December 2025 arXiv papers — page 18

Dakuan Lu, Jiaqi Zhang, Cheng Yuan, Jiawei Shao

Recent advances in large language models (LLMs) have been largely driven by scaling laws for individual models, which predict performance improvements as model parameters and data volume increase. However, the capabilities of any single LLM are inherently bounded. One solution originates from intricate interactions among multiple LLMs, rendering their collec

Subrata Majumdar, Debanjit Mondal

In this work, we address the small-time global controllability properties of a class of fourth-order nonlinear parabolic equations driven by bilinear controls posed on the one-dimensional torus. The controls depend only on time and act through a prescribed family of spatial profiles. Our first result establishes the small-time global approximate controllabil

M. Sadra Heydari, Zafer Kanik, Santiago Montoya-Blandón

We introduce heterogeneous R&D productivities into an endogenous R&D network formation model, generalizing the framework of Goyal and Moraga-Gonz\'alez (2001). Heterogeneous productivities endogenously create asymmetric gains from collaboration: less productive firms benefit disproportionately from links, while more productive firms exert greater R&D effort

Marta Pita-Vidal, Rubén Seoane Souto, Srijit Goswami, Christian Kraglund Andersen

Hybrid semiconductor-superconductor qubits have recently emerged as a promising alternative to traditional platforms, combining material advantages with device-level tunability. A defining feature is their gate-tunable Josephson coupling, enabling superconducting qubit architectures with full electric-field control and offering a path toward scalable, low-cr

Xiu Li

We study visual representation learning from a structural and topological perspective. We begin from a single hypothesis: that visual understanding presupposes a semantic language for vision, in which many perceptual observations correspond to a small number of discrete semantic states. Together with widely assumed premises on transferability and abstraction

Ron F. Del Rosario

We present an openly documented methodology for fine-tuning language models to detect temporal attack patterns in multi-agent AI workflows using OpenTelemetry trace analysis. We curate a dataset of 80,851 examples from 18 public cybersecurity sources and 35,026 synthetic OpenTelemetry traces. We apply iterative QLoRA fine-tuning on resource-constrained ARM64

Xiaoda Xu, Jun Xian

We investigate the expected star discrepancy under a newly designed class of convex equivolume partition models. The main contributions are two-fold. First, we establish a strong partition principle for the star discrepancy, showing that our newly designed partitions yield stratified sampling point sets with lower expected star discrepancy than both classica

Ke Niu, Haiyang Yu, Zhuofan Chen, Zhengtao Yao

Computer-Aided Design (CAD) is essential in industrial design, but the complexity of traditional CAD modeling and workflows presents significant challenges for automating the generation of high-precision, editable CAD models. Existing methods that reconstruct 3D models from sketches often produce non-editable and approximate models that fall short of meeting

Raven Beutner, Bernd Finkbeiner

Hyperproperties are system properties that relate multiple execution traces and occur, e.g., when specifying security and information-flow properties. Checking if a hyperproperty is satisfiable has many important applications, such as testing if some security property is contradictory, or analyzing implications and equivalences between information-flow polic

Weiming Shen, Zhehui Wang, Jiongduo Xie

In this paper, we investigate the asymptotic behaviors of solutions to the singular Yamabe problem with negative constant scalar curvature near singular boundaries and derive optimal estimates, where the background metrics are not assumed to be conformally flat. Specifically, we demonstrate that for a wide class of Lipschitz domains with asymptotic conical s

Hadar Rotschield, Liat Peterfreund

Pattern matching of core GQL, the new ISO standard for querying property graphs, cannot check whether edge values are increasing along a path, as established in recent work. We present a constructive translation that overcomes this limitation by compiling the increasing-edges condition into the input graph. Remarkably, the benefit of this construction goes b

Laurent Boué

This document is a follow-up to our previous paper dedicated to a vectorized derivation of backpropagation in CNNs. Following the same principles and notations already put in place there, we now focus on transformer-based next-token-prediction architectures. To this end, we apply our lightweight index-free methodology to new types of layers such as embedding

Huan-ang Gao, Zikang Zhang, Tianwei Luo, Kaisen Yang

Large Language Model (LLM) agents, while proficient in the digital realm, face a significant gap in physical-world deployment due to the challenge of forming and maintaining a robust spatial mental model. We identify three core cognitive challenges hindering this transition: spatial reasoning, long-horizon state tracking via mental simulation, and active exp

Görkem Giray, Onur Demirörs, Marcos Kalinowski, Daniel Mendez

Context. GenAI tools are being increasingly adopted by practitioners in SE, promising support for several SE activities. Despite increasing adoption, we still lack empirical evidence on how GenAI is used in practice, the benefits it provides, the challenges it introduces, and its broader organizational and societal implications. Objective. This study aims to

Yan-Min Wang, Qing-Yi Liu, Yong-Bo Tang, Lei Wu

The static and dynamic electric dipole polarizabilities of the $5s^2~^1\!S_0$ and $5s5p~^3\!P_{0,2}$ states of Sr atoms are calculated using the relativistic configuration interaction plus the many-body perturbation theory (RCI+MBPT) method. Magic wavelengths are determined for the transitions $5s^2~^1\!S_0\rightarrow 5s5p~^3\!P_{0}$, $5s^2~^1\!S_0\rightarro

Partha Ghose

Recently Szangolies has argued (in the setting of extended Wigner's-friend scenarios) that quantum theory permits ``Rashomon'' situations: multiple internally coherent accounts of events that cannot be combined into a single, consistent global narrative. This note explains why the Rashomon phenomenon can be understood as a \emph{failure of gluing}: local des

Raven Beutner, Bernd Finkbeiner

We study the connection of two problems within the planning and verification community: Conformant planning and model-checking of hyperproperties. Conformant planning is the task of finding a sequential plan that achieves a given objective independent of non-deterministic action effects during the plan's execution. Hyperproperties are system properties that

S. B. Korolev, A. A. Silin

We investigate the generation of squeezed Fock states (SFSs) via particle-number measurements in the modes of multimode Gaussian states. We identify a universal class of $N$-mode Gaussian states for which measuring $N-1$ modes results in the generation of SFSs. The key feature of these states is that the generated SFSs depend only on the total number of dete

Dhruv Nigam

Dereverberation of recorded speech signals is one of the most pertinent problems in speech processing. In the present work, the objective is to understand and implement dereverberation techniques that aim at enhancing the magnitude spectrogram of reverberant speech signals to remove the reverberant effects introduced. An approach to estimate a clean speech s

Pietro d'Avenia, Zhentao He, Chao Ji

In this paper we first establish the theory of a magnetic Sobolev space $H^1_A(\mathcal{G},\mathbb{C})$ on metric graphs $\mathcal{G}$ and we prove the self-adjointness of its corresponding magnetic Schr\"odinger operator. Then, in this setting, we investigate the existence and multiplicity of normalized solutions to nonlinear magnetic Schr\"odinger equation

Junchang Shi, Gang Li

When people listen to music, they often experience rich visual imagery. We aim to externalize this inner imagery by generating images conditioned on music. We propose MESA MIG, a multi agent semantic and emotion aligned framework that first produces structured music captions and then refines them with cooperating agents specializing in scene, motion, style,

Ziqiang Yu, Xiaohui Yu, Yueting Chen, Wei Liu

With the rise of Large Language Models (LLMs), tourists increasingly use it for route planning by entering keywords for attractions, instead of relying on traditional manual map services. LLMs provide generally reasonable suggestions, but often fail to generate optimal plans that account for detailed user requirements, given the vast number of potential POIs

Sheng-Kai Chen, Jie-Yu Chao, Jr-Yu Chang, Po-Lien Wu

Visual Simultaneous Localization and Mapping (vSLAM) systems encounter substantial challenges in dynamic environments where moving objects compromise tracking accuracy and map consistency. This paper introduces PCR-ORB (Point Cloud Refinement ORB), an enhanced ORB-SLAM3 framework that integrates deep learning-based point cloud refinement to mitigate dynamic

Kansei Ushiyama, Shun Sato, Takayasu Matsuo

Designing and analyzing optimization methods via continuous-time models expressed as ordinary differential equations (ODEs) is a promising approach for its intuitiveness and simplicity. A key concern, however, is that the convergence rates of such models can be arbitrarily modified by time rescaling, rendering the task of seeking ODEs with ``fast'' convergen

E. P. Csirmaz, L. Csirmaz

The entropic region is formed by the collection of the Shannon entropies of all subvectors of finitely many jointly distributed discrete random variables. For four or more variables, the structure of the entropic region is mostly unknown. We utilize a variant of the Maximum Entropy Method to obtain five-variable non_shannon entropy inequalities, which delimi

Zuowei Wen, Navid Valizadeh, Timon Rabczuk, Xiaoying Zhuang

Multicomponent vesicles suspended in viscoelastic fluids are crucial for understanding a variety of physiological processes. In this work, we develop a continuum surface force (CSF) phase-field model to investigate the hydrodynamics of inextensible multicomponent vesicles in viscoelastic fluid flows with inertial forces. Our model couples a fluid field compr

Robert Clausecker, Florian Kurpicz, Etienne Palanga

The block tree [Belazzougui et al., J. Comput. Syst. Sci. '21] is a compressed representation of a length-$n$ text that supports access, rank, and select queries while requiring only $O(z\log\frac{n}{z})$ words of space, where $z$ is the number of Lempel-Ziv factors of the text. In other words, its space-requirements are asymptotically similar to those of th

Rashmi Priya, Smarajit Karmakar

Directional memory in amorphous solids is commonly quantified through the Bauschinger effect, yet the observation of the inverse Bauschinger effect suggests that the sign of memory can invert, pointing to distinct underlying plastic organization. Here, we connect directional memory to the nature of yielding in steadily sheared amorphous solids. Using simulat

Sheng-Kai Chen, Yi-Ling Tsai, Chun-Chih Chang, Yan-Chen Chen

Deep neural networks have accelerated inverse-kinematics (IK) inference to the point where low cost manipulators can execute complex trajectories in real time, yet the opaque nature of these models contradicts the transparency and safety requirements emerging in responsible AI regulation. This study proposes an explainability centered workflow that integrate

Huajian Wang, Xiaodian Chen, Shu Wang

Cepheids are fundamental distance indicators, playing a crucial role not only in the cosmic distance ladder but also in mapping the structure, kinematics, and extinction properties of the Milky Way. Using high-precision photometry and parallaxes from $Gaia$ Data Release 3, we identify a significant anti-correlation between the $G$-band extinction coefficient

Abolfazl Younesi, Abbas Shabrang Maryan, Elyas Oustad, Zahra Najafabadi Samani

Deploying large language models (LLMs) on edge devices is challenging due to their limited memory and power resources. Cloud-only inference reduces device burden but introduces high latency and cost. Static edge-cloud partitions optimize a single metric and struggle when bandwidth fluctuates. We propose Splitwise, a novel Lyapunov-assisted deep reinforcement

Chang Liu, Dejun Luo

We study nonlinear wave equations perturbed by transport noise acting either on the displacement or on the velocity. Such noise models random advection and, under suitable scaling of space covariance, may generate an effective dissipative term. We establish well-posedness in both cases and analyse the associated scaling limits. When the noise acts on the dis

Jyotishka Datta, Nicholas G. Polson, Vadim Sokolov, Daniel Zantedeschi

Conformal prediction (CP) is widely presented as distribution-free predictive inference with finite-sample marginal coverage under exchangeability. We argue that CP is best understood as a rank-calibrated descendant of the Fisher-Dempster-Hill fiducial/direct-probability tradition rather than as Bayesian conditioning in disguise. We establish four separation

Jiawei Liu, Zhuo Chen, Rui Zhu, Miaokun Chen

Neural ranking models have achieved remarkable progress and are now widely deployed in real-world applications such as Retrieval-Augmented Generation (RAG). However, like other neural architectures, they remain vulnerable to adversarial manipulations: subtle character-, word-, or phrase-level perturbations can poison retrieval results and artificially promot

Yu Jia, Wen-Long Sang, Xiaonu Xiong, Jian Zhou

Two-photon collision in ultraperipheral heavy-ion collisions (UPCs) provides a unique and powerful platform for probing QCD with linearly polarized quasi-real photons. While photon polarization effects have been recognized in dilepton and even in light hadrons production, their consequences for heavy quarkonium production remain unexplored. In this work we i

Yongbin Du, Xiangdong Zhang

We compute static ($\omega\to0$) tilde Love numbers for scalar ($s=0$) and Dirac ($s=1/2$) perturbations of static acoustic black holes (ABHs) in (3+1) and (2+1) dimensions respectively. By imposing horizon regularity condition and matching to the large-radius expansion, we extract the ratio between decaying and growing modes. It turns out that in (3+1) dime

Md. Sazzadul Islam Prottasha, Nabil Walid Rafi

Multimodal Large Language Models (LLMs) introduce an emerging paradigm for medical imaging by interpreting scans through the lens of extensive clinical knowledge, offering a transformative approach to disease classification. This study presents a critical comparison between two fundamentally different AI architectures: the specialized open-source agent MedGe

Bogdan Dumitru, Mihai Prunescu

A celebrated but non-effective theorem of Tibor Gallai states that for any finite set $A$ of $\Z^n$ and for any finite number of colors $c$ there is a minimal $m$ such that no coloring of the finite $m^n$-grid can avoid that a homothetic image of $A$ is monochromatic. We find (or confirm) $m$ for equilateral triangles, squares, and various types of rectangle

Anne-Lise Marais, Victoria Dumont, Marie Anquetil, Arnaud Mortier

Sensory prediction (SP) is a fundamental mechanism of perception that supports cognitive development. Atypical SP has been reported across multiple neurodevelopmental disorders (ND), suggesting it may constitute an early cross-syndromic marker. Premature birth is a major risk factor for ND, with risk increasing as gestational age (GA) at birth decreases. How

Minjiang Huang, Jipeng Qiang, Yi Zhu, Chaowei Zhang

Audiobook interpretations are attracting increasing attention, as they provide accessible and in-depth analyses of books that offer readers practical insights and intellectual inspiration. However, their manual creation process remains time-consuming and resource-intensive. To address this challenge, we propose AI4Reading, a multi-agent collaboration system

Ole Steuernagel, Ray-Kuang Lee

If the phase space-based Glauber-Sudarshan distribution, $P_{\rho}$, has negative values the quantum state,~$\rho$, it describes is nonclassical. Due to $P$'s singular behaviour this simple criterion is impractical to use. Recent work [Bohmann and Agudelo, Phys. Rev. Lett. 124, 133601 (2020)] presented a general, sensitive, and noise-tolerant certification f

Anbang Song, Ziqiang Yu, Wei Liu, Yating Xu

The Reverse $k$-Nearest Neighbor (R$k$NN) query over moving objects on road networks seeks to find all moving objects that consider the specified query point as one of their $k$ nearest neighbors. In location based services, many users probably submit R$k$NN queries simultaneously. However, existing methods largely overlook how to efficiently process multipl

Khaled Elbassioni

Given a polygon $H$ in the plane, the art gallery problem calls for fining the smallest set of points in $H$ from which every other point in $H$ is seen. We give a deterministic algorithm that, given any polygon $H$ with $h$ holes, $n$ rational veritces of maximum bit-length $L$, and a parameter $\delta \in(0,1)$, is guaranteed to find a set of points in $H$

Théo Boivin, Olivier Gillia

An analysis of the general concept of volume variation partition of a porous body is presented, introducing the breathing coefficient, defined as the ratio of two volume variations. Considering a total volume of a porous body, composed of solid volume and ``void'' volume, this ratio can be used to evaluate the distribution of a volume variation into both oth

Yuchen Xie, Honghang Chi, Haopeng Quan, Yahui Wang

Physics-Informed Neural Networks with hard constraints (HC-PINNs) are increasingly favored for their ability to strictly enforce boundary conditions via a trial function ansatz $\tilde{u} = A + B \cdot N$, yet the theoretical mechanisms governing their training dynamics have remained unexplored. Unlike soft-constrained formulations where boundary terms act a

Toshizumi Fukui, Saiki Hoshino

We introduce the notion of curvature parameters for singular plane curves with finite multiplicities and define the notion of curvatures for them. We then provide criteria to determine their singularity types for A-simple singularities. As an application, we investigate singularity types of their parallel curves.

Arman Martirosyan, Shahane Tigranyan, Maria Razzhivina, Artak Aslanyan

Micro-gesture recognition and behavior-based emotion prediction are both highly challenging tasks that require modeling subtle, fine-grained human behaviors, primarily leveraging video and skeletal pose data. In this work, we present two multimodal frameworks designed to tackle both problems on the iMiGUE dataset. For micro-gesture classification, we explore

Zhuying Wang, Shuikang Yu, Xingkai Cheng, Xiaoyu Xiao

Altermagnetism simultaneously possesses nonrelativistic spin responses and zero net magnetization, thus combining advantages of ferromagnetism and antiferromagnetism. This superiority originates from its unique dual feature, i.e., opposite-magnetic sublattices in real space and alternating spin polarization in momentum space enforced by the same crystal symm

Jiacheng Ding, Cong Guo, Xiaofei Zhang

With the proliferation of temporal graph data, there is a growing demand for analyzing information propagation patterns during graph evolution. Existing graph analysis systems, mostly based on static snapshots, struggle to effectively capture information flows along the temporal dimension. To address this challenge, we introduce ChronoConnect, a novel system

Jiagang Ren, Hua Zhang

Under nondegeneracy assumptions on the diffusion coefficients, we establish the derivative formulae of Bismut-Elworthy-Li's type for forward-backward stochastic differential equations with respect to Poisson random measure using the lent particle method created by Bouleau and Denis, which is not given before. Applying this formula, the existence and uniquene

Amiran Gogatishvili, Julio S. Neves, Luboš Pick, Hana Turčinová

We obtain an explicit characterization of the $K$-functional of a pair of weighted classical Lorentz spaces of type $S$. We develop a method for obtaining such characterization based on a relation between the desired quantity and the $K$-functional of a specific couple of spaces of type $\Lambda$, which are substantially more manageable than their companions

Stefan Le Coz, Boris Shakarov

In this work, we study the dimensional reduction of stationary states in the shrinking limit for a broad class of two-dimensional domains, called open books, to their counterparts on metric graphs. An open book is a two-dimensional structure formed by rectangular domains sharing common boundaries. We first develop a functional-analytic framework suited to va

Persi Diaconis, Andrew Lin, Arun Ram

We show how the tools of modern algebraic combinatorics -- representation theory, Murphy elements, and particularly Schur--Weyl duality -- can be used to give an explicit orthonormal basis of eigenfunctions for a "curiously slowly mixing Markov chain" on the space of binary $n$-tuples. The basis is used to give sharp rates of convergence to stationarity.

Mahdi Kchaou, Francesco Contino, Diederik Coppitters

Given the central role of green e-molecule imports in the European energy transition, many studies optimize import pathways and identify a single cost-optimal solution. However, cost optimality is fragile, as real-world implementation depends on regulatory, spatial, and stakeholder constraints that are difficult to represent in optimization models and can re

Yang Yu, Guan-Sen Wang, Bo Zhang, Tian-Peng Tang

Traditional direct detection experiments lack the sensitivity to probe the sub-GeV dark matter (DM), primarily due to the low energy of the expected nuclear recoils. In this work, we investigate cosmic-ray (CR) upscattering as a mechanism to accelerate DM particles to detectable velocities in underground experiments. By analyzing four models of DM-nucleon in

Riccardo Bonalli, Dario Prandi

Motivated by some recent studies of the magnetic Laplacian on Riemannian manifolds, we focus on the first eigenvalue of the magnetic horizontal Laplacian on contact manifolds. We characterize conditions for positive spectral shift, and provide some sharp upper bounds. In the Riemannian setting, a genus 1 assumption is known to force the underlying metric to

Jiahao Zhu, Jipeng Qiang, Ran Bai, Chenyu Liu

E-commerce live streaming in China, particularly on platforms like Douyin, has become a major sales channel, but hosts often use morphs to evade scrutiny and engage in false advertising. This study introduces the Live Auditory Morph Resolution (LiveAMR) task to detect such violations. Unlike previous morph research focused on text-based evasion in social med

Ryan Shamim

Modern AI inference systems treat transformer execution as mandatory, conflating model capability with execution necessity. We reframe inference as a control-plane decision problem: determining when execution is necessary versus when correctness can be preserved through alternative pathways. We introduce Meaning-First Execution (MFEE), a control-plane archit

Hang Yang, Daiqin Su

Ultralight bosons are compelling dark-matter candidates. Both scalar and vector bosons can be produced through black hole superradiance, forming a boson cloud surrounding a rotating black hole. Self-interaction of bosons, together with transition mixing in binary black hole systems, give rise to dynamical phenomena that could be potentially observable with f

Zengwei Yao, Wei Kang, Han Zhu, Liyong Guo

Existing dominant methods for audio generation include Generative Adversarial Networks (GANs) and diffusion-based methods like Flow Matching. GANs suffer from slow convergence during training, while diffusion methods require multi-step inference that introduces considerable computational overhead. In this work, we introduce Flow2GAN, a two-stage framework th

Shuikang Yu, Junze Deng, Wenhao Liu, Yunmei Zhang

Topologically protected edge channels show prospects for quantum devices. They have been found experimentally in two-dimensional (2D) quantum spin Hall insulators (QSHIs), weak topological insulators and higher-order topological insulators (HOTIs), but the number of materials realizing these topologies is still quite limited. Here, we provide evidence for to

Taichi Miyagawa, Junki Tanaka

The quasi-free $(p,p\alpha)$ reaction is a powerful tool to probe preformed $\alpha$ clusters in nuclei, but it requires accurate reconstruction of both momentum and scattering angles at the reaction point. In this work, ion-optical analysis for $(p,p\alpha)$ measurements with the Grand Raiden spectrometer is presented. An under-focus optical setting was ado

Soonki Hong, Sanghoon Kwon

We introduce the \emph{chamber zeta function} for a complex of groups, defined via an Euler product over primitive tailless chamber galleries, extending the Ihara--Bass framework from weighted graphs to higher-rank settings. Let $\mathcal{B}$ be the Bruhat--Tits building of $\mathrm{PGL}_{3}(F)$ for a non-archimedean local field $F$ with residue field $\math

F Degret, Sylvain Lespinats, N Guillet, M Alias

Two different non-destructive techniques of characterization were coupled to study the mechanical behavior of materials inside a battery during operation: measurement of the deformation of a battery casing by strain gauge and acoustic emission due to the release of mechanical stress inside the battery materials. Experiments were conducted on a commercial Ni-

Eric Gao

I study multidimensional sequential screening. A monopolist contracts with a buyer who privately observes information about the distribution of their eventual valuations for multiple goods. After initial private information is reported and the contract is signed, the buyer learns and reports realized valuations. In these settings, the monopolist frontloads s

Xu Lin, Jinlong Peng, Zhenye Gan, Jiawen Zhu

Existing Real-Time Object Detection (RTOD) methods commonly adopt YOLO-like architectures for their favorable trade-off between accuracy and speed. However, these models rely on static dense computation that applies uniform processing to all inputs, misallocating representational capacity and computational resources such as over-allocating on trivial scenes

Jun Wang, Rui Li, Yi Li, Kai-Ya Zhang

The energy-transfer efficiency of the natural photosynthesis system seems to be perfectly optimized during the evolution for millions of years. However, how to enhance the efficiency in the artificial light-harvesting systems is still unclear. In this paper, we investigate the energy-transfer process in the photosystem I (PSI). When there is no effective cou

Majid Darehmiraki

Diffusion models have recently achieved remarkable success in generative modeling, yet they are commonly formulated as black-box stochastic systems with limited interpretability and few structural guarantees. In this paper, we establish a control-theoretic foundation for diffusion models by embedding them within the port--Hamiltonian (PH) systems framework.

Takahiko Nobukawa

We present a linear $q$-difference equation of rank $3$, which admits the affine Weyl group symmetry of type $E_8^{(1)}$. We further compare this equation with Moriyama-Yamada's quantum curve which has $W(E_8^{(1)})$-symmetry. The symmetry of our equation is provided by the $q$-middle convolution, defined by Sakai-Yamaguchi and reformulated by Arai-Takemura.

Kotaro Hisa, Yukihiro Seki

We discuss the H\'{e}non parabolic equation $\partial_t u = \Delta u + |x|^\sigma u^p$ in a finite ball in $\mathbb{R}^N$ under the Dirichlet boundary condition, where $N\ge1$, $p>1$, and $\sigma>0$. We assume that the exponent $p$ is supercritical in the Sobolev sense. Since the spatial potential term $|x|^\sigma$ vanishes at the origin, solutions seem less

Ashutosh Krishna Amaram, Aaditya Roy, Raghavan Ranganathan

The recent synthesis of Goldene, a 2D sheet of gold exfoliated from $Ti_3AuC_2$, offers high specific surface area (~260 $m^2g^{-1}$), roughly twice that of fine nanodots (~100 $m^2g^{-1}$), and unique electronic properties due to its dense d-orbital. In this work, we investigate the adsorption of single atom catalyst (SAC) of hydrogen atom on pristine golde

Baptiste Bergeot, Christophe Vergez

This paper investigates the dynamic behavior of a simplified single reed instrument model subject to a stochastic forcing of white noise type when one of its bifurcation parameters (the dimensionless blowing pressure) increases linearly over time and crosses the Hopf bifurcation point of its trivial equilibrium position. The stochastic slow dynamics of the m

Yijian Zhang

The (negative) gradient vector fields of Morse functions on a compact manifold provide an important example in dynamical system. In this note we prove two important properties of this kind of vector field: Connectedness of critical points through orbits and exponential shrinkage of the flow on stable submanifolds. We also find applications in showing some va

Lin Han, Zhang Jujia, Wang Xiaofeng, Hu Maokai

We present optical-ultraviolet photometry and optical spectra for the type II supernova (SN) 2022acko. The spectroscopic observations span phases from $\sim$ 1.5 to $\sim$ 60 days after the explosion, while the light curve was observed up to $\sim$ 300 days. The V-band peak is $-15.5 \pm 0.3$ mag, suggesting that SN 2022acko is a low-luminosity SN II (LLSN).

Elie Aïdékon, Yueyun Hu

Attach to each edge of the complete graph on $n$ vertices, i.i.d. exponential random variables with mean $n$. Aldous [1] proved that the longest path with average weight below $p$ undergoes a phase transition at $p=\frac{1}{e}$: it is $o(n)$ when $p<\frac{1}{e}$ and of order $n$ if $p>\frac1e$. Later, Ding [4] revealed a finer phase transition around $\frac{

Alexander Korotin, Gudmund Pammer

This paper studies the inverse problem of flow matching (FM) between distributions with finite exponential moment, a problem motivated by modern generative AI applications such as the distillation of flow matching models. Uniqueness of the solution is established in two cases - the one-dimensional setting and the Gaussian case. The general multidimensional p

Mokhtar Ben Henda

Standards are adopted in a wide range of fields, both technical and industrial, as well as socio-economic, cultural and linguistic. They are presented explicitly as laws and regulations, technical and industrial standards or implicitly in the form of unwritten social standards. However, in a globalization marked by a very fine mosaic of socio-cultural identi

Wanru Ma, Ye Yang, Zuowei Liang, Ping Wu

Two-dimensional (2D) materials provide unique opportunities to realize emergent phenomena by reducing dimensionality. Using scanning tunneling microscopy combined with first-principles calculations, we determine an intriguing case of a metal-insulator transition (MIT) in a bulk compound, (TBA)$_{0.3}$VSe$_2$. Atomic-scale imaging reveals that the initial $4a

Alexanne Worm, Florian Marchal, Sylvain Castagnos

Lack of data is a recurring problem in Artificial Intelligence, as it is essential for training and validating models. This is particularly true in the field of cultural heritage, where the number of open datasets is relatively limited and where the data collected does not always allow for holistic modeling of visitors' experience due to the fact that data a

Hui Fang, Pingping Gui, Yanping Zhou

In this article, we study the stability and large time behavior for an multi-dimensional incompressible magnetohydrodynamical system with a velocity damping term, for small perturbations near a steady-state of magnetic field fulfilling the Diophantine condition. Our results mathematically characterize the background magnetic field exerts the stabilizing effe

Tao Li, Peilin Li, Kui Lu, Yilei Wang

The adverse drug reactions (ADRs) predicted based on the biased records in FAERS (U.S. Food and Drug Administration Adverse Event Reporting System) may mislead diagnosis online. Generally, such problems are solved by optimizing reporting odds ratio (ROR) or proportional reporting ratio (PRR). However, these methods that rely on statistical methods cannot eli

Chien-Hsu Chen, Huan Niu, Hung-Kai Yu, Tsung Te Lin

Graphene, a two-dimensional monolayer of sp2-bonded carbon atoms in a honeycomb lattice, possesses exceptional electronic, mechanical, and quantum properties, making it highly attractive for energy storage, spintronics, and microelectronics. Functionalizing graphene with platinum (Pt) adatoms can further enhance its properties, particularly for hydrogen stor

Dianyun Wang, Qingsen Ma, Yuhu Shang, Zhifeng Lu

Safety alignment -- training large language models (LLMs) to refuse harmful requests while remaining helpful -- is critical for responsible deployment. Prior work established that safety behaviors are governed by low-rank structures, suggesting parameter-efficient fine-tuning (PEFT) should be well-suited for alignment. However, Low-Rank Adaptation (LoRA) con

Athanase Papadopoulos

Vincenzo Galilei and Constantijn Huygens were both humanists and eminent musicians, the former from the late Renaissance and the latter from the early Modern era. Their respective sons, Galileo and Christiaan, were scientists whose importance cannot be overestimated. My aim in this chapter is to set the scene for a parallel presentation of the legacy of the

Tong Shao, Yusen Fu, Guoying Sun, Jingde Kong

Although Diffusion Transformer (DiT) has emerged as a predominant architecture for image and video generation, its iterative denoising process results in slow inference, which hinders broader applicability and development. Caching-based methods achieve training-free acceleration, while suffering from considerable computational error. Existing methods typical

Socratis Gkelios, Savvas D. Apostolidis, Pavlos Ch. Kapoutsis, Elias B. Kosmatopoulos

Unmanned Aerial Vehicles (UAVs) have revolutionized inspection tasks by offering a safer, more efficient, and flexible alternative to traditional methods. However, battery limitations often constrain their effectiveness, necessitating the development of optimized flight paths and data collection techniques. While existing approaches like coverage path planni

Stéphane Mottin, Żaneta Świątkowska-Warkocka, Marta Wolny-Marszałek, Tatiana E Itina

The interplay between laser parameters and liquid environments dictates the outcome of femtosecond laser-induced nanoparticle modification. We present a study of gold and iron oxide nanoparticles in water and a water-acetone mixture, irradiated with femtosecond lasers at 808 nm and 404 nm. While aggregation was observed in pure water at both wavelengths, the

Masaya Takabe, Hiroshi Watanabe, Sujun Hong, Tomohiro Ikai

Image representation is a fundamental task in computer vision. Recently, Gaussian Splatting has emerged as an efficient representation framework, and its extension to 2D image representation enables lightweight, yet expressive modeling of visual content. While recent 2D Gaussian Splatting (2DGS) approaches provide compact storage and real-time decoding, they

Naofumi Matsuyama, So Yokomori, Toshihiro Nomura, Yuto Ishii

The Pomeranchuk effect is a counterintuitive phenomenon where liquid helium-3 (3He) solidifies under specific pressures, not when cooled, but when heated. This behaviour originates from the magnetic entropy of nuclear spins, suggesting a magnetic field should influence it. However, its detailed response to magnetic fields remains elusive due to the small nuc

Yunfei Gao, Aolin Li, Zesen Fu, Bei Zhang

Altermagnets demonstrate significant potential in spintronics due to their unique non-relativistic spin-splitting properties, yet altermagnetic devices still face challenges in efficiently switching logic states. Here, we report electrostatically controllable spin-momentum locking in bilayer Cr$_{2}$SeO and design a dual-gate altermagnetic tunnel junction (A

Yuri Sato, Mukul Bhattacharya, Jose Carpio, Jewel Capili

Tidal disruption events (TDEs) occur when a star is gravitationally disrupted by the tidal field of a supermassive black hole during a close encounter. Radio emission has recently been detected in TDEs and is commonly attributed to synchrotron radiation from both wind and jetted outflows. However, several TDEs exhibit bright radio flares at late times, which

Yinbu Wang, Yong Xu

This paper presents a test for wide-sense stationarity (WSS) based on the geometry of the covariance function. We estimate local patches of the covariance surface and then check whether the directional derivative in the $(1,1,0)$ direction is zero on each patch. The method only requires the covariance function to be locally smooth and does not assume station

Dominik Wagner, Ankit Kanwar, Luke Ong

In safety-critical domains, reinforcement learning (RL) agents must often satisfy strict, zero-cost safety constraints while accomplishing tasks. Existing model-free methods frequently either fail to achieve near-zero safety violations or become overly conservative. We introduce Safety-Biased Trust Region Policy Optimisation (SB-TRPO), a principled algorithm

Shaoxin Wang, Ziyun Ma

Estimating covariance matrices with high-dimensional complex data presents significant challenges, particularly concerning positive definiteness, sparsity, and numerical stability. Existing robust sparse estimators often fail to guarantee positive definiteness in finite samples, while subsequent positive-definite correction can degrade sparsity and lack expl

Hidetoshi Masai

We generalize the horofunction compactification to maps that are not distance functions. As an application we define a horofunction counterpart to the Teichm\"uller distance, and discuss its properties.

Jing-Yi-Ran Jin, Shuang-Quan Ma, Qing Ai

Quantum phase transitions (QPTs) in coherent Ising machines (CIMs) are studied via a spectral mapping between the one-dimensional XY spin model and a network of degenerate optical parametric oscillators (DOPOs). This exact correspondence reveals that the DOPO network faithfully reproduces the quantum critical behavior of the XY model across its anisotropic,

B. I. Min, J. -S. Kang

H2O is a unique substance with exceptional thermal properties arising from the subtle interplay between its electronic, phononic, and structural degrees of freedom. Of particular interest in H2O are the negative thermal expansion (NTE) phenomena, observed in its solid phase (ice) at low temperature, and in its liquid phase (water) near the freezing temperatu

Ziwei Wan, Zhen Gao, Fabien Heliot, Qu Luo

This paper integrates the emerging ultra-massive multiple-input multiple-output (UM-MIMO) technique with orthogonal chirp division multiplexing (OCDM) waveform to tackle the challenging near-field integrated sensing and communication (ISAC) problem. Specifically, we conceive a comprehensive ISAC architecture, where an UM-MIMO base station adopts OCDM wavefor

Shin Seong Kim, Minjung Shin, Hyunin Cho, Youngjung Uh

Recent text-to-image diffusion models have significantly improved visual quality and text alignment. However, generating a sequence of images while preserving consistent character identity across diverse scenes remains challenging. Existing methods often face a trade-off between maintaining identity consistency and per-image prompt alignment. In this paper,

Xingwei Ma, Shiyang Feng, Bo Zhang, Bin Wang

Remote sensing change detection (RSCD), a complex multi-image inference task, traditionally uses pixel-based operators or encoder-decoder networks that inadequately capture high-level semantics and are vulnerable to non-semantic perturbations. Although recent multimodal and vision-language model (VLM)-based approaches enhance semantic understanding of change