portfolio choice problem for an investor whose state-dependent preferences are determined by an exogenous factor that evolves as an It\^o diffusion process. Since risk attitudes at the end of the investment horizon are uncertain, terminal wealth is evaluated under a set of utility functions corresponding to all possible future pref

Florian Schwarz

This paper explores differential bundles in tangent categories, characterizing them as functors from a structure category. This is analogous to the actegory perspective of Garner and Leung, which we also use to describe the tangent categories of Rosick\'y, Cockett and Cruttwell. We generalize the Garner-Leung equivalence between tangent categories and Weil a

Peng Jin, Jiaqi Zhou

In this paper, we study continuous-state interacting multi-type branching processes with immigration (CIMBI processes), where inter-specific interactions -- whether competitive, cooperative, or of a mixed type -- are proportional to the product of their type-population masses. We establish sufficient conditions for the CIMBI process to never hit the boundary

Yuxin Liu, Zeqing Song, Jiong Lou, Chentao Wu

The rapid advancement of large-scale language models (LLMs) has shown their potential to transform intelligent education systems (IESs) through automated teaching and learning support applications. However, current IESs often rely on single-turn static question-answering, which fails to assess learners' cognitive levels, cannot adjust teaching strategies bas

Bekir Baytaş

Bell-network states constitute a class of diffeomorphism-invariant and entangled states of the geometry within loop quantum gravity (LQG) that satisfy an area-law for the entanglement entropy in the limit of large spins. The fluctuations of the geometry for a Bell-network state are entangled, similar to those in the semiclassical limit as described by quantu

Hongjuan Li, Hui Kang, Chenbang Liu, Ruolin Wang

The proliferation of Internet-of-things (IoT) infrastructures and the widespread adoption of traffic encryption present significant challenges, particularly in environments characterized by dynamic traffic patterns, constrained computational capabilities, and strict latency constraints. In this paper, we propose DMLITE, a diffusion model and large language m

Hongxue Liang, Zhihui Liu, Alessandro Montinaro

In this paper, we completely classify the non-trivial 2-(v,k,3) designs admitting an almost simple, flag-transitive automorphism group with socle PSL(2,q).

Jinqiang Wang, Huansheng Ning, Jianguo Ding, Tao Zhu

Proactively predicting a users next utterance in human-machine dialogue can streamline interaction and improve user experience. Existing commercial API-based solutions are subject to privacy concerns while deploying general-purpose LLMs locally remains computationally expensive. As such, training a compact, task-specific LLM provides a practical alternative.

Miguel Moreno, Beatrice Pitton

We study the Borel and analytic subsets of the spaces \({}^{\kappa}\kappa\) and \({}^{\kappa}2\) endowed with ideal topologies, where \(\kappa\) is a regular uncountable cardinal. We establish that the Borel hierarchy does not collapse in any ideal topology and prove that every Borel set in such a topology is analytic. In particular, when the ideal contains

Vaibhav Sharma, Ranjeev Misra, J S Yadav, Akash Garg

We present a comprehensive study of the 2021 outburst of GX 339-4 using AstroSat observations in the hard-intermediate (HIMS) and soft-intermediate states (SIMS). Spectral and timing analyses across these states suggest that during the SIMS, unabsorbed flux (0.1-3 keV), inner disc temperature, and "apparent" inner disc radius do not change, suggesting the st

Qiqi Qiang

Understanding how emotions diffuse through social networks is central to computational social science. Recently, large language models (LLMs) have been increasingly used to simulate social media interactions, raising the question of whether LLM-generated data can realistically reproduce emotion diffusion patterns observed in real online communities. In this

Ankita Sharma, Partha Chakroborty, Pranamesh Chakraborty

This work on gap acceptance is based on the premise that the decision to accept/reject a gap happens in a person's mind and therefore must be based on the perceived gap and not the measured gap. The critical gap must also exist in a person's mind and hence, together with the perceived gap, is a latent variable. Finally, it is also proposed that the critical

Gaoren Lin, Huangxuan Zhao, Yuan Xiong, Lefei Zhang

Text-guided medical segmentation enhances segmentation accuracy by utilizing clinical reports as auxiliary information. However, existing methods typically rely on unaligned image and text encoders, which necessitate complex interaction modules for multimodal fusion. While CLIP provides a pre-aligned multimodal feature space, its direct application to medica

Muhammad Mansur Zubairu, Abdullahi Umar, Fatma Salim Al-Kharousi

In this article, we consider the monoid of all monotone and order-decreasing partial transformations denoted as $\mathcal{DORP}_{n}$ on an $n$ ordered chain $[n]=\{1, \ldots,n\}$, its two-sided ideal $I(n,p)= \{\rho \in \mathcal{DORP}_{n} : \, |Im \, \rho| \leq p\}$ and the Rees quotient ${RQ}_{p}(n)$ of the ideal $I(n,p)$. We compute the order of the monoid

Xiaoyu Mo, Jintian Ge, Zifan Wang, Chen Lv

Multi-agent trajectory generation is a core problem for autonomous driving and intelligent transportation systems. However, efficiently modeling the dynamic interactions between numerous road users and infrastructures in complex scenes remains an open problem. Existing methods typically employ distance-based or fully connected dense graph structures to captu

Francescantonio Oliva, Francesco Petitta, Matheus F. Stapenhorst

We study existence and non-existence of solutions for singular elliptic boundary value problems as \begin{equation}\label{eintro}\begin{cases}\tag{1} \displaystyle -\Delta_p u+ \frac{a(x)}{u^{\gamma}}=\mu f(x) \ &\text{ in }\Omega, \newline u>0&\text{ in }\Omega, \newline u = 0 \ &\text{ on } \partial\Omega, \end{cases} \end{equation} where $\Omega$ is a smo

D. Bonheure, G. P. Galdi, C. Patriarca

We demonstrate existence in the ``large" and uniqueness in the ``small" of equilibrium configurations for the coupled system consisting of a Navier-Stokes fluid interacting with a rigid body subjected to spring forces and restoring moments. The driving mechanism is a uniform, given velocity field of the fluid at large spatial distances from the body. The mai

Karl Friston, Lancelot Da Costa, Alexander Tschantz, Conor Heins

This technical note considers the sampling of outcomes that provide the greatest amount of information about the structure of underlying world models. This generalisation furnishes a principled approach to structure learning under a plausible set of generative models or hypotheses. In active inference, policies - i.e., combinations of actions - are selected

Meike Neuwohner, Vera Traub, Rico Zenklusen

Finding a smallest subgraph that is k-edge-connected, or augmenting a k-edge-connected graph with a smallest subset of given candidate edges to become (k+1)-edge-connected, are among the most fundamental Network Design problems. They are both APX-hard in general graphs. However, this hardness does not carry over to the planar setting, which is not well under

Oliver Normand, Esther Borsi, Mitch Fruin, Lauren E Walker

Large language models (LLMs) often match or exceed clinician-level performance on medical benchmarks, yet very few are evaluated on real clinical data or examined beyond headline metrics. We present, to our knowledge, the first evaluation of an LLM-based medication safety review system on real NHS primary care data, with detailed characterisation of key fail

YuK-Kwan Wong, Tuan-An To, Jipeng Zhang, Ziqiang Zheng

We have witnessed promising progress led by large language models (LLMs) and further vision language models (VLMs) in handling various queries as a general-purpose assistant. VLMs, as a bridge to connect the visual world and language corpus, receive both visual content and various text-only user instructions to generate corresponding responses. Though great

A. Borel, T. V. Ivanova, J. Cervantes-Villanueva, P. Thor

Moir\'e superlattices in transition-metal dichalcogenide semiconductor heterobilayers enable the quantum confinement of interlayer excitons with large out-of-plane permanent electric dipoles and spin-valley control. Here, we report a novel phonon-assisted excitation mechanism of individual moir\'e-trapped interlayer excitons in 2H-stacked MoSe$_2$/WSe$_2$ he

Alex Thornton, Ian Halliday, Harry Saxton, Xu Xu

We make modifications to the unscented Kalman filter (UKF) which bestow almost complete practical identifiability upon a lumped-parameter cardiovascular model with 10 parameters and 4 output observables - a highly non-linear, stiff problem of clinical significance. The modifications overcome the challenging problems of rank deficiency when applying the UKF t

Jingyu Zhu, Daniel W. Apley

A shortcoming of black-box supervised learning models is their lack of interpretability or transparency. To facilitate interpretation, post-hoc global variable importance measures (VIMs) are widely used to assign to each predictor or input variable a numerical score that represents the extent to which that predictor impacts the fitted model's response predic

Ping Li, Wen-Ping Liao, Sheng-Bang Qian, Li-Ying Zhu

$\delta$ Scuti stars in binary or multiple systems serve as crucial probes for studying stellar pulsation and evolution. However, many such systems are not ideal for asteroseismology due to uncertainties in mass transfer with close companions and the challenges of dynamically measuring all components' physical properties. The triple system DG~Leo, comprising

David M T Kuo

We investigate the emergence and topological nature of interface states (IFs) in N-AGNR/$(N-2)$-AGNR/N-AGNR heterostructure (AGNRH) segments lacking translational symmetry, focusing on their relation to the end states (ESs) of the constituent armchair graphene nanoribbon (AGNR) segments. For AGNRs with $R_1$-type unit cells, the ES numbers under a longitudin

Faisal Zaman, Ouns Bouachir, Moayad Aloqaily, Ismaeel Al Ridhawi

Generative Artificial Intelligence (GenAI) and Large Language Models (LLMs) are revolutionizing network management systems, paving the way towards fully autonomous and self-optimizing communication systems. These models enable networks to address complex decision-making tasks across both short-term operational scenarios and long-term strategic planning. Thro

Sichun Luo, Yi Huang, Mukai Li, Shichang Meng

Large language models (LLMs) are increasingly deployed as conversational assistants in open-domain, multi-turn settings, where users often provide incomplete or ambiguous information. However, existing LLM-focused clarification benchmarks primarily assume single-turn interactions or cooperative users, limiting their ability to evaluate clarification behavior

Anouar Bahrouni

This paper establishes the existence of infinitely many solutions for nonlinear problems without any symmetry, achieving three major advances. First, in the setting of semilinear elliptic PDEs, we introduce a refined variational truncation method that yields infinite sequences of positive as well as negative solutions. Second and most notably, we resolve a l

Shi Quan Foo, Chi-Ho Wong, Zhihan Gao, Dit-Yan Yeung

Precipitation nowcasting is a critical spatio-temporal prediction task for society to prevent severe damage owing to extreme weather events. Despite the advances in this field, the complex and stochastic nature of this task still poses challenges to existing approaches. Specifically, deterministic models tend to produce blurry predictions while generative mo

Di Wu, Yifan Hu, Kohei Kamada

The generation of helical magnetic fields and the associated chiral asymmetry via the chiral anomaly is a generic feature in pseudoscalar inflation. In the presence of a Chern--Simons coupling between the inflaton and a U(1) gauge field, the homogeneous evolution of the inflaton induces a tachyonic instability in one circular polarization of the gauge field,

Minyuan Xiao, Yunchun Li, Yuchen Zhao, Tong Guan

Traffic classification on programmable data plane holds great promise for line-rate processing, with methods evolving from per-packet to flow-level analysis for higher accuracy. However, a trade-off between accuracy and efficiency persists. Statistical feature-based methods align with hardware constraints but often exhibit limited accuracy, while online deep

Wenqing Zhang

In this study, we investigate asset price bubbles in a discrete-time, discrete-state market under model uncertainty and short sales prohibitions. Building on a new fundamental theorem of asset pricing and a superhedging duality in this setting, we introduce a notion of bubble based on a novel definition of the fundamental price, and analyze their types and c

Palak Gupta, Sapana Yadav, Ritu Garg

Motivated by the continuous advances in modern experimental facilities, we investigate the radially excited F-wave bottom and bottom-strange mesons that have not yet been observed experimentally. By combining theoretical inputs with available experimental information on charm mesons and applying flavor-symmetry parameters, we predict the masses of the radial

Alexandra Carpentier, Nicolas Verzelen

We consider the problem of ranking $n$ experts according to their abilities, based on the correctness of their answers to $d$ questions. This is modeled by the so-called crowd-sourcing model, where the answer of expert $i$ on question $k$ is modeled by a random entry, parametrized by $M_{i,k}$ which is increasing linearly with the expected quality of the ans

Ahmed M. Hussain, Salahuddin Salahuddin

Current Large Language Models (LLMs) safety approaches focus on explicitly harmful content while overlooking a critical vulnerability: the inability to understand context and recognize user intent. This creates exploitable vulnerabilities that malicious users can systematically leverage to circumvent safety mechanisms. We empirically evaluate multiple state-

Eduard Stefan Dinuta, Iustin Sirbu, Traian Rebedea

Safety for Large Language Models (LLMs) has been an ongoing research focus since their emergence and is even more relevant nowadays with the increasing capacity of those models. Currently, there are several guardrails in place for all public LLMs and multiple proposed datasets for training safety classifiers. However, training these safety classifiers relies

Safal Thapaliya, Zehong Wang, Jiazheng Li, Ziming Li

Graph-structured data exhibit substantial heterogeneity in where their predictive signals originate: in some domains, node-level semantics dominate, while in others, structural patterns play a central role. This structure-semantics heterogeneity implies that no graph learning model with a fixed inductive bias can generalize optimally across diverse graph dom

Nicolai Plintz, Marcus Vetter, Dirk Ifenthaler

Volatile organic compounds (VOCs) represent a novel but underexplored modality for emotion recognition. This paper presents a systematic evidence synthesis and exploratory investigation of VOC-based affective computing using low-cost sensors. Study 1, a systematic scoping review following PRISMA-ScR guidelines, analyzed 16 studies from 610 records across bre

Chao Gong, Dong Li, Yingwei Pan, Jingjing Chen

Text-guided image inpainting endeavors to generate new content within specified regions of images using textual prompts from users. The primary challenge is to accurately align the inpainted areas with the user-provided prompts while maintaining a high degree of visual fidelity. While existing inpainting methods have produced visually convincing results by l

Ashmita Singh, Sheela Verma

In this article, we study sharp bounds for the Neumann eigenvalues of the Laplace operator on graphs. We first establish both lower and upper bounds for the second Neumann eigenvalue on simple graphs, and then derive monotonicity properties of Neumann eigenvalues on trees. In particular, we show that adding a vertex to a tree reduces the corresponding Neuman

Zixiao Huang, Jixiao Yang, Sijia Li, Chi Zhang

This study proposes a unified forecasting framework for high-dimensional multi-task time series to meet the prediction demands of cloud native backend systems operating under highly dynamic loads, coupled metrics, and parallel tasks. The method builds a shared encoding structure to represent diverse monitoring indicators in a unified manner and employs a sta

Carlo Danieli, Valentina Brosco, Claudio Conti, Laura Pilozzi

Controlled and multi-controlled quantum gates, whose action on a target qubit depends on the state of multiple control qubits, represent a fundamental logical building block for complex quantum algorithms. We propose a scheme for realizing this class of gates based on non-Abelian holonomies in modulated photonic waveguide networks. Our approach relies on lin

Dongchao Yang, Zhaoqing Li, Yu Dai, Lili Lang

Spin-orbit torque efficiency is conventionally fixed by bulk materials. $D$-wave altermagnets introduce an additional nonrelativistic spin-charge conversion channel beyond inverse spin-Hall effect. Using prototypical candidate RuO$_2$ as an example, we show that the adjacent ferromagnet alone can dictate both the magnitude and sign of spin-charge conversion.

Jaeseong Lee, Junyeong Ahn, Taewoong Kang, Jaegul Choo

Constructing drivable and photorealistic 3D head avatars has become a central task in AR/XR, enabling immersive and expressive user experiences. With the emergence of high-fidelity and efficient representations such as 3D Gaussians, recent works have pushed toward ultra-detailed head avatars. Existing approaches typically fall into two categories: rule-based

Alexander Guterman, Andrey Yurkov

Let $V$ be a vector space of rectangular $n\times k$ matrices annihilating the Cullis' determinant. We show that $\dim(V) \le (n-1)k$, extending Dieudonn{\'{e}}'s result on the dimension of vector spaces of square matrices annihilating the ordinary determinant. Furthermore, for certain values of $n$ and $k$, we explicitly describe such vector spaces of maxim

Mariam Saeed, Manar Amr, Farida Adel, Nada Hassan

Direct speech-to-image generation has recently shown promising results. However, compared to text-to-image generation, there is still a large gap to enclose. Current approaches use two stages to tackle this task: speech encoding network and image generative adversarial network (GAN). The speech encoding networks in these approaches produce embeddings that do

Yichen Dong, Eugene Demler, Zhiyuan Sun

In Wigner-crystal states of two-dimensional electrons, the spin ordering remains poorly understood. The small energy differences between candidate spin orders make theoretical studies less reliable, and probing magnetic order at a nonzero wave vector is experimentally challenging. In modern realizations of Wigner crystals, the electronic spin degree of freed

Bernat Frangi, Laura Monroy, Aldo Moreno-Oyervides, Oscar E. Bonilla-Manrique

Optical spectroscopy, in particular dual-comb (DC) spectroscopy, is a critical, non-invasive tool for combustion diagnostics, offering high precision and calibration-free advantages. However, its implementation remains challenging, especially in the mid-infrared region. This work presents the development of a robust DC spectroscopic system based on electro-o

Suparna Biswas, Rituparna Sen

Historically, financial risk management has mostly addressed risk factors that arise from the financial environment. Climate risks present a novel and significant challenge for companies and financial markets. Investors aiming for avoidance of firms with high carbon footprints require suitable risk measures and portfolio management strategies. This paper pre

Paul-Hermann Balduf, Erik Panzer

We introduce tropical scalar field theory as a model for renormalizable quantum field theory, and examine in detail the case of quartic self-interaction and internal $O(N)$ symmetry. This model arises in a formally zero-dimensional limit of critical long-range models, but nevertheless its Feynman integrals exhibit strong numerical correlations with the ordin

Daniil Burakov, Ivan Petrov, Dmitrii Khelimskii, Ivan Bessonov

Patient status, angiographic and procedural characteristics encode crucial signals for predicting long-term outcomes after percutaneous coronary intervention (PCI). The aim of the study was to develop a predictive model for assessing the risk of cardiac death based on the real and synthetic data of patients undergoing PCI and to identify the factors that hav

Yucheng Lai, Yongliang Zhang, Kai Chang

Artificial gauge fields open up burgeoning opportunities for wave engineering in different disciplines. So far,previous works have mostly focused on synthesizing spatial gauge fields, where the pseudo-magnetic fields lie at the heart of these phenomena. In this Letter, we generalize the paradigm of gauge field optics to the time domain by using time-varying

Daeyeol Jeon, Yongjae Kwon

The modular curve X_0(N) parametrizes elliptic curves together with a cyclic subgroup of order N, and hence cyclic N-isogenies. While explicit moduli descriptions of X_1(N) are well developed, a comparable construction for X_0(N) has remained incomplete. We give a uniform method for constructing explicit generators of C(X_0(N)), extending an approach of Dowd