November 2025 arXiv papers — page 51

Jawaria Maqbool, M. Imran Cheema

Multimode fiber~(MMF) imaging using deep learning has high potential to produce compact, minimally invasive endoscopic systems. Nevertheless, it relies on large, diverse real-world medical data, whose availability is limited by privacy concerns and practical challenges. Although data augmentation has been extensively studied in various other deep learning ta

Fangda Chen, Jintao Tang, Pancheng Wang, Ting Wang

The Segment Anything Model (SAM) has recently demonstrated significant potential in medical image segmentation. Although SAM is primarily trained on 2D images, attempts have been made to apply it to 3D medical image segmentation. However, the pseudo 3D processing used to adapt SAM results in spatial feature loss, limiting its performance. Additionally, most

Davide Picca

This paper proposes a novel semiotic framework for analyzing Large Language Models (LLMs), conceptualizing them as stochastic semiotic engines whose outputs demand active, asymmetric human interpretation. We formalize the trade-off between expressive richness (semiotic breadth) and interpretive stability (decipherability) using information-theoretic tools. B

Anis Ahmed, Arefin Ahamed Shuvo, Naruttam Kumar Roy, Neloy Prosad Bishnu

This paper investigates the impact of COVID-19 on the power sector in Bangladesh, how the country has dealt with it, and explores the path to stability. The study employs data visualisation and complex statistics to examine critical data about power systems in Bangladesh. This includes load patterns on a daily, monthly, annual, weekend, and weekday basis. Si

Amin Hosseini

Let T be a unital triangular algebra, let n > 1 be an integer, let gamma be an invertible element of Z(T), the center of T, and let Psi, Omega:\mathcal{T}\rightarrow \mathcal{T}$ be additive mappings satisfying \begin{align*} \Psi(X^n) = \gamma X^{n - 1}\Omega(X) = \gamma \Omega(X) X^{n - 1}\end{align*} for all $X \in \mathcal{T}$. If $\Omega(\textbf{1}) \in

Jannik Olbrich, Enno Ohlebusch

Modern genomic analyses increasingly rely on pangenomes, that is, representations of the genome of entire populations. The simplest representation of a pangenome is a set of individual genome sequences. Compared to e.g. sequence graphs, this has the advantage that efficient exact search via indexes based on the Burrows-Wheeler Transform (BWT) is possible, th

Axel Petzold, Joachim Pum, David P Crabb

Biomarkers are critical tools in the diagnosis and monitoring of neurodegenerative diseases. Reliable quantification depends on assay validity, especially the demonstration of parallelism between diluted biological samples and the assay's standard curve. Inadequate parallelism can lead to biased concentration estimates, jeopardizing both clinical and researc

Timur Mamedov, Anton Konushin, Vadim Konushin

Generalizable person re-identification (Re-ID) aims to recognize individuals across unseen cameras and environments. While existing methods rely heavily on limited labeled multi-camera data, we propose DynaMix, a novel method that effectively combines manually labeled multi-camera and large-scale pseudo-labeled single-camera data. Unlike prior works, DynaMix

Xiangyu Chang, Manyi Yao, Srikanth V. Krishnamurthy, Christian R. Shelton

In Asynchronous Federated Learning (AFL), the central server immediately updates the global model with each arriving client's contribution. As a result, clients perform their local training on different model versions, causing information staleness (delay). In federated environments with non-IID local data distributions, this asynchronous pattern amplifies t

Zacchary Sadeddine, Winston Maxwell, Gaël Varoquaux, Fabian M. Suchanek

Large Language Models (LLMs) may one day replace search engines as the primary portal to information on the Web. In this article, we investigate the societal challenges that such a change could bring. We focus on the roles of LLM Providers, Content Creators, and End Users, and identify 15 types of challenges. With each, we show current mitigation strategies

Bernardo Gonçalves

Considering that Turing's original test was co-opted by Weizenbaum and that six of the most common criticisms of the Turing test are unfair to both Turing's argument and the historical development of AI.

Taimin Miao, Yu Xu, Bo Liang, Wenpei Zhu

Angle-resolved photoemission spectroscopy (ARPES) directly probes the energy and momentum of electrons in quantum materials, but conventional setups capture only a small fraction of the full 2$\pi$ solid angle. This limitation is acute in laser-based ARPES, where the low photon energy restricts momentum space despite ultrahigh resolution. Here we present sys

Hayami Takahashi, Kensuke Takahashi

In expressing emotions, as an expression form separate from natural language, we propose an alternative form that complements natural language, acting as a proxy or window for emotional states. First, we set up an expression form "Effect of Contradictory Structure." "Effect of Contradictory Structure" is not static but dynamic. Effect in "Effect of Contradic

Qiyang Yu, Yu Fang, Tianrui Li, Xuemei Cao

Prompt-free image segmentation aims to generate accurate masks without manual guidance. Typical pre-trained models, notably Segmentation Anything Model (SAM), generate prompts directly at a single granularity level. However, this approach has two limitations: (1) Localizability, lacking mechanisms for autonomous region localization; (2) Scalability, limited

Bin Hu, Liyan Luo, Kaiyuan Wang, Lei Wu

Improving the efficiency of the direct simulation Monte Carlo (DSMC) method has become increasingly urgent with the rapid development of space exploration. To address this issue, the direct intermittent general synthetic iteration (DIG) scheme has recently been proposed to enable DSMC's rapid and accurate convergence to steady-state solutions, even when the

Amir Omranpour, Lea Kämmerer, Catalina Leiva-Leroy, Anna Rabe

In the present work, we investigate oxygen vacancies (V$_\mathrm{O}$) in Co$_3$O$_4$, both in the bulk phase and under liquid-phase ethylene glycol oxidation, by combining theoretical and experimental techniques. Density functional theory calculations for bulk Co$_3$O$_4$ show that introducing an oxygen vacancy reduces two adjacent Co$^{3+}$ ions to Co$^{2+}

Pei Liu, Terry Zhuo, Jiawei Deng, Thong James

Recent advancements in artificial intelligence (AI) and its widespread integration into mobile software applications have received significant attention, highlighting the growing prominence of AI capabilities in modern software systems. However, the inherent hallucination and reliability issues of AI continue to raise persistent concerns. Consequently, appli

Han Luo, Xinyue Wang, Xin Zhou, Longfei Sun

Conventional $J_c$-enhancement methods like doping and irradiation often introduce extrinsic elements or defects, altering intrinsic properties. Here, we report a significant $J_c$ enhancement in FeSe single crystals through compressive strain applied using a glass-fiber-reinforced plastic substrate with anisotropic thermal contraction during cooling. Under

Hai Wu, Shuai Tang, Jiale Wang, Longkun Zou

Perception of Low-Altitude Aircraft (LAA) in 3D space enables precise 3D object localization and behavior understanding. However, datasets tailored for 3D LAA perception remain scarce. To address this gap, we present LAA3D, a large-scale dataset designed to advance 3D detection and tracking of low-altitude aerial vehicles. LAA3D contains 15,000 real images a

Luigi Marra, Onofrio Semeraro, Lionel Mathelin, Andrea Meilán-Vila

This work presents a scalable control framework based on nonlinear Model Predictive Control for high-dimensional dynamical systems. The proposed approach addresses the key challenges of model scalability and partial observability by integrating data-driven reduced order modelling, control in a latent space, and state estimation within a unified formulation.

Xinda Zheng, Canchen Jiang, Hao Wang

The growing demand for electric vehicle (EV) charging infrastructure presents significant planning challenges, requiring efficient strategies for investment and operation to deliver cost-effective charging services. However, the potential benefits of EV charging assignment, particularly in response to varying spatial-temporal patterns of charging demand, rem

Yue Sun, Yuling Xiang, Zhixiang Shi, Tsuyoshi Tamegai

The depairing limit and the vortex-free state in a superconductor is crucial for both the study of supercurrent related physics and the application eliminating noise linked to vortex motion. In this work, we report the evidence of depairing limit and the vortex-free state achieved by geometric constraint in FeSe superconductors. A series of narrow bridges wi

Simon Bekemeier, Moritz Blum, Luana Caron, Alisa Chirkova

Refrigeration based on the magnetocaloric effect (MCE) can contribute to energysaving, environmentally friendly cooling in private households, or industrial application. The cooling is based on the reversible heat release or uptake during a phase-transformation of the materials that can be controlled by a magnetic field. This process could replace convention

Pragjyotish Bhuyan Gogoi, Awadhesh Prasad, Aryan Patel, Ram Ramaswamy

The Stuart-Landau oscillator generalized to $D > 2$ dimensions has SO($D$) rotational symmetry. We study the collective dynamics of a system of $K$ such oscillators of dimensions $D =$ 3 and 4, with coupling chosen to either preserve or break rotational symmetry. This leads to emergent dynamical phenomena that do not have analogs in the well-studied case of

Zhen Tao, Shidong Pan, Zhenchang Xing, Emily Black

Large language model (LLM) services have been rapidly integrated into people's daily lives as chatbots and agentic systems. They are nourished by collecting rich streams of data, raising privacy concerns around excessive collection of sensitive personal information. Privacy policies are the fundamental mechanism for informing users about data practices in mo

Xiaogang Li, Changchang Xi

As is known, every finite-dimensional algebra over a field is isomorphic to the centralizer algebra of \textbf{two} matrices. So it is fundamental to study first the centralizer algebra of a single matrix, called a centralizer matrix algebra. In this article, stable equivalences between centralizer matrix algebras over arbitrary fields are completely charact

Wei Wei, Qiang Hou, Jiajia Feng, Xinyue Wang

Recent studies have identified two superconducting domes in FeSe-based superconductors. It was discovered that each dome is accompanied by a distinct nematic quantum critical point (QCP): one associated with a pure nematic QCP, and the other with a nematic QCP entangled with antiferromagnetism (AFM). In this study, we delve into the evolution of the critical

Ruojun Xu, Yu Kai, Xuhua Ren, Jiaxiang Cheng

Direct Preference Optimization (DPO) has shown promising results in aligning generative outputs with human preferences by distinguishing between chosen and rejected samples. However, a critical limitation of DPO is likelihood displacement, where the probabilities of chosen samples paradoxically decrease during training, undermining the quality of generation.

Teodor Kostić, Ivan Milić, Matthias Rempel, Brian T. Welsch

We tested whether simultaneous spectropolarimetric imaging in two magnetically sensitive optical spectral lines, which probe two different layers of the solar atmosphere (the photosphere and the temperature minimum), can help constrain the depth variation of horizontal flows. We first tested the feasibility of our method using Fourier local correlation track

Aradhana Singh, Amod Rai, Sheksha Dudekula, Devanarayanan P

We study the coupled dynamics of multilayer networks with symmetric (MLs) and asymmetric (MLas) inter-layer connections. The symmetric inter-layer connections arise from a one-to-one correspondence between the nodes of different layers. In contrast, asymmetry results from the multiplicity of inter-layer connections, achieved by randomizing the links while pr

Yiven, Zhu

Neuroeconomics promises to ground welfare analysis in neural and computational evidence about how people value outcomes, learn from experience and exercise self-control. At the same time, policy and commercial actors increasingly invoke neural data to justify paternalistic regulation, "brain-based" interventions and new welfare measures. This paper asks unde

Anglin Liu, Rundong Xue, Xu R. Cao, Yifan Shen

Medical image segmentation is fundamental for biomedical discovery. Existing methods lack generalizability and demand extensive, time-consuming manual annotation for new clinical application. Here, we propose MedSAM-3, a text promptable medical segmentation model for medical image and video segmentation. By fine-tuning the Segment Anything Model (SAM) 3 arch

Nguyen Duc Minh Quang, Chang Liu, Shuangyang Li, Hoai-Nam Vu

Recently, environment reconstruction (ER) in integrated sensing and communication (ISAC) systems has emerged as a promising approach for achieving high-resolution environmental perception. However, the initial results obtained from ISAC systems are coarse and often unsatisfactory due to the high sparsity of the point clouds and significant noise variance. To

Trung Chau

Neural codes form an algebraic framework to study the nervous system, and understanding neural codes is a key goal of mathematical neuroscience. Neural rings and ideals are the tools connecting neuroscience and commutative algebra. In this article, we study the projective dimension and (Castelnuovo-Mumford) regularity of polarized neural ideals on $n$ neuron

Qixuan Hu, Chengjie Yu

In this note, we extend the rigidity of Cheng-Yau gradient estimate in \cite{HXY} to surfaces with lower Ricci curvature bound. Motivated by these sharp Cheng-Yau gradient estimates, pointwise Cheng-Yau gradient estimates for higher dimensional Riemannian manifolds are obtained, and as their applications, monotonicity formulas for positive harmonic functions

Sin-iti Sirono, Diego Turrini

Chondrules are spherical or subspherical particles of crystallized or partially crystallized liquid silicates that constitute large-volume fractions of most chondritic meteorites. Chondrules typically range $0.1-2\,$mm in size and solidified with cooling rates of $10-1000\,{\rm K\,h^{-1}}$, yet these characteristics prove difficult to reconcile with proposed

Dibya Kirti Mishra, Subhamoy Chatterjee, Bibhuti Kumar Jha, Hemapriya Raju

Kodaikanal Solar Observatory (KoSO) is one of the oldest solar observatories, possessing an archive of multi-wavelength solar observations, including white light, Ca II K, and H-alpha images spanning over a century. In addition to these observations, KoSO has preserved hand-drawn suncharts (1904-2022), on which various solar features such as sunspots, plages

Cassandra C. Chou, Scott L. Zeger, Benjamin Q. Huynh

Extreme event attribution (EEA), which assesses the extent to which disasters are caused by climate change, is crucial for informing climate policy and legal proceedings. Machine learning is increasingly used for EEA by modeling rare weather events too complex or computationally intensive for traditional methods. However, its validity remains unclear, as mac

Yves Achdou, Claudio Marchi, Nicoletta Tchou

We study a class of deterministic mean field games and related optimal control problems, with a finite time horizon and in which the state space is a network. An agent controls her velocity, and, when she occupies a vertex, she can either remain still or enter any adjacent edge. The running and terminal costs are assumed to be continuous in each edge, but ma

Zimo Yan, Zheng Xie, Chang Liu, Yuan Wang

Message passing graph neural networks are widely used for learning on graphs, yet their expressive power is limited by the one-dimensional Weisfeiler-Lehman test and can fail to distinguish structurally different nodes. We provide rigorous theory for a Laplacian positional encoding that is invariant to eigenvector sign flips and to basis rotations within eig

Daniel Bauer, Nils Kohl, Stephen F. McCormick, Rasmus Tamstorf

As the discretization error for the solution of a partial differential equation (PDE) decreases, the precision required to store the corresponding coefficients naturally increases. Storing the solution's finite element coefficients explicitly requires $\mathcal O(n \log n)$ bits of storage, where $n$ is the number of degrees of freedom (DoFs). This paper pre

Kai Zheng, Zhenkai Wu, Fupeng Wei, Miaolan Zhou

Accurately and swiftly assessing damage from conflicts is crucial for humanitarian aid and regional stability. In conflict zones, damaged zones often share similar architectural styles, with damage typically covering small areas and exhibiting blurred boundaries. These characteristics lead to limited data, annotation difficulties, and significant recognition

Maria Teresa Rotolo

We consider linear, time-dependent and skew-adjoint perturbations of periodic transport equations on the one-dimensional torus. We describe the long-time behavior of solutions for all non-degenerate perturbations in resonant regime, proving that either there exist solutions whose Sobolev norms explode exponentially fast, provoking energy transfer phenomena,

Gengyuan Zhang, Mingcong Ding, Jingpei Wu, Ruotong Liao

Embodied exploration is a target-driven process that requires embodied agents to possess fine-grained perception and knowledge-enhanced decision making. While recent attempts leverage MLLMs for exploration due to their strong perceptual and reasoning abilities, we find that MLLM-based embodied agents remain suboptimal in exploring new environments: (i) they

Yuchen Zhou, Haihang Wu

Monocular Simultaneous Localization and Mapping (SLAM) aims to estimate a robot's pose while simultaneously reconstructing an unknown 3D scene using a single camera. While existing monocular SLAM systems generate detailed 3D geometry through dense scene representations, they are computationally expensive due to the need for iterative optimization. To address

Xusheng Wang, Lianyi He, Shuai-hua Ji

Through a comprehensive free energy analysis, we demonstrate that finite temperature can simultaneously weaken superconductivity and mitigate spin polarization induced depairing, leading to potential non-monotonic temperature-dependent behaviors in superconductors subjected to large exchange fields. Remarkably, superconductivity can be counterintuitively enh

Alban Degezelle, Jonas Strobelt, Sarah Loebner, Moussa Mebarki

Tailoring at will polar textures in ferroelectrics is critical for the development of nanoscale electronics and functional oxide technologies. Freestanding ferroelectric membranes have enabled studies of strain-induced polarization responses, but the control over membrane shape and local polarization typically remains limited to spontaneous buckling or uniax

Xilai Li, Yilin Wu, Zhengnuo Chen, Mengqi Yang

We develop a weakly nonlinear, multi-mode theory for the Rayleigh-Taylor instability (RTI) on a time-varying spherical interface, fully incorporating mode couplings and the Bell-Plesset (BP) effects arising from interface convergence. Our model extends prior analyses, which have been largely restricted to static backgrounds, 2D cylindrical geometries, or sin

Christine Awofeso, Patrick Greaves, Oded Lachish, Amit Levi

We study property testing in the \emph{random neighbor oracle} model for graphs, originally introduced by Czumaj and Sohler [STOC 2019]. Specifically, we initiate the study of characterizing the graph families that are $H$-\emph{testable} in this model. A graph family $\mathcal{F}$ is $H$-testable if, for every graph $H$, $H$-\emph{freeness} (that is, not ha

Meisam Sharifi Sani, Saeid Iranmanesh, Raad Raad, Faisel Tubbal

Opportunistic Networks (OppNets) employ the Store-Carry-Forward (SCF) paradigm to maintain communication during intermittent connectivity. However, routing performance suffers due to dynamic topology changes, unpredictable contact patterns, and resource constraints including limited energy and buffer capacity. These challenges compromise delivery reliability

Quentin Gromoff, Magali Benoit, Jacek Goniakowski, Carlos R. Salazar

This study investigates the formation of zinc oxide (ZnO) nanoparticles, a material of significant technological interest with complex structural properties, through atom-by-atom deposition modeling a process common in bottom-up synthesis. Our findings demonstrate that, although the body-centered tetragonal (BCT) structure is thermodynamically stable at equi

Long Tang, Guoquan Zhen, Jie Hao, Jianbo Zhang

Blind image quality assessment (BIQA) plays a crucial role in evaluating and optimizing visual experience. Most existing BIQA approaches fuse shallow and deep features extracted from backbone networks, while overlooking the unequal contributions to quality prediction. Moreover, while various vision encoder backbones are widely adopted in BIQA, the effective

Yuting Gao, Weihao Chen, Lan Wang, Ruihan Xu

Preference learning has recently emerged as a pivotal strategy for post-training alignment of Multimodal Large Language Models (MLLMs). However, existing approaches predominantly rely on external human-annotated preference data, which is costly and labor-intensive to collect. In this work, we propose OrdMoE, a novel preference alignment framework that bypass

Argyrios Christodoulou, Konstantinos Zarvalis

The main goal of this article is to bring together the theories of holomorphic iteration in the unit disc and semigroups of holomorphic functions. We develop a technique that allows us to partially embed the orbit of a holomorphic self-map $f$ of the disc, into a semigroup which captures the asymptotic behaviour of the orbit. This extends the semigroup-ficat

Andrew Maranhão Ventura D'addario

The integration of Large Language Models (LLMs) into healthcare demands a safety paradigm rooted in \textit{primum non nocere}. However, current alignment techniques rely on generic definitions of harm that fail to capture context-dependent violations, such as administrative fraud and clinical discrimination. To address this, we introduce Medical Malice: a d

Qiyang Yu, Yu Fang, Tianrui Li, Xuemei Cao

Vision Transformers (ViTs) have demonstrated strong capabilities in capturing global dependencies but often struggle to efficiently represent fine-grained local details. Existing multi-scale approaches alleviate this issue by integrating hierarchical or hybrid features; however, they rely on fixed patch sizes and introduce redundant computation. To address t

Vishnu Priya Chekuru, Ganapathiraju S S Ananya Varma, Arti Yardi, Praful Mankar

Orthogonal Frequency-Division Multiplexing (OFDM) is widely used in modern wireless communication systems due to its robustness against time-dispersive channels. In this work, we consider a non-cooperative scenario where the receiver does not have prior knowledge of the OFDM parameters such as the number of subcarriers and the aim is to estimate them using t

Soham Mirajkar

Large Language Models (LLMs) are increasingly deployed in high-stakes financial domains, yet they suffer from specific, reproducible hallucinations when performing arithmetic operations. Current mitigation strategies often treat the model as a black box. In this work, we propose a mechanistic approach to intrinsic hallucination detection. By applying Causal

Nguyen Duc Minh Quang, Chang Liu, Huy-Trung Nguyen, Shuangyang Li

Low-altitude wireless networks (LAWN) are rapidly expanding with the growing deployment of unmanned aerial vehicles (UAVs) for logistics, surveillance, and emergency response. Reliable connectivity remains a critical yet challenging task due to three-dimensional (3D) mobility, time-varying user density, and limited power budgets. The transmit power of base s

Blazej Wrobel, Dominik Bojko

We investigate a process of joining $k$ random spanning trees on a fixed clique $K_n$. The joined trees may not be disjoint and multiple edges are replaced by one simple edge. This process produces a simple graph $G$ on $n$~vertices with an edge set, which is a union of edge sets of the joined trees. We study a random variable $S_{k}$ of the number of edges

Louise Dewick, Amy L Turnbull, Kate F Walker, Nia W Jones

In 2020 we first described placental contractions, and we have now undertaken a study to characterise them and seek features that might automatically separate them from uterine contractions. We recruited 36 healthy pregnant women to undergo magnetic resonance imaging (MRI) between 29 and 42 weeks of pregnancy in a single-centre, prospective, observational st

Dong Yang

We set out to solve a dual puzzle regarding reproductive strategies: The "Ancient vs. Modern" Puzzle (why pre-modern elites adopted a "Survival" strategy while modern elites adopt an "Anxiety" strategy) and the "Class Divide" Puzzle (why modern involution manifests as a U-shaped fertility pattern). We develop a unified computational framework (DP + Monte Car

Xinghe Chen, Dajun Sun, Quanqing Xu, Wei Dong

Differential Privacy (DP) is a widely adopted standard for privacy-preserving data analysis, but it assumes a uniform privacy budget across all records, limiting its applicability when privacy requirements vary with data values. Per-record Differential Privacy (PrDP) addresses this by defining the privacy budget as a function of each record, offering better

Sergio Belmonte Diaz, Rene P. Breton, Zafiirah Hosenie, Ben W. Stappers

Traditionally, fast radio transient searches are conducted on dedispersed time series using thresholding techniques based on the statistical properties of the data. However, peaks in dedispersed time series do not directly provide information on the nature of the source. In the DM-time domain, the S/N variation of real, dispersed astrophysical signals forms

James E. Owen, James Kirk

Transmission spectroscopy of sub-Neptunes was expected to reveal their compositions and hence origins, yet many show flat near- to mid-infrared spectra. Such spectra can be explained either by metal dominated atmospheres or by high-altitude, grey aerosols. Observations of escaping hydrogen and helium from several of these planets rule out metal dominated atm

Dev Karan Singh, Shiv Datt Kumar

In this paper, we introduce the concept of relative Lie central extension for pair of multiplicative Lie algebras. Then, we discuss the concept of isoclinism for relative Lie central extensions and prove some related results. We also define the Frattini subalgebra for multiplicative Lie algebras and discuss its properties, finally the Schur multiplier for pa

Taoliang Tan, Chengwei Ma, Zhen Tian, Zhao Lin

The intelligent review of power grid engineering design drawings is crucial for power system safety. However, current automated systems struggle with ultra-high-resolution drawings due to high computational demands, information loss, and a lack of holistic semantic understanding for design error identification. This paper proposes a novel three-stage framewo

Jiale Zhang, Yeqiang Qian, Tong Qin, Mingyang Jiang

The increase in vehicle ownership has led to increased traffic congestion, more accidents, and higher carbon emissions. Vehicle platooning is a promising solution to address these issues by improving road capacity and reducing fuel consumption. However, existing platooning systems face challenges such as reliance on lane markings and expensive high-precision

Vyacheslav Yu. Shaprynski\vı, Dmitry V. Skokov

This paper is the first part of a study devoted to description of modular elements in the lattices of semigroup and epigroup varieties. We provide strengthened necessary and sufficient conditions under which a semigroup or epigroup variety constitutes a modular element in its respective lattice. These results refine previously known criteria and lay the grou

Junbo Zhang, Ran Chen, Qianli Zhou, Xinyang Deng

Large language models (LLMs) demonstrate powerful capabilities across various natural language processing tasks,yet their inherent safety vulnerabilities undermine the reliable application of LLMs in real-world scenarios. To enhance LLM safety, various jailbreak defense methods have been proposed to guard against harmful outputs. However, improvements in mod

Liuyi Chen, Yuchen Hu, Zhengyi Yang, Xu Zhou

Subgraph matching is a core task in graph analytics, widely used in domains such as biology, finance, and social networks. Existing top-k diversified methods typically focus on maximizing vertex coverage, but often return results in the same region, limiting topological diversity. We propose the Distance-Diversified Top-k Subgraph Matching (DTkSM) problem, w

Carsten Källner, Ola Ali, Andrea Vismara, Guillermo Prieto-Viertel

Modelling migration is complicated, as people move for many reasons. Some leave their country for the first time, others return to places they once called home, or move on to new destinations. However, most models focus only on who arrives, missing the full picture of how migrant populations evolve. We introduce a model for diaspora flows that estimates both

Cesare Bracco, Francesco Patrizi, Alessandra Sestini

We introduce a novel quadrature strategy for Isogeometric Analysis (IgA) boundary element discretizations, specifically tailored to collocation methods. Thanks to the dimensionality reduction and the natural handling of unbounded domains, boundary integral formulations are particularly appealing in the IgA framework. However, they require the evaluation of b

Di Wu, Liting Jiang, Ruiyu Fang, Bianjing

Spoken Language Understanding (SLU) consists of two sub-tasks: intent detection (ID) and slot filling (SF). Given its broad range of real-world applications, enhancing SLU for practical deployment is increasingly critical. Profile-based SLU addresses ambiguous user utterances by incorporating context awareness (CA), user profiles (UP), and knowledge graphs (

Juan García-Bellido

The nature of the cosmological constant is a mystery. We don't understand its quantum origin but we associate it with the actual acceleration of the universe because it is the simplest description we had until recently of the present cosmological observations. However, this may change with the next generation of experiments. If we can convince ourselves that

Wentao Qu, Guofeng Mei, Yang Wu, Yongshun Gong

Text-to-LiDAR generation can customize 3D data with rich structures and diverse scenes for downstream tasks. However, the scarcity of Text-LiDAR pairs often causes insufficient training priors, generating overly smooth 3D scenes. Moreover, low-quality text descriptions may degrade generation quality and controllability. In this paper, we propose a Text-to-Li

Jingzhou Sun

We prove an explicit formula for the Bergman kernel of polarized abelian varieties. As applications, we show that if two positive line bundles represent the same first Chern class and have identical Bergman kernel functions for some tensor power, then the corresponding powers of the bundles are isomorphic. We also obtain localization results for the maxima a

Dominik Gond, Justus Arweiler, Thomas Specht, Hans Hasse

Sigma-profiles obtained from quantum-chemical calculations are key molecular descriptors for solvent selection, thermodynamic modeling, and data-driven molecular design. However, existing sigma-profile libraries are limited in size and inconsistent in quality, which restricts their utility. In this work, we introduce CHAOS (Computed High-Accuracy Observables

Zdeněk Mihula, Maximilián Pándy

We introduce and study two new relations between function spaces over measure spaces of infinite measure, motivated by the question of establishing compactness. The first relation captures the uniform decay of function (quasi-)norms ``at infinity''. It appeared implicitly in the first author's recent work on the compactness of Sobolev embeddings of radially

Iván Mozún Mateo

The current KM3NeT/ORCA neutrino telescope, still under construction, has not yet reached its full potential in neutrino reconstruction capability. When training any deep learning model, no explicit information about the physics or the detector is provided, thus they remain unknown to the model. This study leverages the strengths of transformers by incorpora

Jorge Ruiz-Garcia, Anthony Grbic

Fully harnessing the vast design space enabled by metamaterials to control electromagnetic (EM) fields remains an open problem for researchers. Inverse-design techniques have shown to best exploit the degrees of freedom available in design, resulting in high-performing systems for wireless communications, sensing and analog signal processing. Nonetheless, fu

Gul Hameed, Tao Chen, Antonio del Rio Chanona, Lorenz T. Biegler

Gray-box optimization, where parts of optimization problems are represented by algebraic models while others are treated as black-box models lacking analytic derivatives, remains a challenge. Trust-region (TR) methods provide a robust framework for gray-box problems through local reduced models (RMs) for black-box components, but they are complex and require

Chenhao Zhai, Chang Meng, Xueliang Wang, Shuchang Liu

The rapid proliferation of short videos on social media platforms presents unique challenges and opportunities for recommendation systems. Users exhibit diverse preferences, and the responses resulting from different strategies often conflict with one another, potentially exhibiting inverse correlations between metrics such as watch time and video view count

Kaidi Wan, Minghao Liu, Yong Lai

Wepropose SplitGNN, a graph neural network (GNN)-based approach that learns to solve weighted maximum satisfiabil ity (MaxSAT) problem. SplitGNN incorporates a co-training architecture consisting of supervised message passing mech anism and unsupervised solution boosting layer. A new graph representation called edge-splitting factor graph is proposed to prov

Yunxiang Wang, Lixin Yan, Hong-Wei Zhang

Let $\mathcal{L}$ be the positive definite left-invariant distinguished Laplacian, and let $\mathrm{d}ρ$ denote the right Haar measure on a Damek--Ricci space $S$. Let $u(t,x)$ denote the solution to the wave equation $\partial_t^2 u + \mathcal{L} u=0$ with initial data $(u,\partial_t u)|_{t=0}=(f,g)$. In this paper, we establish the sharp-in-regularity $L^p

Christian Haase, Zongpu Zhang

In this paper, we study the multigraded Betti numbers of Veronese embeddings of projective spaces. Due to Hochster's formula, we interpret these multigraded Betti numbers in terms of the homology of certain simplicial complexes. By analyzing these simplicial complexes and applying Forman's discrete Morse theory, we derive vanishing and non-vanishing results

Christos Koutlis, Symeon Papadopoulos

With the rapid advancement of sophisticated synthetic audio-visual content, e.g., for subtle malicious manipulations, ensuring the integrity of digital media has become paramount. This work presents a novel approach to temporal localization of deepfakes by leveraging Audio-Visual Speech Representation Reconstruction (AuViRe). Specifically, our approach recon

Zineddine Tighidet, Lazhar Labiod, Mohamed Nadif

The mixture model is undoubtedly one of the greatest contributions to clustering. For continuous data, Gaussian models are often used and the Expectation-Maximization (EM) algorithm is particularly suitable for estimating parameters from which clustering is inferred. If these models are particularly popular in various domains including image clustering, they

Duolikun Danier, Ge Gao, Steven McDonagh, Changjian Li

Video generation models have made significant progress in generating realistic content, enabling applications in simulation, gaming, and film making. However, current generated videos still contain visual artifacts arising from 3D inconsistencies, e.g., objects and structures deforming under changes in camera pose, which can undermine user experience and sim

Ohad Bachner, Bar Gamliel

Robots often fail at everyday tasks because instructions skip commonsense details like hidden preconditions and small subgoals. Traditional symbolic planners need these details to be written explicitly, which is time consuming and often incomplete. In this project we combine a Large Language Model with symbolic planning. Given a natural language task, the LL

Tarun Prajapati

Modern Retrieval-Augmented Generation (RAG) systems struggle with a fundamental architectural tension: vector indices are optimized for query latency but poorly handle continuous knowledge updates, while data lakes excel at versioning but introduce query latency penalties. We introduce LiveVectorLake, a dual-tier temporal knowledge base architecture that ena

G. A. Bobkov, I. A. Shvets, I. V. Bobkova, A. M. Bobkov

The superconductor/ferromagnet/superconductor (S/F/S) Josephson junctions (JJs) with an anomalous ground state phase shift $\varphi_0 \neq 0,\pi$ ($\varphi_0$-S/F/S JJs) enable the implementation of the zero-field Josephson diode effect with the possibility to control the diode efficiency and polarity. It is just as important that in this case $\varphi_0$ pr

Wassim Benabbas, Mohammed Brahimi, Samir Akhrouf, Bilal Fortas

Recent advances in deep learning have enabled significant progress in plant disease classification using leaf images. Much of the existing research in this field has relied on the PlantVillage dataset, which consists of well-centered plant images captured against uniform, uncluttered backgrounds. Although models trained on this dataset achieve high accuracy,

Marcial Sanchis-Agudo, Ricardo Vinuesa

We propose a theoretical framework where the dissipative structures of turbulence emerge from microscopic path uncertainty. By modeling fluid parcels as stochastic tracers governed by the Schr\"odinger Bridge (SB) variational principle, we demonstrate that the Navier--Stokes viscous term is a natural linear, second-order macroscopic operator consistent with

Omar Faris, Sławomir Tadeja, Fulvio Forni

Object handover is a common form of interaction that is widely present in collaborative tasks. However, achieving it efficiently remains a challenge. We address the problem of ensuring resilient robotic actions that can adapt to complex changes in object pose during human-to-robot object handovers. We propose the use of Virtual Model Control to create an int

Matthew Newton, Zuxun Xiong, Han Wang, Antonis Papachristodoulou

One of the desirable objectives in feedback control design is to formulate and solve the design problem as an optimisation problem that is convex, so that an optimal solution can be found efficiently. Unfortunately many control design problems are non-convex: approximations, relaxations, or iterative schemes are usually employed to solve them. Several such a

Donghu Kim

The challenge of building neural networks that can continuously learn and adapt to evolving data streams is central to the fields of continual learning (CL) and reinforcement learning (RL). This lifelong learning problem is often framed in terms of the plasticity-stability dilemma, focusing on issues like loss of plasticity and catastrophic forgetting. Unlik

Vitor Araujo, Luciana Salgado

We obtain sufficient conditions for the existence of physical/SRB measures for asymptotically sectionally hyperbolic attracting sets with any finite co-dimension, extending the co-dimension two case. We provide examples of such attractors, either with non-sectional hyperbolic equilibria, or with sectional-hyperbolic equilibria of mixed type, i.e., with a Lor

Jaeyeong Kim, Seungwoo Yoo, Minhyuk Sung

We introduce SpLap, a proxy-free deformation method for Gaussian splats (GS) based on a Laplacian operator computed from our novel surface-aware splat graph. Existing approaches to GS deformation typically rely on deformation proxies such as cages or meshes, but they suffer from dependency on proxy quality and additional computational overhead. An alternativ

Sajjad Taravati

Space-time metamaterials are redefining wave engineering by enabling fully dynamic four-dimensional control of electromagnetic fields, allowing simultaneous manipulation of frequency, amplitude, momentum, and propagation direction. This unified functionality moves well beyond reciprocity-breaking mechanisms, marking a fundamental transition from static media