April 2026 arXiv papers — page 54

Biagio Andreucci, Arcangelo Castiglione

The offensive security landscape is highly fragmented: enterprise platforms avoid memory-corruption vulnerabilities due to Denial of Service (DoS) risks, Automatic Exploit Generation (AEG) systems suffer from semantic blindness, and Large Language Model (LLM) agents face safety alignment filters and "Live Fire" execution hazards. We introduce Automation-Expl

Tim Buchholz, Julian Dörner

The present paper studies finite element discretizations of second-order elliptic boundary value problems with homogeneous right-hand side and inhomogeneous boundary conditions. We establish discrete spatial decay estimates on element patches for the energy norm of the discrete solution, showing that the influence of boundary data decays exponentially away f

Friedemann Brock, Francesco Chiacchio, Adele Ferone, Anna Mercaldo

In this paper weighted Dirichlet-type inequalities for the decreasing rearrangement in cylinders are proved. A weighted isoperimetric inequality is also obtained.

Stephen R. Green, Kirill Krasnov, Adam Shaw

The Euclidean Kerr metric is conformal, in two distinct ways, to a Kahler metric, with conformal factors determined by the repeated eigenvalue of the two chiral halves of the Weyl curvature. A Lorentzian analogue holds, where the conformally related metric is complex but retains key features of Kahler geometry. We show that this hidden Kahler structure provi

Dursun Bulutoglu, Daniel Baczkowski, Joshua Yauney

In this paper we determine the structure of the group of all operations that send each Legendre pair to an equivalent Legendre pair.

Meghyn Bienvenu, Diego Figueira, Pierre Lafourcade

We consider the following fundamental problem: given a database D, Boolean conjunctive query (CQ) q, and fact f in D, decide whether f is relevant to q wrt. D, i.e., does f belong to a minimal subset S of D such that S |= q. Despite being of central importance to query answer explanation, the combined complexity of deciding query relevance has not been studi

Kritika Rushiya, Gaurav Hajong, Bhabani Prasad Mandal, Poonam Mehta

We develop a consistent mathematical framework for studying two flavor neutrino oscillations in presence of non-Hermitian dynamics. We consider two approaches : (a) bi-orthonormal inner product defined by a positive-definite metric operator $\mathcal{G}$ and (b) the density matrix prescription by Brody and Graefe [Phys. Rev. Lett. 109, 230405 (2012)]. For th

Minghui Xu, Qi Luo, Kun Li

Traditional data valuation methods based on ``row-count $\times$ quality coefficient'' paradigms fail to capture the nuanced, nonlinear contributions that data makes to Large Language Model (LLM) capabilities. This paper presents a dynamic data valuation framework that transitions from static accounting to utility-based pricing. Our approach operates on thre

Vanessa Ryborz

We prove that any metric measure spacetime arising from a smooth manifold $M$ endowed with a continuous Lorentzian metric $g$ is infinitesimally Minkowskian, under the assumption that $(M, g)$ is causally simple.

Indranil Biswas, Manish Kumar, A. J. Parameswaran

We compute the Harder-Narasimhan filtration of vector bundles $f_*\mathcal O_Y$ for certain finite morphisms $f\,:\,Y\,\longrightarrow\, X$ and in some other cases.

Claudia de Rham, Jan Kożuszek, Andrew J. Tolley, Toby Wiseman

We consider the ghost-free dRGT massive gravity with two of its three possible mass terms. This theory has five gravitational degrees of freedom. On Minkowski spacetime these modes have helicity-2, -1 and -0 and propagate on the Minkowski lightcone in the high-frequency limit. However for a general background the degrees of freedom corresponding to the helic

Annie Landerberg, Kari Flatmo, Alan Said

Social chatbots based on large language models are increasingly embedded in everyday platforms, yet how users develop trust in these systems over time remains unclear. We present a four-week longitudinal qualitative survey study (N = 27) of trust formation in Snapchat's My AI, a socially embedded conversational agent. Our findings show that trust is shaped b

Zongyu Li

Latent variables pose a fundamental obstacle to both causal discovery and inference. Local approaches exploiting direct neighborhood relations provide little beyond immediate dependencies. Cluster-level methods, though capable of broader reasoning, generally require cluster assignments or causal sufficiency in advance, conditions that are rarely satisfied in

María J. Ortín, José R. Hoyos, Jesus García-Molina

Database migration is a key task in software modernization, increasingly involving transformations across heterogeneous data models such as relational and NoSQL systems. Existing approaches are typically designed for specific source-target combinations, which limits their applicability in multi-model environments. This paper proposes a generic database migra

Qinhan Hou, Jing Tang

Graph Transformers can mix information globally, but this flexibility also creates failure modes: some tasks require long-range communication while others are better served by local interaction. We study this through a synthetic node-classification benchmark on contextual stochastic block model graphs, where labels are generated by a controllable mixture of

Alberto Messina, Stefano Scotta

Even when decoding with temperature $T=0$, large language models (LLMs) can produce divergent outputs for identical inputs. Recent work by Thinking Machines Lab highlights implementation-level sources of nondeterminism, including batch-size variation, kernel non-invariance, and floating-point non-associativity. In this short note we formalize this behavior b

Francesco Della Pietra

We study the efficiency of the first Dirichlet eigenfunction $u$ on bounded convex domains $\Omega \subset \mathbb{R}^N$, defined as the ratio between the mean value of $u$ on $\Omega$ and its maximum value. By exploiting improved log-concavity estimates, we establish new sharp lower bounds for the first eigenvalue $\lambda_1$ and upper bounds for the effici

Dawid Dopierała, Luca Cocconi, Robert L. Jack, Anton Souslov

Active self-assembly can bypass equilibrium bottlenecks through external energy injection. However, generic driving typically distorts target structures and requires sustained energy input even after assembly is complete. Here, we investigate a class of non-reciprocal interactions that accelerates assembly while preserving the equilibrium Boltzmann distribut

Junjun Huang, Xiliang Lu, Xuelin Xie, Jerry Zhijian Yang

K-plane clustering (KPC), hyperplane clustering, and mixture regression all essentially fall within the same class of problems. This problem can be conceptualized as clustering in relatively high-dimensional K subspaces or K linear manifolds. Traditional KPC or fuzzy KPC models demonstrate a pronounced susceptibility to outliers, as they presuppose that the

Lucio Bedulli, Lorenzo Marcocci

We consider homogeneous hypercomplex manifolds with a transitive action of a compact Lie group and we give a characterization of invariant HKT metrics on them. On every such hypercomplex manifold we prove the existence of an invariant HKT-Einstein metric, which is unique up to scaling. Furthermore, we determine for which invariant HKT metrics the torsion and

A. Yermekov, D. A. Herrera-Martí

Feature selection in high-dimensional genomic data ($d \gg n$) demands methods that are simultaneously accurate, sparse, and stable. Existing approaches either require manual threshold specification (mRMR, stability selection), produce unstable selections under data perturbation (Lasso, Boruta), or ignore biological structure entirely. We introduce StackFeat

Navid Ardakanian

On $T^6/(Z_3 \times Z_3)$ heterotic orbifolds where three quark generations arise from $Z_3$ fixed-point triplication, we prove that the leading-order tree-level Yukawa amplitude -- the three-point coupling among massless string states -- has an exact column texture: $Y_{\rm lead}(i,j) = c\,\varepsilon^{q_R[j]}$, with the $O(1)$ coefficient $c$ universal acr

Maxim N. Demchenko

We consider the characteristic problem for the ultrahyperbolic equation in the Euclidean space. The value of a solution is prescribed on the characteristic hyperplane. A well-posed set-up of the problem is discussed. We obtain a certain representation for a solution suitable for analysis of its asymptotics at the infinity.

Guillaume Elias, Emanuele Daddi, Chiara D'Eugenio, David Elbaz

Cold accretion and quenching are closely related aspects of galaxy evolution, as sustained gas supply is required to maintain star formation. High-redshift galaxy groups therefore provide a valuable laboratory for testing how the thermal state of accreting gas relates to the emergence of quiescence. We measure quiescent fractions in a sample of 16 spectrosco

Giacomo Garaccione, Riccardo Coppola, Luca Ardito

Unified Modeling Language (UML) Use Case and Class Diagrams are fundamental modeling notations in Software Engineering (SE) education due to their importance for requirements and model-based engineering, yet their relevance is underestimated by students, who tend to dismiss the topic as secondary. Gamification has been adopted to make modeling education more

Xinyan Chi, Ruoao Yang, Zhiyuan Li, Tuo Liu

Nanophotonic supercontinuum generation offers a practical route to chip-based f-2f interferometry by leveraging coexisting chi(2) and chi(3) nonlinearities. In conventional uniform waveguides, the phase-matching bandwidth for second-harmonic generation (SHG) is intrinsically narrow, restricting the spectral overlap factor for heterodyne beating. To address t

Sangjun Kang, Hyeyoung Cho, Maximilian Töllner, Anna Rose Nelson

Space charge layers (SCLs) at grain boundaries play a crucial role in modulating local electric fields and influencing the functional properties of materials, such as oxygen vacancy migration and ionic conductivity in oxide ceramics. However, the direct experimental analysis of such localized electric fields and the corresponding charge distribution remains

Sunday A. Adetunji

Background:Adverse reproductive history is a multisystemic risk factor, but evidence is constrained by isolated outcome studies, limited adjustment, and non-interpretable algorithmic models. We re-frame the estimand from prediction to concurrent risk classification and emphasize calibration, interpretability, and systematic error. Methods:We analyzed 1,602 U

Yuxuan He, Jiangwei Wu, Xiangmin Liu, Feiyang Shen

Rare-earth-doped materials constitute the foundation of conventional solid-state lasers, but their bulk-crystal form is inherently incompatible with photonic integration, making it challenging to realize compact, high performance nanoscale laser sources. Lithium niobate on insulator (LNOI), with its exceptional electro-optic and nonlinear optical properties,

Sayali V. Chaudhary, Ashish V. Orpe

We investigate the flow of spherical, bulk granular particles down an inclined plane mixed with small-sized spherical lubricant particles using discrete element method simulations. Predefined cohesive interaction is implemented between lubricant and bulk particles, enabling the coating of the former over the latter. The overall flow rate exhibits non-monoton

Araujo-Pardo Gabriela, Kiss György

In this paper, we introduce a problem closely related to the {\emph{Cage Problem}}. We are interested in {\emph{Balanced Biregular Cages}}, which are the smallest biregular graphs of fixed girth that have the same number of vertices of one degree as the other. We introduce the graphs and obtain lower and upper bounds for some values of degree and girth. In p

Matthijs Lau, Ioan Mărcuţ

We introduce multiplicative Ehresmann connections on surjective submersions of Lie groupoids, extending both the classical notion of Ehresmann connections on fibre bundles and the more recent notion of multiplicative connections on Lie groupoid extensions. We investigate the existence of such connections, showing that, in general, they may fail to exist even

Chan Xu, Shuowen Zhang

This paper studies an integrated sensing and communication (ISAC) system where a multi-antenna base station (BS) communicates with multiple single-antenna users in the downlink and senses the unknown and random angle information of a target based on its prior distribution information and the received echo signals. We focus on a challenging scenario with hete

Zhanli Wu, Fabrizio Leisen, Miguel-Angel Luque-Fernandez, F. Javier Rubio

The Super Learner (SL) is a widely used ensemble method that combines predictions from a library of learners based on their predictive performance. Interval predictions are of considerable practical interest because they allow uncertainty in predictions produced by an individual learner or an ensemble to be quantified. Several methods have been proposed for

Shunpeng Chen, Yukun Song, Changwei Wang, Rongtao Xu

Visual Place Recognition (VPR) determines a query image's geographic location by matching it against geotagged databases. However, existing methods struggle with perceptual aliasing caused by irrelevant regions and inefficient re-ranking due to rigid candidate scheduling. To address these issues, we introduce FoL++, a method combining robust discriminative r

Alexey Samokhin

Spherical and cylindrical KdV-B equations have few known exact solutions, yet these solutions are hard to be interpreted physically. But these equations do have a family of diverging shock waves. Their properties such as asymptotic modes, stability, rules of their interactions/superposition are the subject of this paper. It gives a detailed asymptotic descri

Xu Lu, Qianhong Peng, Qihao Zhou, Shaopeng Liu

Transrectal ultrasound (TRUS) imaging is a cost-effective and non-invasive modality widely used in the diagnosis of prostate cancer. The computer-aided diagnosis (CAD) relying on TRUS images has been extensively investigated recently. Compared to static images, TRUS video provides richer spatial-temporal information, which make it a promising alternative for

Giulio Belletti, Renaud Detcherry

We prove that given two compact oriented $3$-manifolds $N$ and $M,$ with $M$ satisfying only a mild hypothesis, there is a hyperbolic $3$-manifold $N'$ arbitrarily ``closely related'' to $N,$ and such that $N'$ does not embed in $M.$ For instance, as a weak version of our main theorem, if $M$ is a rational homology sphere then for any $k\geq

Daniele Calandriello, Alessandro Lazaric, Michal Valko

One of the major limits of kernel ridge regression (KRR) is that storing and manipulating the kernel matrix K_n for n samples requires O(n^2) space, which rapidly becomes unfeasible for large n. Nystrom approximations reduce the space complexity to O(nm) by sampling m columns from K_n. Uniform sampling preserves KRR accuracy (up to epsilon) only when m is pr

Akram Erraqabi, Michal Valko, Alexandra Carpentier, Odalric-Ambrym Maillard

Rejection sampling is a technique for sampling from difficult distributions. However, its use is limited due to a high rejection rate. Common adaptive rejection sampling methods either work only for very specific distributions or without performance guarantees. In this paper, we present pliable rejection sampling (PRS), a new approach to rejection sampling,

Dogan Ulus

We present Reelay, a unified online temporal logic monitoring framework designed for the rigorous analysis and runtime verification of cyber-physical systems. Reelay addresses the fragmentation of existing logical formalisms and tools by providing a single computational model and interface that supports a broad class of temporal logics. These include Linear

Yufan Zhuang, Zili Meng, Zehong Lin, Jun Zhang

Real-time communications (RTC) is a core technology for emerging applications in 6G, such as cloud gaming, teleoperation, and extended reality (XR), which require consistently low latency and high bitrates. Existing RTC solutions fundamentally struggle to maintain low latency while supporting high bitrates due to their reliance on trial-and-error-based mecha

Cheng-Ming Li, Guang-Hao Yu, Ya-Peng Zhao, Zhibin Li

Solutions of the quark gap equation and the corresponding vacuum pressure are investigated within a modified Nambu-Jona-Lasinio model, which is a basic issue for studying the QCD equation of state (EOS) and the properties of hypothetical non-strange quark stars. In this study, the coupling strength $G$ is modified as $G=G_1+G_2\langle\bar{\psi}\psi\rangle$ t

Masaki Iwaya, Vivien Raymond, Soichiro Morisaki, Kazuki Takada

Gravitational-wave parameter estimation for binary neutron star (BNS) systems poses severe computational challenges due to the extended signal duration, which can reach several minutes in current detectors. Neural posterior estimation (NPE), a simulation-based inference approach, offers dramatic speedups but requires effective dimensionality reduction of the

Jincheng Ying, Yitao Chen, Li Wenlin, Minghui Xu

Recent advances in distilling expensive diffusion models into efficient few-step generators show significant promise. However, these methods typically demand substantial computational resources and extended training periods, limiting accessibility for resource-constrained researchers, and existing supplementary loss functions have notable limitations. Regres

Qing-Hu Hou, Yan-Ping Mu

We propose a systematic method for constructing Wilf-Zeilberger (WZ) seeds and present seven WZ seeds. We also demonstrate how to construct WZ seeds from existing ones. With these WZ seeds, several hypergeometric identities are derived. The construction can be extended to the $q$-cases, leading to the $q$-analogues of the seven WZ seeds.

Kenta Koshihara, Kazuya Yuasa

We study the thermodynamics of a quantum measurement-powered engine that converts energy injected by measurement backaction into work. We consider an engine with a finite-dimensional working substance, driven purely by quantum measurements, i.e., by bare quantum measurements, without feedback control or thermal contact in the thermodynamic cycle. On the basi

Laura Ciobanu, Daniel Turaev

In this paper we explore the connections between the class of Visibly Pushdown Languages ($\mathbf{VPL}$) and the natural sets of words one can associate to a finitely generated group. We show that the word problem of a finitely generated group is $\mathbf{VPL}$ exactly when the group is finite. We also show that free reduction does not preserve $\mathbf{VPL

Changhao Lai, Rui Zhao, Xuewen Zhong, Jinsong Su

Sign language translation (SLT) converts continuous sign videos into spoken-language text, yet it remains challenging due to the intrinsic modality mismatch between visual signs and written text, particularly in gloss-free settings. Recent SLT systems increasingly adopt CLIP-like Vision-Language pretraining (VLP) for cross-modal alignment, but the random in-

Marco Damele, Andrea Loi

We study simplicity of Lie skew braces from both global and infinitesimal perspectives. After reviewing the correspondence between connected Lie skew braces, simply transitive affine actions, and post-Lie algebras, we investigate ideals and rigidity phenomena. Our main result concerns compact connected Lie skew braces. We prove that any compact connected sim

Wenjie Xiao, Xuehai Tang, Biyu Zhou, Songlin Hu

Agent skills introduce a new and more severe form of indirect injection for LLM agents: unlike traditional indirect prompt injection, attackers can hide malicious instructions inside a dense, action-oriented skill that already functions as a legitimate instruction source. We study pre-execution skill-poison detection and show that successful skill poisoning

Yuki Hashimoto, Kazuharu Bamba, Sanjay Mandal

In modern cosmology, the rapid growth of high-precision observational data, along with significant theoretical advances, has intensified the challenge of identifying a robust, model-independent framework to probe the expansion history of the Universe. In this work, we propose a novel artificial neural network (ANN)-based framework for the non-parametric reco

Lars Reichwein, Dimitris Sofikitis, Oliver Mathiak, T. Peter Rakitzis

Pinching of the driver beam in plasma wakefield acceleration is generally considered an unwanted effect that needs to be mitigated. Here, we propose that this effect can be utilized for the injection of spin-polarized electron beams from hydrogen halide targets into wakefields. Particle-in-cell simulations show that the electron spin is preserved on a level

Akbar Yermekov, D. A. Herrera-Martí

In high-dimensional genomic data, the curse of dimensionality (d >> n) and limited sampling make feature selection inherently unstable - a critical barrier to biomarker discovery. We introduce StackFeat, an iterative algorithm that accumulates two statistics across repeated cross-validation: signed coefficients (measuring effect strength and direction) and s

Noah Kaufmann, Kasper H. Nielsen, Eva M. González-Ruiz, Anders S. Sørensen

Entanglement has been proposed as a means to improve the sensitivity of sensing weak signals. While the degree of this quantum advantage is well understood in noiseless settings, the situation is more complex under realistic conditions, where the system is subject to decoherence. In this case, the enhancement depends on the specific noise characteristics. Pr

Rui Zhao, Xuewen Zhong, Xiaoyun Zheng, Jinsong Su

Sign language research has achieved significant progress due to the advances in large language models (LLMs). However, the intrinsic ability of LLMs to understand sign language, especially in multimodal contexts, remains underexplored. To address this limitation, we introduce CNSL-bench, the first comprehensive Chinese em{National Sign Language benchmark des

Elsa Cazelles, Edouard Pauwels, Léo Portales

We introduce and analyze a statistical estimator for Monge transport maps: solutions to the quadratic optimal transport problem in the Euclidean space. For absolutely continuous source measures, this map is uniquely defined as the gradient of a convex function, a result known as Brenier's theorem. Without absolute continuity, the problem is relaxed, maps

Pu Li, Huafeng Li, Yafei Zhang, Yu Liu

Thermal infrared image enhancement aims to restore high-quality images from complex compound degradations. Existing all-in-one approaches typically employ a single shared backbone to handle diverse degradations, which causes gradient interference and parameter competition. To address this, we propose a Structural Entropy-Guided Decoupled (SEGD) Framework. Un

Samir Datta, Asif Khan, Felix Tschirbs, Nils Vortmeier

Consider two planar graphs which are subject to edge insertions and deletions. We show that whether the two graphs are isomorphic can be maintained with first-order logic formulas and auxiliary data of polynomial size. This places the dynamic planar graph isomorphism problem into the dynamic descriptive complexity class DynFO. As a consequence, there is a dy

Maharani Ahsani Ummi, Stuart Barber, Henry M. Wood, Arief Gusnanto

Detecting copy number alterations (CNAs) from next-generation sequencing data remains challenging, particularly for short segments under noisy conditions. Existing segmentation methods often suffer from high false positive rates or fail to reliably detect short aberrations, especially in low-coverage data. In this study, we propose a modified tail-greedy unb

Zeyi Li, Yushi Yang, Shawn Xie, Kyle Xu

Household environments present one of the most common, impactful yet challenging application domains for robotics. Within household scenarios, manipulating deformable objects is particularly difficult, both in simulation and real-world execution, due to varied categories and shapes, complex dynamics, and diverse material properties, as well as the lack of re

Mauricio Che, Raquel Perales

We introduce the notion of timed-Gromov--Hausdorff distance for timed-metric spaces. We prove that this distance is bi-Lipschitz equivalent to the intrinsic timed-Hausdorff distance of Sakovich--Sormani, and therefore induces the same notion of convergence. We establish a compactness theorem for the timed Gromov--Hausdorff distance, obtained as a straightfor

Yusuke Fujiwara, Yusuke Matsushita, Kohei Suenaga, Atsushi Igarashi

Tanaka et al. proposed a type system for verifying functional correctness properties of programs that use arrays and pointer arithmetic. Their system extends ConSORT -- a type system combining fractional ownership and refinement types for imperative program verification -- with support for pointer arithmetic. Their idea was to extend fractional ownership so

Hai Jin, Diansheng Guo

Spatial redistricting is a practical combinatorial optimization problem that demands high-quality solutions, rapid turnaround, and flexibility to accommodate multi-criteria objectives and interactive refinement. A central challenge is the contiguity constraint: enforcing contiguity in integer-programming or heuristic search can severely shrink the feasible n

Benedikt Franke, Nils Förster, Frank Köster, Asja Fischer

Neural activation coverage (NAC) is a recently-proposed technique for out-of-distribution detection and generalization. We build upon this promising foundation and extend the method to work as an uncertainty estimation technique for already-trained artificial neural networks in the domain of regression. Our experiments confirm NAC uncertainty scores to be mo

Vadim V. Bobylev, Anisa T. Bajkova, Nazar R. Ikhsanov

A sample of 139 young open star clusters closely associated with the Radcliffe wave is considered. Modeling their spatial distribution and kinematics over a time interval of 30 Myrs ago and 30 Myrs into the future revealed that they exhibit the main properties characteristic of a Radcliffe wave over the past 10-15 Myr. They are distributed on the galactic XY

Mateusz Kamyczura, Jakub Przybyło

The conflict-free chromatic index of a graph $G$ is the minimum number of colours in an edge colouring of $G$ such that the neighbourhood of every edge contains a colour appearing exactly once. Its vertex analogue is the conflict-free chromatic number. These two parameters naturally coincide when the second is applied to the line graph of $G$. It is known th

Kang Liu, Jianchen Hu, Wei Peng

Classical ReLU-based Input Convex Neural Networks (ICNNs) are equivalent to the optimal value functions of Linear Programming (LP). This intrinsic structural equivalence restricts their representational capacity to piecewise-linear polyhedral functions. To overcome this representational bottleneck, we propose the SOC-ICNN, an architecture that generalizes th

Zhikun Tu, Yuhe Zhang, Yiou Jia, Kang Li

Each scanner possesses its unique characteristics and exhibits its distinct sampling error distribution. Training a network on a dataset that includes data collected from different scanners is less effective than training it on data specific to a single scanner. Therefore, we present a novel one-shot learning method allowing for edge extraction on point clou

Fu-Peng Li, Long-Gang Pang, Guang-You Qin

The equation of state (EoS) of strongly interacting matter at finite temperature and chemical potentials (baryon, charge, and strangeness) is a crucial input for hydrodynamic simulations of relativistic heavy-ion collisions. We construct a four-dimensional EoS using a deep-learning-assisted quasi-particle model (DLQPM) within a physics-informed neural networ

R. A. R. Moens, A. G. M. Pietrow, B. Brandl, R. Van de Plas

Mid-infrared astronomy from the ground faces critical challenges in accurately detecting and quantifying sources due to the dominant spatially and time-variable background noise. Moreover, chopping and nodding, the traditional methods for dealing with these background issues, will not be technically feasible on the next generation of extremely large telescop

Dominik Kuczkowski, Laura Ruotsalainen

Monocular visual odometry (VO) is a fundamental computer vision problem with applications in autonomous navigation, augmented reality and more. While deep learning-based methods have recently shown superior accuracy compared to traditional geometric pipelines, particularly in environments where handcrafted features struggle due to poor structure or lighting

Adrián del Pino, David A. Clarke, Carleton DeTar, Aida X. El-Khadra

We present preliminary results from a lattice-QCD study of the hadronic contributions to the running of the electromagnetic coupling, $\Delta\alpha(Q^2)$, and the electroweak mixing angle, $\Delta\sin^2\theta_{W}(Q^2)$. Using $N_f = 2+1+1$ HISQ ensembles at physical quark masses, we discuss the challenges posed by strong statistical correlations in the time-

Nanae Aratake, Taisei Tosaki, Yuji Okamoto, Eiichiro Uchino

Clinical risk prediction using longitudinal medical data supports individualized care. Self-supervised foundation models have emerged as a promising approach for leveraging large-scale unlabeled healthcare records. In natural language processing, scaling laws suggest that larger models achieve predictably lower pretraining losses, supporting the foundation m

Hefeng Zhou, Xuan Liu, Sicheng Chen, Wutong Zhang

Federated cross-modal retrieval faces severe challenges from heterogeneous client data, particularly non-IID semantic distributions and missing modalities. Under such heterogeneity, a single global model is often insufficient to capture both shared cross-modal knowledge and client-specific characteristics. We propose RCSR, a personalization-friendly federate

Soumen Kumar Bera, Taotao Fang, Tapan K. Sasmal, M. Kunert-Bajraszewska

We conducted an extensive identification and analysis of various morphological classes and subclasses of radio galaxies using the latest high-resolution data from the second data release of the LOFAR Two-Metre Sky Survey (LoTSS DR2). This paper presents the first results of our large-scale investigation: a new catalog of ``winged" radio galaxies (WRGs). Thes

Yu Chen, Maria D'Antuono, Robin Hutt, Cesar Magen

Helium focused ion beam irradiation enables the fabrication of tunnel field-effect transistors based on two-dimensional electron systems (2DESs) at an oxide interface.High resolution scanning transmission electron microscopy and strain mapping reveal localized lattice deformation confined to the irradiated regions, which act as nanoscale potential barriers.

Weixu Zhang, Ye Yuan, Changjiang Han, Yuxing Tian

Large Language Models (LLMs) exhibit strong implicit personalization ability, yet most existing approaches treat this behavior as a black box, relying on prompt engineering or fine tuning on user data. In this work, we adopt a mechanistic interpretability perspective and hypothesize the existence of a sparse set of Preference Heads, attention heads that enco

Pavel Šťovíček, Edita Pelantová

We study a class of square matrices with non-negative elements which have cyclically monotone rows in the sense that each row of a matrix from the class consists of a cyclically non-increasing sequence of numbers starting from a maximal element on the diagonal. We prove that if every diagonal element is strictly larger than all other elements in the respecti

Yifan Ke, Chuanjing Zeng, Xinming Qin, Wei-Lin Tu

Understanding the dynamical evolution of large-scale moir\'e systems is crucial for connecting theoretical predictions with experimental observations. Here we develop a machine-learning-based workflow, integrating DeePMD and DeepH frameworks with first-principles calculations, to efficiently investigate time-dependent structural and electronic responses in t

Tamás Csernák, Lajos Soukup

Suppose that pebbles are distributed on the vertices of a graph G. A pebbling step along an edge uv removes two pebbles from u and places one pebble on v. We introduce two new graph parameters: stack(G): the least integer t such that every configuration with t pebbles can be transformed, by a finite sequence of pebbling steps, into a configuration with all p

S. Bellotti, A. D. Sellek, P. Sharda, K. M. Dutkowska

International student mobility plays a critical role in shaping future research careers, particularly in highly globalized fields such as astrophysics. The Leiden/ESA Astrophysics Program for Summer Students (LEAPS) offers a 10-week, fully funded research program at Leiden Observatory and the European Space Agency's ESTEC centre for undergraduate and master'

Fujun Han, Junan Chen, Xintong Zhu, Jingqi Ye

Multimodal Large Language Models (MLLMs) have shown promising potential in diverse understanding tasks, e.g., image and video analysis, math and physics olympiads. However, they remain blank and unexplored for Small Object Understanding (SOU) tasks. To fill this gap, we introduce SOUBench, the first and comprehensive benchmark for exploring the small objects

Yunsong Wang, Gim Hee Lee

Handling the dynamic environments is a significant research challenge in Visual Simultaneous Localization and Mapping (SLAM). Recent research combines 3D Gaussian Splatting (3DGS) with SLAM to achieve both robust camera pose estimation and photorealistic renderings. However, using SLAM to efficiently reconstruct both static and dynamic regions remains challe

Sven Jacob, Bardh Prenkaj, Weijia Shao, Gjergji Kasneci

Most tabular-data generators match marginal statistics yet ignore causal structure, leading downstream models to learn spurious or unfair patterns. We present TabSCM, a mixed-type generator that preserves those causal dependencies. Starting from a Completed Partially Directed Acyclic Graph (CPDAG) found by any causal structure discovery algorithm, TabSCM (i)

Wakutaka Nakano, Ryoto Takai

We propose a quantum-enhanced sensing scheme for the detection of wave-like dark matter and high-frequency gravitational waves using two-dimensional ion crystals in a Penning trap. The protocol employs spin-motion squeezed states to improve the signal-to-noise ratio and enable a super-Heisenberg scaling with respect to the number of ions over a broad paramet

Weixu Zhang, Fanghua Ye, Qiang Gao, Jian Li

Large language models (LLMs) often produce content that contradicts or overlooks information provided in the input context, a phenomenon known as faithfulness hallucination. In this paper, we propose Context-Fidelity Boosting (CFB), a lightweight and general decoding-time framework that reduces such hallucinations by increasing the generation probability of

Louis Martinez, Maks Ovsjanikov

Recent advances in pretraining 3D point cloud encoders (e.g., Point-BERT, Point-MAE) have produced powerful models, whose abilities are typically evaluated on geometric or semantic tasks. At the same time, topological descriptors have been shown to provide informative summaries of a shape's multiscale structure. In this paper we pose the question whether top

Dongwei Sun, Jing Yao, Kan Wei, Xiangyong Cao

Rapid situational awareness is critical in post-disaster response. While remote sensing damage assessment is evolving from pixel-level change detection to high-level semantic analysis, existing vision-language methodologies still struggle to provide actionable intelligence for complex strategic queries. They remain severely constrained by unimodal optical de

Carlisle Casuga, Heikki Mäntysaari

We perform a global analysis of HERA total inclusive cross section and charm quark production data to extract the non-perturbative initial condition for the next-to-leading order Balitsky-Kovchegov (BK) equation. We extend our previous analyses to full next-to-leading order + next-to-leading logarithm (NLO+NLL) accuracy by combining the NLO DIS impact factor

Lomash Relia, Jai G Singla, Amitabh, Nitant Dube

This study analyses simulated and real-world implementations of depth-aware rover navigation, highlighting the transition from stereo vision to monocular depth estimation using edge AI. A Unity-based lunar terrain simulator with stereo cameras and OpenCV's StereoSGBM was used to generate disparity maps. A physical rover built on Raspberry Pi 4 employed UniDe

Xavier Roca-Maza, D. H. Jakubassa-Amundsen

The parity-violating asymmetry, accounting for the vector and axial-vector vertex plus self-energy correction as well as for vacuum polarization, is calculated nonperturbatively by solving the corresponding Dirac equation for the electronic scattering states. Investigating the nuclei $^{27}$Al, $^{48}$Ca and $^{208}$Pb at collision energies in the GeV region

Bao-Qing Wang, Can Shao, Takami Tohyama, Hong-Gang Luo

The emergence of the antiferromagnetic (AFM) Chern insulator (AFCI) phase in the Kane-Mele-Hubbard (KMH) model with a finite sublattice potential is investigated. The AFCI, characterized by AFM correlations coexisting with quantized Hall conductance, has long raised the question of whether it can exist in the KMH model that respects time-reversal symmetry (T

Cinzia Tomaselli, Stefano Covone, Andreagiovanni Reina, Mario di Bernardo

This paper presents a novel control strategy for multi-agent shepherding of non-cohesive targets in obstacle-rich environments. Unlike previous approaches that assume cohesive flocking behavior, our method handles targets that interact only with nearby herders through repulsive forces and exhibit no inter-target coordination. Each herder employs a hybrid con

Rebeka Sarkar, Krishna Kumar, Sugata Pratik Khastgir

The linear and nonlinear motions of a damped rigid planar pendulum, driven by vibrating its pivot sinusoidally, are reexamined. The pendulum is known to exhibit periodic, quasiperiodic, and chaotic motions. Floquet analysis identifies regions of instability and stability within the driving parameter space. A new type of nonlinear oscillation may occur at dri

Fahmida Alam, Ellen Riloff

Existing Natural Language Processing (NLP) resources often lack the task-specific information required for real-world problems and provide limited coverage of lesser-known or newly introduced entities. For example, business organizations and health care providers may need to be classified into a variety of different taxonomic schemes for specific application

Gaoruishu Long, Jinchao Liu, Bo Liu, Jie Liu

Raman spectra obtained in real world applications are often a noisy combination of several spectra of various substances in a tested sample. Unmixing such spectra into individual components corresponding to each of the substances is of great value and has been a longstanding challenge in Raman spectroscopy. Existing unmixing methods are predominantly designe

Davide Dardari

Wave-domain processing is an emerging paradigm where signal processing operations are partially shifted from the digital to the electromagnetic (EM) domain. Leveraging reconfigurable EM devices, this approach aims to reduce complexity, energy consumption, and latency in next-generation wireless systems employing holographic MIMO. This paper establishes funda

Mengyi Wei, Chenyu Zuo, Dongsheng Chen, Liqiu Meng

Public awareness of AI ethics plays a crucial role in fostering the responsible and sustainable development of AI technology. However, finding effective ways to promote public understanding of the ethical risks of AI remains a challenge. Given the complexity of AI ethical issues and the cognitive limitations of the public, this review paper proposes a concep

Xiaolong Lv, Yu Zhang, Yuxuan Wei, Chuanshan Tian

While the Dirac band structure of graphene has established it as a leading platform for ultrafast optoelectronics, its non-perturbative nonlinear response under intense excitation remains poorly understood. Here, we report ultrafast spectral modulation of nonlinear optical signals in graphene. By utilizing a robust suspended-graphene platform that allows for