December 2025 arXiv papers — page 97

Shifu Bie, Jiangxia Cao, Zixiao Luo, Yichuan Zou

We present PushGen, an automated framework for generating high-quality push notifications comparable to human-crafted content. With the rise of generative models, there is growing interest in leveraging LLMs for push content generation. Although LLMs make content generation straightforward and cost-effective, maintaining stylistic control and reliable qualit

Alessia Micieli, Giovanni Maria Farinella, Francesco Ragusa

In this work we present SignIT, a new dataset to study the task of Italian Sign Language (LIS) recognition. The dataset is composed of 644 videos covering 3.33 hours. We manually annotated videos considering a taxonomy of 94 distinct sign classes belonging to 5 macro-categories: Animals, Food, Colors, Emotions and Family. We also extracted 2D keypoints relat

Nadia Abdolkhani, Walaa Hamouda

This paper proposes a hierarchical deep reinforcement learning (DRL) framework based on the soft actor-critic (SAC) algorithm for hybrid underlay-overlay cognitive Internet of Things (CIoT) networks with simultaneous wireless information and power transfer (SWIPT)-energy harvesting (EH) and cooperative caching. Unlike prior hierarchical DRL approaches that f

Yu. Kozitsky

Half a century ago, Ihor Yukhnovskii elaborated a method of studying the critical point of the three-dimensional Ising model based on a layer-by-layer integration in the space of collective variables. His method was an alternative to that based on the $\varepsilon$-expansion for which K. G. Wilson was awarded the Nobel Prize in Physics in 1982. However, Yukh

Lea Bischof, Melanie Ast, Jiang Ji Ho-Zhang, Nicole Knust

Designed to detect gravitational waves in the lower-frequency band, the space mission LISA will open a new window to astronomy after its launch in the 2030s. Each LISA spacecraft houses two optical benches that require the exchange of a phase reference between them via an optical connection, called a Backlink. Here we present the construction and commissioni

Jiang Ji Ho-Zhang, Melanie Ast, Lea Bischof, Michael Born

The current planned space-based gravitational-wave detectors require a bidirectional optical connection, referred to as Backlink, between two adjacent optical benches to provide a mutual phase reference for the local interferometric measurements. However, if the Backlink shows asymmetry between the two propagation directions, the effective optical pathlength

Runze Li, Chaoxi Cui, Ying Liu, Zhi-Ming Yu

An electron beam may experience an anomalous spatial shift during an interface scattering process. Here, we investigate this phenomenon for reflection from mirror-symmetry-protected nodal-ring semimetals, which are characterized by an integer topological charge $\chi_h$. We show that the shift is generally enhanced by the presence of nodal rings, and the rin

A. Pointner, D. Thalheim, S. Belasi, L. Heinen

Nitrogen-vacancy (NV) centers in diamond provide a versatile quantum sensing platform for biological imaging through magnetic field detection, offering unlimited photostability and the ability to perform long-term observations without photobleaching or phototoxicity. However, conventional stage-top incubators are incompatible with the unique requirements for

Shizhuo Mao, Song Chen, Yi Kang

Large language models (LLMs) excel at natural language tasks but face deployment challenges due to their growing size outpacing GPU memory advancements. Model quantization mitigates this issue by lowering weight and activation precision, but existing solutions face fundamental trade-offs: dynamic quantization incurs high computational overhead and poses depl

Weiheng Zhao, Zilong Huang, Jiashi Feng, Xinggang Wang

Contrastive Language-Image Pretraining (CLIP) achieves strong generalization in vision-language tasks by aligning images and texts in a shared embedding space. However, recent findings show that CLIP-like models still underutilize fine-grained semantic signals in text, and this issue becomes even more pronounced when dealing with long and detailed captions.

Stella Boula, Apostolos Mastichiadis, Demosthenes Kazanas

Blazars, a subclass of radio-loud active galactic nuclei with relativistic jets aligned close to our line of sight, emit highly variable non-thermal radiation across the electromagnetic spectrum. The physical origin of their emission and the blazar sequence remain open questions. We present a self-consistent two-zone leptonic model in which relativistic elec

Andreas Sjölander, Valeria Belloni, Robel Fekadu, Andrea Nascetti

Tunnels are essential elements of transportation infrastructure, but are increasingly affected by ageing and deterioration mechanisms such as cracking. Regular inspections are required to ensure their safety, yet traditional manual procedures are time-consuming, subjective, and costly. Recent advances in mobile mapping systems and Deep Learning (DL) enable a

Erwin Walter, John P. Farmer, Marlene Turner, Frank Jenko

Several different schemes for plasma wakefield acceleration using a train of drivers have been pursued, based on the resonant excitation of a plasma wave. Since these schemes rely on the plasma electron wave surviving for many periods, the motion of the plasma ions can have a significant impact on the beam--plasma interaction. In this work, simulations are u

Johann Glock, Clemens Bauer, Martin Pinzger

Conventional unit tests validate single input-output pairs, leaving most inputs of an execution path untested. Property-based testing addresses this shortcoming by generating multiple inputs satisfying properties but requires significant manual effort to define properties and their constraints. We propose a semantics-based approach that automatically transfo

Annu Rana, Gaurav Kumar

Large Language Models (LLMs) often struggle with complex multi-step planning tasks, showing high rates of constraint violations and inconsistent solutions. Existing strategies such as Chain-of-Thought and ReAct rely on implicit state tracking and lack an explicit problem representation. Inspired by classical AI planning, we propose Model-First Reasoning (MFR

Ricardo Hueso, Leigh N. Fletcher, Damya Souami, Thierry Fouchet

The Extremely Large Telescope (ELT) will transform our knowledge of the outer planets and their satellite systems; however the visibility of unique targets of opportunity with high scientific value will be reduced for northern objects. Uranus' declination favors observations from the Northern Hemisphere until 2055, and Neptune will be favored from the Northe

Zelin Li, Guoye Guan, Xiu Xian, Dongying Xie

Deep learning segmentation and fluorescence imaging techniques allow the cellular morphology of living embryos to be constructed spatiotemporally. These development processes involve numerous molecules distributed at the subcellular scale, such as cell adhesion (E-cadherin), which accumulate at cell-cell interfaces to regulate intercellular connection. Howev

Additi Pandey, Liang Wei, Hessam Babaee, George Em Karniadakis

Accurate chemical kinetics modeling is essential for combustion simulations, as it governs the evolution of complex reaction pathways and thermochemical states. In this work, we introduce Kinetic-Mamba, a Mamba-based neural operator framework that integrates the expressive power of neural operators with the efficient temporal modeling capabilities of Mamba a

C. Esteban, J. M. Vilchez, J. García-Rojas, R. Amorín

Star-forming dwarf galaxies in the local Universe, especially extremely metal-poor ones, can be considered analogous to early galaxies of the Epoch of Reionization (z >= 6). Currently available telescopes cannot adequately detect and measure heavy element recombination lines and certain faint collisionally excited lines, which are essential for exploring the

Borja Anguiano, David Valls-Gabaud, Guillaume F. Thomas, David Martínez Delgado

By the 2040s--50s, facilities such as \emph{Gaia}, WEAVE, 4MOST, Rubin, \emph{Euclid}, \emph{Roman}, and the ESO ELT will have transformed our global view of the Milky Way. Yet key questions will remain incompletely resolved: a detailed reconstruction of the Galaxy's assembly from its earliest building blocks, and robust tests of dark matter granularity usin

C. Gallart, E. Fernández-Alvar, A. B. A. Queiroz, A. Aparicio

A 30 m class optical/near-IR telescope in the Northern Hemisphere, equipped for diffraction-limited imaging and high-resolution, multi-object spectroscopy of faint stars, would enable a transformational investigation of the formation and evolution of M31 and its satellite system - on par with what Gaia, the HST, and other major photometric and spectroscopic

Miriam Garcia, Artemio Herrero, Ignacio Negueruela, Norberto Castro

Massive stars are at the core of our observations of the Universe up to the reionization epoch, both through their intense ionizing fluxes and through the energetic end products that release fresh elements into the interstellar medium. Our interpretation of very high redshift galaxies and transient phenomena depends on knowledge derived from massive star pop

Francesca Pinna, Isabel Pérez, Anna Ferré-Mateu, Begoña García Lorenzo

Nuclear star clusters (NSCs) are dense, compact stellar systems only a few parsecs across, located at galaxy centers. Their small sizes make them difficult to resolve spatially. NSCs often coexist with massive black holes, and both trace the dynamical state and evolution of their host galaxies. Dense stellar environments such as NSCs are also ideal sites for

Piercosma Bisconti, Marcello Galisai, Matteo Prandi, Federico Pierucci

Safety mechanisms in LLMs remain vulnerable to attacks that reframe harmful requests through culturally coded structures. We introduce Adversarial Tales, a jailbreak technique that embeds harmful content within cyberpunk narratives and prompts models to perform functional analysis inspired by Vladimir Propp's morphology of folktales. By casting the task as s

F. Coti Zelati, P. G. Jonker, C. P. Gutiérrez, S. Mattila

We outline the science case for a 30-40 m optical/infrared telescope in the Northern Hemisphere, optimised for transformative time-domain astronomy in the 2040s. Upcoming multi-wavelength and multi-messenger facilities will reveal fast, faint, rapidly evolving Northern transients whose earliest phases carry decisive diagnostics. A Northern ELT with rapid res

J. de León, N. Pinilla-Alonso, P. Tanga, D. Souami

Small Solar system Objects (SSOs) preserve the physical, chemical, and dynamical signatures of the Sun's protoplanetary disk. Upcoming surveys will discover vast numbers of new objects, yet their scientific value will depend on follow-up observations requiring far greater sensitivity and resolution than those currently available. A 30-m class telescope like

Anwesh Ray

In the first part of the paper, we fix a non-CM elliptic curve $E/\mathbb{Q}$ and an odd prime $\ell$ and investigate the distribution of invariants associated to the $\ell$-volcano containing the reduction $E_p$, as $p$ ranges over primes of good ordinary reduction. Let $H(p)$ be the height of the volcano and let $d'(p)$ denote the relative position of $j(E

Mireia Montes, Ignacio Trujillo, David Martínez Delgado, Borja Anguiano

The Extragalactic Low Surface Brightness (LSB, $\mu_V\gtrsim 27$ mag/arcsec$^2$) Universe represents a crucial, yet largely unseen, frontier in modern astrophysics. This faint realm holds the keys to completing our understanding of galaxy evolution, hierarchical assembly, and even the fundamental nature of dark matter. Our current theoretical models are inhe

J. Alfonso L. Aguerri, Jesús Falcón-Barroso, María Argudo-Fernández, Yago Ascasibar

Dwarf galaxies dominate the galaxy population in the nearby Universe and occupy the regime where feedback, reionization, and environment exert their strongest influence on galaxy formation. Despite their importance, detailed spectroscopic constraints on the faintest dwarfs are currently limited to a handful of systems in the Local Volume, leaving the role of

I. Mendigutía, N. Huélamo, I. Jiménez-Serra, E. Villaver

The detection and characterization of protoplanets in protoplanetary disks around young stars is emerging as a transformative field that will redefine our understanding of how planetary systems form. While current facilities have revealed the diversity of mature exoplanets and the complex structures of disks, we still lack the crucial observational link betw

Pablo G. Pérez-González, Roberto Maiolino, Pascal A. Oesch, Alvio Renzini

Full sky coverage with 30-40 meter-class telescopes is essential to answer fundamental questions in Astrophysics, Cosmology, and Physics, such as the composition of the Universe and the formation of the first stars and supermassive black holes. An ELT/TMT-like telescope in the Northern Hemisphere is a fundamental and necessary facility to provide multiplexin

Xinhua Shen, Hongpeng Sun

Nonconvex optimization problems are widespread in modern machine learning and data science. We introduce an extrapolation strategy into a class of preconditioned second-order convex splitting algorithms for nonconvex optimization problems. The proposed algorithms combine second-order backward differentiation formulas (BDF2) with an extrapolation method. Mean

A. Vazdekis, P. Sánchez-Blázquez, A. Ferré-Mateu, I. Martín-Navarro

This white paper highlights how stellar population gradients, chemical abundance patterns, stellar initial mass function (IMF) variations, and structural signatures in early-type galaxies (ETGs), measured at faint and large galactocentric radii, out to $\sim4R_e$, provide powerful diagnostics of their formation and evolutionary histories. These observables e

Tomoaki Abuku, Alda Carvalho, Urban Larsson, Richard J. Nowakowski

In an impartial combinatorial game, both players have the same options in the game and all its subpositions. The classical Sprague-Grundy Theory was developed for short impartial games, where players have a finite number of options, there are no special moves, and an infinite run is not possible. Subsequently, many generalizations have been proposed, particu

Siyuan Zhu, Chengdong Xu, Kaiqiang Ke, Chao Yu

In long-context question answering, selecting the appropriate scope of context for a query remains a key and unresolved challenge. Insufficient context can lead to missing essential information, whereas excessive context often introduces noise and degrades answer quality. Conventional methods, such as retrieving a fixed number of passages or applying reranki

Sujoy Chakraborty, Saurav Holme Choudhury

Let $C$ be an irreducible smooth projective curve of genus $g\geq 2$ over an algebraically closed field. We prove that the moduli stack of semi-stable vector bundles on $C$ of fixed rank and determinant is $\mathbb{A}^1$--connected. We also show that the moduli stack of quasi-parabolic vector bundles with a fixed determinant and a given quasi-parabolic data

M. L. Mays, P. J. MacNeice, A. Taktakishvili, C. P. Wiegand

The purpose of this project was to assess improvements in CME arrival time forecasts at Earth using the Air Force Data Assimilative Photospheric Flux Transport (ADAPT) model driven by data from the Global Oscillation Network Group (GONG) ground observatories. These outputs are then fed into the coupled Wang-Sheeley-Arge (WSA) - ENLIL model and compared to an

Arianna Nigioni, Diego Turrini, Camilla Danielski, Danae Polychroni

Planetary formation might occur at different stages of the stellar evolution of compact binaries. In recent years, the formation of second-generation planets has been tested in circumbinary discs formed by the ejection of stellar material from double white dwarf (DWD) binaries. In these environments, planets ranging from sub-Neptunian to giant masses can for

Sky Semone, Matthew J. Brandsema, Thang Hoang, Christos Argyropoulos

Plasmonic metasurfaces have emerged as a promising platform for enhancing a range of nonlinear optical processes, offering compact geometry and flexibility in light manipulation. Second order nonlinear processes, like second harmonic generation (SHG), typically require non-centrosymmetric crystals to be realized. Here, we experimentally demonstrate enhanced

G. Blázquez-Calero, G. Anglada, S. Cabrit, M. Osorio

Outflows play a key role in the star and planet formation processes. Some outflows show discrete clumps of cold molecular gas moving at extremely high velocities (EHVs) of $\sim$100 km s$^{-1}$, known as ''molecular bullets'', that are likely closely associated with their primary driving agent. Here we present ALMA CO(J=3-2) observations of a bright EHV mole

Jingyang Zhao, Mingyu Xiao

Given a complete graph with $n$ vertices and non-negative edge weights, where $n$ is divisible by 3, the maximum weight 3-path packing problem is to find a set of $n/3$ vertex-disjoint 3-paths such that the total weight of the 3-paths in the packing is maximized. This problem is closely related to the classic maximum weight matching problem. In this paper, w

Jong In Han, Sijong Kwak, Wanseok Lee

The classical results, initiated by Castelnuovo and Fano and later refined by Eisenbud and Harris, provide several upper bounds on the number of quadrics defining a nondegenerate projective variety. Recently, it has been revealed that these bounds extend naturally to certain linear syzygies, suggesting the presence of a hierarchical structure governing the q

Fabiola Moyón, Florian Angermeir, Daniel Mendez, Tony Gorschek

Companies adopt agile methodologies and DevOps to facilitate efficient development and deployment of software-intensive products. This, in turn, introduces challenges in relation to security standard compliance traditionally following a more linear workflow. This is especially a challenge for the engineering of products and services associated with critical

Helene Wetter, Jan Wingenbach, Falk Rehberg, Wenlong Gao

Metasurfaces are a powerful tool for manipulating light using small structures on the nanoscale. In most meta-surfaces, near-field couplings are treated as unfavorable perturbations. Here, we experimentally investigate a structure consisting of sinusoidally modulated silicon waveguides where near-field coupling of local resonances leads to negative coupling,

Gil Serrano, Marcelo Jacinto, Bruno J. Guerreiro, Rita Cunha

This work addresses the problem of designing an equivariant observer for a first order dynamical system on the unit-sphere. Building upon the established case of unit bearing vector dynamics with angular velocity inputs, we introduce an additional linear velocity input projected onto the unit-sphere tangent space. This extended formulation is particularly us

Riccardo Busetto, Elia Cereda, Marco Forgione, Gabriele Maroni

We introduce a benchmark for system identification based on 75k real-world samples from the Crazyflie 2.1 Brushless nano-quadrotor, a sub-50g aerial vehicle widely adopted in robotics research. The platform presents a challenging testbed due to its multi-input, multi-output nature, open-loop instability, and nonlinear dynamics under agile maneuvers. The data

Sean Thrasher, Ioannis Kolotouros, Julien Michel, Petros Wallden

Quantum computing promises to efficiently and accurately solve many important problems in quantum chemistry which elude classical solvers, such as the electronic structure problem of highly correlated materials. Two leading methods in solving the ground state problem are the Variational Quantum Eigensolver (VQE) and Adiabatic Quantum Computing (AQC) algorith

Xingfu Zhou, Pengfei Wang

Large Language Model (LLM) agents relying on external retrieval are increasingly deployed in high-stakes environments. While existing adversarial attacks primarily focus on content falsification or instruction injection, we identify a novel, process-oriented attack surface: the agent's reasoning style. We propose Reasoning-Style Poisoning (RSP), a paradigm t

I. Wischnevsky Shlush, A. Denniston, R. Wagner, I. Korover

Short-range correlated (SRC) nucleon pairs provide a sensitive probe of the short-distance structure of atomic nuclei and the underlying nucleon-nucleon (NN) interaction. We present a simple numerical method to estimate the number of two- and three-nucleon SRC clusters using an independent-particle shell model with a harmonic-oscillator basis. The relative a

Marco Moriconi

We present a geometric proof of the invariance of the relativistic spacetime interval based solely on the constancy of the speed of light, and the homogeneity and isotropy of spacetime. The derivation is based on a simple construction involving light rectangles, whose areas remain invariant across inertial frames. Based on this construction, we also derive t

Brenton Walker, Markus Fidler

In some models of parallel computation, jobs are split into smaller tasks and can be executed completely asynchronously. In other situations the parallel tasks have constraints that require them to synchronize their start and possibly departure times. This is true of many parallelized machine learning workloads, and the popular Apache Spark processing engine

Akira Takeshima, Kenta Shiraishi, Atsushi Okazaki, Tadashi Tsuyuki

While machine learning-based weather prediction (MLWP) has achieved significant advancements, research on assimilating real observations or ensemble forecasts within MLWP models remains limited. We introduce ClimaX-LETKF, the first purely data-driven ML-based ensemble weather forecasting system. It operates stably over multiple years, independently of numeri

Sharvari Kamble, Arjun Dangle, Gargi Khurud, Om Kendre

Indian Railway workshops form the backbone of rolling-stock maintenance, employing over 250,000 workers across 44 major workshops nationwide. Despite their scale and operational importance, workshop safety remains a persistent challenge. A field study conducted at the Jhansi Wagon Workshop involving 309 workers revealed that while basic protective equipment

Arnaud Pierens, Thomas Collin-Dufresne, Min-Kai Lin, Emmanuel DiFolco

The streaming instability is considered one of the leading candidates for the formation of planetesimals, due to its ability to overcome the bouncing and fragmentation barriers. The formation of dense dust clumps through this process, however, is possible provided it involves solids with dimensionless stopping times $\sim 0.1$ in standard discs, which typica

Zixin Zhang, Kanghao Chen, Hanqing Wang, Hongfei Zhang

Affordance prediction, which identifies interaction regions on objects based on language instructions, is critical for embodied AI. Prevailing end-to-end models couple high-level reasoning and low-level grounding into a single monolithic pipeline and rely on training over annotated datasets, which leads to poor generalization on novel objects and unseen envi

S. Muller, A. Beelen, M. Guelin, J. H. Black

Absorption spectroscopy toward high-redshift quasars provides strong constraints on the putative variation of fundamental constants of physics on cosmological time scales. The submillimeter ground-state transitions of methylidyne (CH) and water (H2O), both molecules widespread and coeval in the interstellar medium, provide a sensitive test for variations of

Félix Mortas

This paper quantifies the carbon emissions related to data consumption during video calls, focusing on the impact of having the camera on versus off. The findings regarding the environmental benefits achieved by turning off cameras during meetings challenge the claims of some prevalent articles. The experiment was carried out using a 4G connection via a cell

Leon Sick, Lukas Hoyer, Dominik Engel, Pedro Hermosilla

In recent years, the state-of-the-art in unsupervised video instance segmentation has heavily relied on synthetic video data, generated from object-centric image datasets such as ImageNet. However, video synthesis by artificially shifting and scaling image instance masks fails to accurately model realistic motion in videos, such as perspective changes, movem

Quan Yuan, Zhikun Zhang, Linkang Du, Min Chen

Video recognition systems are increasingly being deployed in daily life, such as content recommendation and security monitoring. To enhance video recognition development, many institutions have released high-quality public datasets with open-source licenses for training advanced models. At the same time, these datasets are also susceptible to misuse and infr

Xavier Gonze, Christian Tantardini, Antoine Levitt

The temperature dependence of most solid-state properties is dominated by lattice vibrations, but metals display notable purely electronic effects at low temperature, such as the linear specific heat and the linear entropy, that were derived by Sommerfeld for the non-interacting electron gas via the low-temperature expansion of Fermi-Dirac integrals. Here we

Jiahui Liang, Wenlihan Lu, Tianyi Liu, Kang Kang

In intelligent low-altitude networks, integrating monitoring tasks into communication unmanned aerial vehicles (UAVs) can consume resources and increase handoff latency for communication links. To address this challenge, we propose a strategy that enables a "double use" of UAVs, unifying the monitoring and relay handoff functions into a single, efficient pro

Quan Yuan, Daqian Cao, Weibang Bai

Redundant parallel robots are normally employed in scenarios requiring good precision, high load capability, and large workspace compared to traditional parallel mechanisms. However, the elementary robotic configuration and geometric parameter optimization are still quite challenging. This paper proposes a novel 3-(PP(2-(UPS))) redundant parallel mechanism,

Zihao Lv, Siqi Ai, Yanbin Zhang

Targeted maintenance strategies, ensuring the dependability and safety of industrial machinery. However, current modeling techniques for assessing both local and global correlation of battery degradation sequences are inefficient and difficult to meet the needs in real-life applications. For this reason, we propose a novel deep learning architecture, multisc

Zhuoran Li, Zhen Gao, Sheng Chen, Dusit Niyato

This paper introduces a sensing-centric joint communication and millimeter-wave radar paradigm to facilitate collaboration among intelligent vehicles. We first propose a chirp waveform-based delay-Doppler quadrature amplitude modulation (DD-QAM) that modulates data across delay, Doppler, and amplitude dimensions. Building upon this modulation scheme, we deri

Alan Price

The proposed fixed-target experiment, MUonE, at CERN will aim to measure the hadronic contribution to the running of the QED coupling by analysing the scattering of muons on electrons. Here we present state-of-the-art predictions for the process $\mu^{\pm}e^-\rightarrow\mu^{\pm}e^-$, where for the first time an all-order resummation of soft and soft-collinea

Zhuowen Guo, Jiahao Qiu, Hui Xu, Xiangdong Ye

Let $A\subset \mathbb{N}$. We say $A$ is an $R$-sequence for a given minimal system $(Y,S)$ if there is $y\in Y$ such that $\{S^ny:n\in A\}$ is dense in $Y$. Richter asked if $A$ is an $R$-sequence for all minimal equicontinuous systems implies that $A$ is an $R$-sequence for all minimal systems. In this paper, we investigate this question and related issues

Yukun Ren, Siwei Yu, Kai Chen, Jianwei Ma

To address the steep learning curve and reliance on complex manual file editing and command-line operations in the traditional workflow of the mainstream open-source seismic wave simulation software SPECFEM, this paper proposes an intelligent, interactive workflow powered by Large Language Models (LLMs). We introduce the first Model Context Protocol (MCP) se

Gabriele Prato, Shagun Sodhani, Alessandro Sordoni, Sarath Chandar

The standard practice for training large language models involves packing multiple documents together to optimize computational efficiency. However, the impact of this process on the models' capabilities remains largely unexplored. To address this gap, we investigate how different document-packing strategies influence the latent multi-hop reasoning abilities

Simon Steuernagel, Marcus Baum

Extended object tracking involves estimating both the physical extent and kinematic parameters of a target object, where typically multiple measurements are observed per time step. In this article, we propose a deterministic closed-form elliptical extended object tracker, based on decoupling of the kinematics, orientation, and axis lengths. By disregarding p

Boyang Wang, Yash Vishe, Xin Xu, Zachary Novack

Natural language information needs over symbolic music scores rarely reduce to a single step lookup. Many queries require compositional Music Information Retrieval (MIR) that extracts multiple pieces of evidence from structured notation and aggregates them to answer the question. This setting remains challenging for Large Language Models due to the mismatch

Hosna Hooshyar, Mattia Fumagalli, Marco Montali, Giancarlo Guizzardi

Object-centric process mining is a new branch of process mining where events are associated with multiple objects, and where object-to-object interactions are essential to understand the process dynamics. Traditional event data models, also called case-centric, are unable to cope with the complexity introduced by these more refined relationships. Several mod

Yewen Cao, Yulin Shao

The advancement to 6G calls for waveforms that transcend static robustness to achieve intelligent adaptability. Affine Frequency Division Multiplexing (AFDM), despite its strength in doubly-dispersive channels, has been confined by chirp parameters optimized for worst-case scenarios. This paper shatters this limitation with Agile-AFDM, a novel framework that

Zhuo Chen, Fanyue Wei, Runze Xu, Jingjing Li

Training-free image editing with large diffusion models has become practical, yet faithfully performing complex non-rigid edits (e.g., pose or shape changes) remains highly challenging. We identify a key underlying cause: attention collapse in existing attention sharing mechanisms, where either positional embeddings or semantic features dominate visual conte

Kornelius Raeth, Nicole Ludwig

Standard weather forecast evaluations focus on the forecaster's perspective and on a statistical assessment comparing forecasts and observations. In practice, however, forecasts are used to make decisions, so it seems natural to take the decision-maker's perspective and quantify the value of a forecast by its ability to improve decision-making. Decis

Waqas Ahmed

The cybersecurity of Industrial Control Systems that manage critical infrastructure such as Water Distribution Systems has become increasingly important as digital connectivity expands. BATADAL benchmark data is a good source of testing intrusion detection techniques, but it presents several important problems, such as imbalance in the number of classes, mul

Mischa Dombrowski, Felix Nützel, Bernhard Kainz

Recent advances in generative image modeling have achieved visual realism sufficient to deceive human experts, yet their potential for privacy preserving data sharing remains insufficiently understood. A central obstacle is the absence of reliable memorization detection mechanisms, limited quantitative evaluation, and poor generalization of existing privacy

Nakamasa Inoue, Kanoko Goto, Masanari Oi, Martyna Gruszka

Large vision-language models (LVLMs) have shown impressive performance across a broad range of multimodal tasks. However, robust image caption evaluation using LVLMs remains challenging, particularly under domain-shift scenarios. To address this issue, we introduce the Distribution-Aware Score Decoder (DISCODE), a novel finetuning-free method that generates

Xiaoqi Ma, Jin Zhang

This paper introduces a unified analysis framework of equal-order hybridized discontinuous finite element (HDG) methods. The general framework covers standard HDG, embedded discontinuous finite element, and embedded-hybridized discontinuous finite element methods.

Dejun Hu, Zhiming Li, Jia-Rui Shen, Jia-Ning Tu

Machine learning is profoundly reshaping molecular and materials modeling; however, given the vast scale of chemical space (10^30-10^60), it remains an open scientific question whether models can achieve convergent learning across this space. We introduce a Dual-Axis Representation-Complete Convergent Learning (RCCL) strategy, enabled by a molecular represen

Jia Hu, Junqi Li, Weimeng Lin, Peng Jia

Vehicle Dispatching Systems (VDSs) are critical to the operational efficiency of Automated Container Terminals (ACTs). However, their widespread commercialization is hindered due to their low transferability across diverse terminals. This transferability challenge stems from three limitations: high reliance on port operational specialists, a high demand for

Björn Liljegren-Sailer

Model order reduction seeks to approximate large-scale dynamical systems by lower-dimensional reduced models. For linear systems, a small reduced dimension directly translates into low computational cost, ensuring online efficiency. This property does not generally hold for nonlinear systems, where an additional approximation of nonlinear terms -- known as c

Hongyu Chen, Yangfeng Fu, Weiqiang Yu, Rong Yu

We propose a single-layer tensor network framework for the variational determination of ground states in two-dimensional quantum lattice models. By combining the nested tensor network method [Phys. Rev. B 96, 045128 (2017)] with the automatic differentiation technique, our approach can reduce the computational cost by three orders of magnitude in bond dimens

Aymen Echarghaoui, Robert Tibshirani

We propose a procedure for sparse regression with pairwise interactions, by generalizing the Univariate Guided Sparse Regression (UniLasso) methodology. A central contribution is our introduction of a concept of univariate (or marginal) interactions. Using this concept, we propose two algorithms -- uniPairs and uniPairs-2stage -- , and evaluate their perform

Gil Serrano, Pedro Lourenço, Bruno J. Guerreiro, Rita Cunha

Rendezvous and docking between a chaser spacecraft and an uncooperative target, such as an inoperative satellite, require synchronization between the chaser spacecraft and the target. In these scenarios, the chaser must estimate the relative attitude and angular velocity of the target using onboard sensors, in the presence of gyroscope bias. In this work, we

Mohammed Ayman Habib, Aldo Petruzzelli

Omnia presents a synthetic data driven pipeline to accelerate the training, validation, and deployment readiness of militarized humanoids. The approach converts first-person spatial observations captured from point-of-view recordings, smart glasses, augmented reality headsets, and spatial browsing workflows into scalable, mission-specific synthetic datasets

Muhammad Sukri Bin Ramli

As the global economy transitions toward decarbonization, the aluminium sector has become a focal point for strategic resource management. While policies such as the Carbon Border Adjustment Mechanism (CBAM) aim to reduce emissions, they have inadvertently widened the price arbitrage between primary metal, scrap, and semi-finished goods, creating new incenti

Michelle Döring, Jannes Malanowski, Stefan Neubert

Recently, the River Method was introduced as novel refinement of the Split Cycle voting rule. The decision-making process of River is closely related to the well established Ranked Pairs Method. Both methods consider a margin graph computed from the voters' preferences and eliminate majority cycles in that graph to choose a winner. As ties can occur in the m

Alessandro Fasano, Mateo Fernández-Torreiro, Guillermo Pascual-Cisneros, Roger John Hoyland

Our objective is to characterize the QUIJOTE Thirty and Forty GHz instrument (TFGI), calibrate it with a reference calibration signal on the ground, compare our results with on-sky calibration based on bright sources, and study the stability of the calibration parameters over time. First, from the ground, we fit the data using a reference calibration signal

Le Jiang, Shaotong Zhu, Yedi Luo, Shayda Moezzi

In dynamic Neural Radiance Fields (NeRF) systems, state-of-the-art novel view synthesis methods often fail under significant viewpoint deviations, producing unstable and unrealistic renderings. To address this, we introduce Expanded Dynamic NeRF (ExpanDyNeRF), a monocular NeRF framework that leverages Gaussian splatting priors and a pseudo-ground-truth gener

Mateusz Kuniej, Paweł Machnikowski, Michał Gawełczyk

Mechanical degrees of freedom very weakly couple to spins in semiconductors. The inefficient coupling between phonons and single electron spins in semiconductor quantum dots (QDs) hinders their integration into on-chip acoustically coupled quantum hybrid systems. We propose a hybrid acousto-optical spin control method that circumvents this problem and effect

Hangjun Cho, Fabio V. G. Amaral, Andrei A. Klishin, Cassio M. Oishi

In this work, we revisit dictionary-based sparse regression, in particular, Sequential Threshold Least Squares (STLS), and propose a score-guided library selection to provide practical guidance for data-driven modeling, with emphasis on SINDy-type algorithms. STLS is an algorithm to solve the $\ell_0$ sparse least-squares problem, which relies on splitting t

Jeck Lim, Akshat Mudgal, Cosmin Pohoata, Xuancheng Shao

The exponential Freiman dimension of a finite set $A \subset \mathbb{R}^{m}$, introduced by Green and Tao in 2006, represents the largest positive integer $d$ for which $A$ contains the vertices of a non-degenerate $d$-dimensional parallelepiped. For every $d \geq 1$, we precisely determine the largest constant $C_{d}>0$ (exponential in $d$) for which $$|A+A

Anuj Kumar Singh, Parul Sharma, Kishor Kumar Mandal, Lekshmi Eswaramoorthy

Single-photon emitters (SPEs) constitute a foundational resource for quantum technologies, including secure communication, photonic quantum computing, and emerging quantum network architectures. A wide range of quantum materials, from atom-like point defects in bulk crystals to excitonic states in low-dimensional semiconductors, now provide bright, coherent,

Minbo Yang, Shunneng Zhao

In this paper, we are concerned with the critical elliptic equation \begin{equation}\label{kx} \left\lbrace\begin{aligned} &-\Delta u=u^{p}+\epsilon \kappa(x)u^{q}\quad\hspace{2mm} \mbox{in}~~\Omega, \\&u>0\quad \quad\quad\quad\quad\quad\quad\quad\hspace{1mm}\hspace{0.5mm}~\mbox{in}~~\Omega \\&u=0\quad \quad\quad\quad\quad\quad\quad\quad\hspace{1mm}\hspace{0

Fangzhou Lin, Guoshun He, Zhenyu Guo, Zhe Huang

Electric load is simultaneously affected across multiple time scales by exogenous factors such as weather and calendar rhythms, sudden events, and policies. Therefore, this paper proposes GRAFT (GRid-Aware Forecasting with Text), which modifies and improves STanHOP to better support grid-aware forecasting and multi-source textual interventions. Specifically,

Dániel Pfeifer, Edith Alice Kovács

Vine copula models have become highly popular and practical tools for modelling multivariate probability distributions due to their flexibility in modelling different kinds of dependences between the random variables involved. However, their flexibility comes with the drawback of a high-dimensional parameter space. To tackle this problem, truncated vine copu

Gang Zhao, Su Wang, Jiangpei Dou

We investigate the crucial role of self-gravity in the formation of warps in debris disks, focusing on the HD 110058 system as an example. Using advanced, GPU-accelerated $N$-body simulations, we model the gravitational dynamics of a massive planetesimal disk perturbed by an inclined, inner planet. Our simulations reveal that self-gravity fundamentally alter

Yunjia Yang, Weishao Tang, Mengxin Liu, Nils Thuerey

Machine-learning surrogate models have shown promise in accelerating aerodynamic design, yet progress toward generalizable predictors for three-dimensional wings has been limited by the scarcity and restricted diversity of existing datasets. Here, we present SuperWing, a comprehensive open dataset of transonic swept-wing aerodynamics comprising 4,239 paramet

Marvin Leusch, Alessandro Toschi, Andreas Hausoel, Giorgio Sangiovanni

We analyze the impact of the lattice geometry on the thermodynamic transition to magnetically ordered phases in strongly interacting electron systems for various Bravais lattices in three, four and five dimensions, including both local and nonlocal correlation effects. In a first step we use the dynamical mean-field theory (DMFT), which takes into account pu

Wentao Wan, Qiqing Lao, Zhiwei Xie, Hefeng Wu

Knowledge Editing (KE) is a field that studies how to modify some knowledge in Large Language Models (LLMs) at a low cost (compared to pre-training). Currently, performing large-scale edits on LLMs while ensuring the Reliability, Generality, and Locality metrics of the edits remain a challenge. This paper proposes a Massive editing approach for LLMs based on