November 2025 arXiv papers — page 178

Mathias Lundteigen Mohus, Jingyue Li, Zhirong Yang

The widespread adoption of generative models such as Stable Diffusion and ChatGPT has made them increasingly attractive targets for malicious exploitation, particularly through data poisoning. Existing poisoning attacks compromising synthesised data typically either cause broad degradation of generated data or require control over the training process, limit

Soham Chatterjee, Prahladh Harsha, Mrinal Kumar

We show that Reed-Solomon codes of dimension $k$ and block length $n$ over any finite field $\mathbb{F}$ can be deterministically list decoded from agreement $\sqrt{(k-1)n}$ in time $\text{poly}(n, \log |\mathbb{F}|)$. Prior to this work, the list decoding algorithms for Reed-Solomon codes, from the celebrated results of Sudan and Guruswami-Sudan, were eithe

A. B. Nechaeva, I. V. Zimovets, I. N. Sharykin, S. A. Anfinogentov

This work investigates the decayless kink oscillations of solar coronal loops and examines possible changes in their behaviour in active regions (ARs) before powerful solar flares (M- and X-class) and in the absence of powerful flares. To this end, we analysed 14 ARs with powerful flares and 14 ARs without powerful flares. For each event, images obtained in

Meetu Verma, Carsten Denker, Alexander G. M. Pietrow, Robert Kamlah

The center-to-limb variations (CLVs) of photospheric and chromospheric spectral lines were obtained in 2025 July and August using drift scans from the echelle spectrograph of the 0.7 m Vacuum Tower Telescope at the Observatorio del Teide (ODT) in Tenerife, Spain. This instrument can observe four spectral regions simultaneously, enabling multi-line spectrosco

Sushil Kumar, Soumya P. Dash, George C. Alexandropoulos

This paper considers a multiple-input multiple-output (MIMO) wireless system wherein two legitimate users attempt to exchange secret keys over free-space optical (FSO) channels. Novel frameworks for the use of the one- and two-way discrete-variable quantum key distribution (DV-QKD) protocols, employing weak coherent pulses and decoy states, are presented. Fo

P. Schulte, D. Wenz, L. Althueser, R. Braun

This manuscript details the proof-of-concept of a small-scale cryogenic heat pump demonstrator, a technology designed to enable high-flow xenon distillation systems for the removal of $^{222}$Rn in future liquid xenon observatories such as the XLZD experiment. The heat pump demonstrator operates on a left-turning Clausius-Rankine cycle, utilizing xenon as a

Davide Marincione, Donato Crisostomi, Roberto Dessi, Emanuele Rodolà

Foundation models capable of generalizing across species and tasks represent a promising new frontier in bioacoustics, with NatureLM being one of the most prominent examples. While its domain-specific fine-tuning yields strong performance on bioacoustic benchmarks, we observe that it also introduces trade-offs in instruction-following flexibility. For instan

Zijiang Yang, Hanqing Chao, Bokai Zhao, Yelin Yang

Nucleus detection and classification (NDC) in histopathology analysis is a fundamental task that underpins a wide range of high-level pathology applications. However, existing methods heavily rely on labor-intensive nucleus-level annotations and struggle to fully exploit large-scale unlabeled data for learning discriminative nucleus representations. In this

Simon Baur, Tristan Ruhwedel, Ekin Böke, Zuzanna Kobus

Peptide receptor radionuclide therapy (PRRT) is an established treatment for metastatic neuroendocrine tumors (NETs), yet long-term disease control occurs only in a subset of patients. Predicting progression-free survival (PFS) could support individualized treatment planning. This study evaluates laboratory, imaging, and multimodal deep learning models for P

Alexander Lappe, Martin A. Giese

Vision foundation models achieve strong performance on both global and locally dense downstream tasks. Pretrained on large images, the recent DINOv3 model family is able to produce very fine-grained dense feature maps, enabling state-of-the-art performance. However, computing these feature maps requires the input image to be available at very high resolution

Franz G. Mertens, Bernardo Sánchez-Rey, Niurka R. Quintero

We investigate the effects on solitons dynamics of introducing a PT-symmetric complex potential in a specific family of the cubic Dirac equation in (1+1)-dimensions, called the ABS model. The potential is introduced taking advantage of the fact that the nonlinear Dirac equation admits a Lagrangian formalism. As a consequence, the imaginary part of the potent

Ahmad Hatahet, Christoph Knieke, Andreas Rausch

Software Architecture Descriptions (SADs) are essential for managing the inherent complexity of modern software systems. They enable high-level architectural reasoning, guide design decisions, and facilitate effective communication among diverse stakeholders. However, in practice, SADs are often missing, outdated, or poorly aligned with the system's actual i

Marco Antonio Pellegrini, Lorenzo Schena

A representation $\Phi: G \to \mathrm{GL}_n(\mathbb{F})$ of a finite group $G$ is called unisingular if the matrix $\Phi(g)$ admits $1$ as an eigenvalue for any $g\in G$. In this paper, we determine all the complex irreducible unisingular representations of the finite simple groups of Lie type of rank $1$ and of the almost simple sporadic groups.

Aras Erarslan, Carlos Sevilla Salcedo, Ville Tanskanen, Anni Nisov

Preferential Bayesian optimization allows optimization of objectives that are either expensive or difficult to measure directly, by relying on a minimal number of comparative evaluations done by a human expert. Generating candidate solutions for evaluation is also often expensive, but this cost is ignored by existing methods. We generalize preference-based o

G. P. Djotyan, A. A. Avetisyan, A. P. Djotyan

We present a novel scheme for coherent manipulation of populations and robust creation of arbitrary coherent superposition of metastable states of a quantum system with lambda configuration of operating energy levels using laser pulses with a quadratically chirped carrier frequency. The case of a single broadband laser pulse is considered, when the frequency

Pragjyotish Bhuyan Gogoi, Rahul Ghosh, Debashis Ghoshal, Awadhesh Prasad

We use Clifford's geometric algebra to extend the Stuart-Landau system to dimensions $D >2$ and give an exact solution of the oscillator equations in the general case. At the supercritical Hopf bifurcation marked by a transition from stable fixed-point dynamics to oscillatory motion, the Jacobian matrix evaluated at the fixed point has $N=\lfloor{D/2}\rfloor

Sahar Salimpour, Iacopo Catalano, Tomi Westerlund, Mohsen Falahi

Autonomous micro-mobility platforms face challenges from the perspective of the typical deployment environment: large indoor spaces or urban areas that are potentially crowded and highly dynamic. While social navigation algorithms have progressed significantly, optimizing user comfort and overall user experience over other typical metrics in robotics (e.g.,

Azhar Hussain Mozumder, M. John Basha, Chayapathi A. R

With more and more existing networks being transformed to Software-Defined Networking (SDN), they need to be more secure and demand smarter ways of traffic control. This work, SmartSecChain-SDN, is a platform that combines machine learning based intrusion detection, blockchain-based storage of logs, and application-awareness-based priority in SDN networks. T

Mohit Dhanik, Shraddha Sharma, Pitamber Mahanandia

This study presents an improved quantum teleportation protocol designed to enhance fidelity in noisy environments by combining weak measurements (WMs) with flip and reversal operations. In our scheme, Alice prepares a four-qubit entangled state and shares one of the entangled qubits with Bob, which serves as the quantum channel for teleporting an arbitrary s

F. Lesjak, L. Nortmann, D. Cont, P. J. Amado

WASP-69b and KELT-11b are two low-density hot Jupiters, which are expected to show strong atmospheric features in their transmission spectra. Such features offer valuable insights into the chemical composition, thermal structure, and cloud properties of exoplanet atmospheres. High-resolution spectroscopic observations can be used to study the line-forming re

Gaëtan Caillaut, Raheel Qader, Jingshu Liu, Mariam Nakhlé

The financial industry's growing demand for advanced natural language processing (NLP) capabilities has highlighted the limitations of generalist large language models (LLMs) in handling domain-specific financial tasks. To address this gap, we introduce the LLM Pro Finance Suite, a collection of five instruction-tuned LLMs (ranging from 8B to 70B parameters)

Joseph M. Jones, M. W. Long

We provide a systematic formula, in terms of integer partitions, that generates perturbation theory explicitly at an arbitrary order. Our approach naturally includes an infinite number of perturbations and uses a single matrix equation that contains the information for both the eigenvalue and eigenvector corrections. The formula reduces to the standard case

Adrian Azzarelli, Nantheera Anantrasirichai, David R Bull

Deformable Gaussian Splatting (GS) accomplishes photorealistic dynamic 3-D reconstruction from dense multi-view video (MVV) by learning to deform a canonical GS representation. However, in filmmaking, tight budgets can result in sparse camera configurations, which limits state-of-the-art (SotA) methods when capturing complex dynamic features. To address this

Marco Ornigotti

This work unveils a novel and fundamental connection between structured light and topological field theory by showing how the natural geometrical setting for paraxial vector beams is that of a $SU(2)$ principal bundle over $\mathbb{R}^{2+1}$. Going beyond the usual high-order Poincar\'e sphere approach, we show how the nonseparable structure of polarisation

Cristina Olmedilla, Jesus Escudero-Sahuquillo, Pedro J. Garcia, Francisco J. Quiles

Over the past decade, Supercomputers and Data centers have evolved dramatically to cope with the increasing performance requirements of applications and services, such as scientific computing, generative AI, social networks or cloud services. This evolution have led these systems to incorporate high-speed networks using faster links, end nodes using multiple

E. Dyachenko

The Erdos-Straus conjecture (ESC) concerns the representation of the fraction 4/P, where P is a prime number, as a sum of three positive unit fractions. The focus here is on the case when P is congruent to 1 modulo 4. Two constructive approaches are proposed. Method ED1 is based on a factorization identity and leads to a nonlinear parameterization in P, whic

Moto Togawa, Chunhai Lyu, Chintan Shah, Marc Botz

Ultraintense pulses from X-ray free-electron lasers can drive, within femtoseconds, multiple processes in the inner shells of atoms and molecules in all phases of matter. The ensuing complex ionization pathways of outer-shell electrons from the neutral to the final highly charged states make a comparison with theory enormously difficult. We resolve these pat

A. Barone, F. Rodler, D. Gandolfi, A. Bonfanti

TOI-282 is a bright (V=9.38) F8 main-sequence star known to host three transiting long-period ($P_b$=22.9 d, $P_c$=56.0 d, and $P_d$=84.3 d) small ($R_p\approx$ 2-4 $R_{\oplus}$) planets. The orbital period ratio of the two outermost planets, namely TOI-282 c and d, is close to the 3:2 commensurability, suggesting that the planets might be trapped in a mean

Luigi De Masi, Andrea Marchese, Annalisa Massaccesi

This paper introduces two variational formulations for a model of robust optimal transport, that is, the problem of designing optimal transport networks that are resilient to potential damages, balancing construction costs against the benefit of maintaining partial functionality when parts of the network are damaged. We propose a Eulerian formulation, where

Silvia Preda, Matteo Semplice

We propose a level-set-based semi-Lagrangian method on graded adaptive Cartesian grids to address the problem of surface reconstruction from point clouds. The goal is to obtain an implicit, high-quality representation of real shapes that can subsequently serve as computational domain for partial differential equation models. The mathematical formulation is v

Frederik Rautenberg, Fritz Seebauer, Jana Wiechmann, Michael Kuhlmann

The control of perceptual voice qualities in a text-to-speech (TTS) system is of interest for applications where unmanipu- lated and manipulated speech probes can serve to illustrate pho- netic concepts that are otherwise difficult to grasp. Here, we show that a TTS system, that is augmented with a global speaker attribute manipulation block based on normali

Bernardo Sánchez-Rey, David Mellado-Alcedo, Niurka R. Quintero

The linear stability of two exact stationary solutions of the parametrically driven, damped nonlinear Dirac equation is investigated. Stability is ascertained through the resolution of the eigenvalue problem, which stems from the linearization of this equation around the exact solutions. On the one hand, it is proven that one of these solutions is always uns

Ana Isaković

We show that non-positively curved $k$-fold triangle groups have finitely many cone types, and hence a regular language of all geodesics. Further, we prove that the language of lexicographically first geodesics is both regular and satisfies the fellow traveller property, giving an automatic structure for this family of groups.

Gwyn Bellamy, Simone Castellan, Isambard Goodbody

Motivated by the representation theory of symplectic reflection algebras, deformed preprojective algebras, and graded Hecke algebras, we consider filtered algebras $U$ whose associated graded is Koszul. The Koszul dual of $U$, as defined by Positselski, is a curved dg-algebra. We establish an exact equivalence between the unbounded derived category of $U$ an

Nils Andersson, Rhys Counsell, Fabian Gittins, Suprovo Ghosh

We develop a fully relativistic approach for determining the response of a compact star to a time/frequency dependent (tidal) environment. The strategy involves matching the solution for the linearised fluid dynamics in the star's interior to the spacetime perturbations in the near-zone surrounding the body, along with an identification of the tidal driving

Hai Dang Nguyen, Hoang Nam Cao

In this work, we study two potentials, the single-field and the two-field, from the modified ($R+\gamma R^n$) gravity in D=8 dimensions. From those potentials, we calculate four observable quantities in inflation, including scalar-to-tensor ratio, spectral index, running index and scalar amplitude. Then, we compare them to the experimental data to verify the

Mees M. Flapper, Giulia Piumini, Roberto Verzicco, Sander G. Huisman

This study presents a combined experimental and computational investigation of an oloid shaped particle settling in a quiescent fluid. The oloid, a unique convex shape with anisotropic geometry, provides a distinctive model for exploring how a particle's shape and orientation affect its settling dynamics. The settling oloids are tracked experimentally for Ga

Junghwan Lim, Sungmin Lee, Dongseok Kim, Taehyun Kim

We introduce Motif-2-12.7B, a new open-weight foundation model that pushes the efficiency frontier of large language models by combining architectural innovation with system-level optimization. Designed for scalable language understanding and robust instruction generalization under constrained compute budgets, Motif-2-12.7B builds upon Motif-2.6B with the in

Patrice Labedan, Nicolas Drougard

ACCADIL is a project that led to the development of software tools for the identification of coin die links from coin photographs. It provides a computational algorithm based on computer vision and classification techniques, along with an online interface for the interactive verification of results. This guide briefly describes the algorithmic principles, th

Robin Armingaud, Romaric Besançon

While large general-purpose Transformer-based encoders excel at general language understanding, their performance diminishes in specialized domains like manufacturing due to a lack of exposure to domain-specific terminology and semantics. In this paper, we address this gap by introducing ManufactuBERT, a RoBERTa model continually pretrained on a large-scale

Hendrik Paul Lopuhaa

We provide a unified approach to MM-estimation with auxiliary scale for balanced linear models with structured covariance matrices. This approach leads to estimators that are highly robust against outliers and highly efficient for normal data. These properties not only hold for estimators of the regression parameter, but also for estimators of scale invarian

Urslla Uchechi Izuazu, Mounir Bensalem, Admela Jukan

While Intent-Based Networking (IBN) promises operational efficiency through autonomous and abstraction-driven network management, a critical unaddressed issue lies in IBN's implicit trust in the integrity of intent ingested by the network. This inherent assumption of data reliability creates a blind spot exploitable by Man-in-the-Middle (MitM) attacks, where

Son Dinh-Van, Nam Phuong Tran, Matthew D. Higgins

Blind beamforming has emerged as a promising approach to configure reconfigurable intelligent surfaces (RISs) without relying on channel state information (CSI) or geometric models, making it directly compatible with commodity hardware. In this paper, we propose a new blind beamforming algorithm, so-called Blind Optimal RIS Beamforming with Sensing (\textsc{

Fernando Berzal

The loss function used to train a neural network is strongly connected to its output layer from a statistical point of view. This technical report analyzes common activation functions for a neural network output layer, like linear, sigmoid, ReLU, and softmax, detailing their mathematical properties and their appropriate use cases. A strong statistical justif

Juan Magalang, Tyll Krueger, Joerg Galle

RNA-based vaccination has been broadly applied in the COVID pandemic. A characteristic of the immunization was fast waning immunity. However, the time scale of this process varied considerable for virus subtypes and among individuals. Understanding the origin of this variability is crucial in order to improve future vaccination strategies. Here, we introduce

Ryudai Iwakami, Bo Peng, Hiroyuki Hanyu, Tasuku Ishigooka

The field of autonomous vehicle research is advancing rapidly, necessitating platforms that meet real-time performance, safety, and security requirements for practical deployment. AUTOSAR Adaptive Platform (AUTOSAR AP) is widely adopted in development to meet these criteria; however, licensing constraints and tool implementation challenges limit its use in r

Bin Fan, Jian-Jian Jiang, Zhuohao Li, Xiao-Ming Wu

Object manipulation, which focuses on learning to perform tasks on similar parts across different types of objects, can be divided into an approaching stage and a manipulation stage. However, previous works often ignore this characteristic of the task and rely on a single policy to directly learn the whole process of object manipulation. To address this prob

Andrea Ichino, Fabrizia Mealli, Javier Viviens

Every year, over one million EU students choose a secondary school track based on teacher recommendations, yet little evidence shows this yields optimal assignments. Using Dutch data, we examine whether access to standardized test scores improves recommendation quality. We develop a Principal-Stratification metric in a quasi-randomized setting, conduct a wel

Séverin Philip

Grothendieck defined a group that represents the local obstruction for an abelian variety to have semi-stable reduction. These groups were studied by Silverberg and Zarhin and more recently by the author in order to give a group theoretic characterization of them depending only on the dimension. We give an overview of the developments since Grothendieck's de

Ariane Nidelle Meli Chrisko, Philipp Otto, Wolfgang Schmid

This paper introduces a spatiotemporal exponential generalised autoregressive conditional heteroscedasticity (spatiotemporal E-GARCH) model, extending traditional spatiotemporal GARCH models by incorporating asymmetric volatility spillovers, while also generalising the time-series E-GARCH model to a spatiotemporal setting with instantaneous, potentially asym

Fei Li, Xiao-Wei Li, Oscar Dahlsten

In quantum illumination, the probe photon is entangled with an ancilla photon, and both are jointly measured at the end. The entanglement between the probe and ancilla photons enhances the detection performance per unit average photon number in the probe mode, particularly in low-reflectivity and high-noise scenarios. However, photon loss severely limits the

Felix Divo, Maurice Kraus, Anh Q. Nguyen, Hao Xue

Text offers intuitive access to information. This can, in particular, complement the density of numerical time series, thereby allowing improved interactions with time series models to enhance accessibility and decision-making. While the creation of question-answering datasets and models has recently seen remarkable growth, most research focuses on question

R. Brivio, S. Covino, M. Ferro, A. Saccardi

Gamma-ray bursts (GRBs) are extremely bright phenomena powered by relativistic jets arising from explosive events at cosmological distances. The nature of the jet and the configuration of the local magnetic fields are still unclear, with the distinction between different models possibly provided by the detection of early-time polarisation. Past observations

Sergey Shvydun

Centrality is a fundamental concept in network science, providing critical insights into the structure and dynamics of complex systems such as social, transportation, biological and financial networks. Despite its extensive use, there is no universally accepted definition of centrality, leading to the development of a large variety of distinct centrality mea

Weiping Bu, Zhengfang Xie, Yushi Wang

This paper focuses on the numerical solution of a dual-phase-lag heat conduction equation on a space unbounded domain. First, based on the Laplace transform and the Pad\'e approximation, a high-order local artificial boundary condition is constructed for the considered problem, which effectively transforms the original problem into an initial-boundary value

Daniel Grießhaber, Maximilian Kimmich, Johannes Maucher, Ngoc Thang Vu

Evolutionary prompt optimization has demonstrated effectiveness in refining prompts for LLMs. However, existing approaches lack robust operators and efficient evaluation mechanisms. In this work, we propose several key improvements to evolutionary prompt optimization that can partially generalize to prompt optimization in general: 1) decomposing evolution in

Víctor Mayoral-Vilches, Luis Javier Navarrete-Lozano, Francesco Balassone, María Sanz-Gómez

Operational Technology (OT) cybersecurity increasingly relies on rapid response across malware analysis, network forensics, and reverse engineering disciplines. We examine the performance of Cybersecurity AI (CAI), powered by the \texttt{alias1} model, during the Dragos OT CTF 2025 -- a 48-hour industrial control system (ICS) competition with more than 1,000

Elisa Varani

We investigate stationary torsional configurations supported by chiral Majorana neutrino currents in linearized gravity. A Ricci-flow-inspired geometric relaxation (with no physical time interpretation) is introduced to drive the metric perturbation toward fixed points sustained by chiral sources while keeping curvature invariants negligible. We show that di

Ian Kolaja, Ludovic Jantzen, Tatiana Siaraferas, Massimiliano Fratoni

Pebble bed reactor (PBR) operation presents unique advantages and challenges due to the ability to continuously change the fuel mixture and excess reactivity. Each operation parameter affects reactivity on a different timescale. For example, fuel insertion changes may take months to fully propagate, whereas control rod movements have immediate effects. In-co

J. Guo, A. B. Zheglov

In this paper, which is a follow-up of our first paper "Normal forms for ordinary differential operators, I", we extend the theory of normal forms for non-commuting operators, and obtain as an application a commutativity criterion for operators in the Weyl algebra or, more generally, in the ring of ordinary differential operators, which we prove in the case

Alex Junior da Cunha Coelho, Araceli Hernandez, Luis Badesa

The Transient Stability-Constrained Optimal Power Flow (TSC-OPF) incorporates dynamic stability constraints into the OPF formulation to ensure secure and economical operation under disturbances. While discretizing system dynamics enables the use of nonlinear programming techniques, it significantly increases computational burden. To enhance scalability, many

Shilpa Bijavara Seshashayana, Henrik Jönsson, Valentina D'Orazi, Angela Bragaglia

Open clusters have been extensively used as tracers of Galactic chemical evolution, as their constituent stars possess shared characteristics, including age, Galactocentric radius, metallicity, and chemical composition. By examining the trends of elemental abundances with metallicity, age, and Galactocentric radius, valuable insights can be gained into the d

Prateek Rajput, Abdoul Aziz Bonkoungou, Yewei Song, Abdoul Kader Kabore

Current evaluations of LLMs for code generation emphasize functional correctness, overlooking the fact that functionally correct solutions can differ significantly in algorithmic complexity. For instance, an $(O(n^2))$ versus $(O(n \log n))$ sorting algorithm may yield similar output but incur vastly different performance costs in production. This discrepanc

Álvaro Guglielmin Becker, Lana Bertoldo Rossato, Anderson Rocha Tavares

Creating programs to represent board games can be a time-consuming task. Large Language Models (LLMs) arise as appealing tools to expedite this process, given their capacity to efficiently generate code from simple contextual information. In this work, we propose a method to test how capable three LLMs (Claude, DeepSeek and ChatGPT) are at creating code for

Qilong Yuan

The Joint Routing-Assignment (JRA) optimization problem simultaneously determines the assignment of items to placeholders and a Hamiltonian cycle that visits each node pair exactly once, with the objective of minimizing total travel cost. Previous studies introduced an exact mixed-integer programming (MIP) solver, along with datasets and a Gurobi implementat

Pietro Benotto, Benedetta Vulcani, Peter J. Watson, Giulia Rodighiero

Ram pressure stripping (RPS) plays a crucial role in shaping galaxy evolution in dense environments, yet its impact on the molecular and dusty phases of the interstellar medium remains poorly understood. We present JWST/NIRCam $3.3\mathrm{\mu m}$ polycyclic aromatic hydrocarbon (PAH) emission maps for the nine most striking RPS galaxies in the Abell 2744 clu

Ruixin Zuo, Matthias Reichelt, Cong Ngo, Xiaohong Song

We compute and analyze the dependence of excitonic second- and third-harmonic generation (SHG/THG) as a function of the optical excitation intensity in the presence of static electric fields by solving the semiconductor Bloch equations. Our simulations are performed for excitation of the strongly bound intralayer exciton of an inversion-symmetric homobilayer

Do Hyun Kim, Ahmet Cetinkaya

In this paper, we provide a probabilistic analysis of the confidentiality in a card-based protocol. We focus on Bert den Boer's original Five Card Trick to develop our approach. Five Card Trick was formulated as a secure two-party computation method, where two players use colored cards with identical backs to calculate the logical AND operation on the bits t

Xingzhi Zhang, Buyi Lv, Yimin Lu, Kai Bu

The IP-stride prefetcher has recently been exploited to leak secrets through side-channel attacks. It, however, cannot be simply disabled for security with prefetching speedup as a sacrifice. The state-of-the-art defense tries to retain the prefetching effect by hardware modification. In this paper, we present PhantomFetch as the first prefetching-retentive

Benjamin Kahl, Marcus Hebel, Michael Arens

Geospatial sensor data is essential for modern defense and security, offering indispensable 3D information for situational awareness. This data, gathered from sources like lidar sensors and optical cameras, allows for the creation of detailed models of operational environments. In this paper, we provide a comparative analysis of traditional representation me

Jörg Gamerdinger, Benedict Wetzel, Patrick Schulz, Sven Teufel

Lane detection for autonomous driving in snow-covered environments remains a major challenge due to the frequent absence or occlusion of lane markings. In this paper, we present a novel, robust and realtime capable approach that bypasses the reliance on traditional lane markings by detecting roadside features,specifically vertical roadside posts called delin

Luke G. Bennetts, Jie Liang

The transient response of an ice shelf to an incident wave packet from the open ocean is studied with a model that allows for extensional waves in the ice shelf, in addition to the standard flexural waves. Results are given for strains imposed on the ice shelf by the incident packet, over a range of peak periods in the swell regime and a range of packet widt

Yasemin Turkan, F. Boray Tek, M. Serdar Nazlı, Öykü Eren

Alterations in retinal layer thickness, measurable using Optical Coherence Tomography (OCT), have been associated with neurodegenerative diseases such as Alzheimer's disease (AD). While previous studies have mainly focused on segmented layer thickness measurements, this study explored the direct classification of OCT B-scan images for the early detection of

Tim Bauer, Johannes Reuther

Quasiparticle hybridization remains a major challenge to realizing and controlling exotic states of matter in existing quantum simulation platforms. We report the absence of hybridization for compact localized states (CLS) emerging in the chiral spin liquid described by the Yao-Kivelson model. The CLS form due to destructive quantum interference at fine-tune

Yuhang Liu, Wenjun Mei

In this paper, we propose a zeroth-order resilient distributed online algorithm for networks under Byzantine edge attacks. We assume that both the edges attacked by Byzantine adversaries and the objective function are time-varying. Moreover, we focus on the scenario where the complete time-varying objective function cannot be observed, and only its value at

Sichao Li, Xinyue Xu, Xiaomeng Li

Large language models (LLMs) often achieve impressive predictive accuracy, yet correctness alone does not imply genuine understanding. True LLM understanding, analogous to human expertise, requires making consistent, well-founded decisions across multiple instances and diverse domains, relying on relevant and domain-grounded decision factors. We introduce St

Eduardo Vital, Jean-Marc Gratien, Yassine Ayoun, Thibault Faney

When simulating multiscale systems, where some fields cannot be fully prescribed despite their effects on the simulation's accuracy, closure models are needed. This phenomenon is observed in turbulent fluid dynamics, where Large Eddy Simulations (LES) depict global behavior while turbulence modeling introduces dissipation correspondent to smaller sub-grid sc

Disesdi Susanna Cox, Niklas Bunzel

Neural networks have become pervasive across various applications, including security-related products. However, their widespread adoption has heightened concerns regarding vulnerability to adversarial attacks. With emerging regulations and standards emphasizing security, organizations must reliably quantify risks associated with these attacks, particularly

Yu Mao, Xiao Wang

In this paper, we apply Hoshi's mono-anabelian reconstruction of number fields to establish a group-theoretic reconstruction of a number field K together with its maximal unramified outside S extension K_S for a density 1 subset of primes of K starting from the profinite group G_{K,S}.

Arslan Mumtaz, Mridula Singh

Global Navigation Satellite Systems (GNSS) provide Positioning, Navigation, and Timing (PNT) information to over 4 billion devices worldwide. Despite its pervasive use in safety critical and high precision applications, GNSS remains vulnerable to spoofing attacks. Cryptographic enhancements, such as the use of TESLA protocol in Galileo, to provide navigation

Mrinal Kanti Roychowdhury

This expository paper provides a unified and pedagogical introduction to optimal quantization for probability measures supported on spherical curves and discrete subsets of the sphere, emphasizing both continuous and discrete settings. We first present a detailed geometric and analytical foundation for intrinsic quantization on the unit sphere, including def

Romain Lefeuvre, Charly Reux, Stefano Zacchiroli, Olivier Barais

Tracking vulnerabilities inherited from third-party open-source software is a well-known challenge, often addressed by tracing the threads of dependency information. However, vulnerabilities can also propagate through forking: a code repository forked after the introduction of a vulnerability, but before it is patched, may remain vulnerable long after the vu

Fuyang Liu, Jiaqi Xu, Xiaowei Hu

Adverse weather severely impairs real-world visual perception, while existing vision models trained on synthetic data with fixed parameters struggle to generalize to complex degradations. To address this, we first construct HFLS-Weather, a physics-driven, high-fidelity dataset that simulates diverse weather phenomena, and then design a dual-level reinforceme

Zhaoyang Li, Shangzhuo Xie, Qianqian Yang

The emergence of sixth-generation networks heralds an intelligent communication ecosystem driven by the rapid proliferation of intelligent services and increasingly complex communication scenarios. However, current physical-layer designs-typically following modular and isolated optimization paradigms-fail to achieve global end-to-end optimality due to neglec

Despoina Farakou, Constantinos Skordis

We present an emulator suite for the one- and two-loop cold dark matter power spectrum from the Effective Field Theory of Large Scale Structures (EFTofLSS). Specifically, we emulate separately the various contributions to the one- and two-loop parts of the power spectrum, leaving out the possible counterterms which can be added as multiplicative prefactors.

Ruolin Li, Min Liu, Yuan Bian, Zhaoyang Li

With growing concerns over data privacy, researchers have started using virtual data as an alternative to sensitive real-world images for training person re-identification (Re-ID) models. However, existing virtual datasets produced by game engines still face challenges such as complex construction and poor domain generalization, making them difficult to appl

Tuomas Orponen

I prove two variants of the $ABC$ sum-product theorem for $δ$-separated sets $A,B,C \subset [0,1]$ satisfying Katz-Tao spacing conditions. The main novelty is that the cardinality of the sets $B,C$ need not match their non-concentration exponent. The new $ABC$ theorems are sharp under their respective hypotheses, and imply the previous one.

Xuan Chen, Matthieu Crussière, Luc Le Magoarou

In this paper, we investigate the impact of hardware impairments in antenna arrays on the beamforming performance of multi-input multi-output (MIMO) communication systems. We consider two types of imperfections: per-element gain mismatches and inter-element spacing deviations. We analytically determine the impairment configurations that result in the worst-c

Zhiquan Yu, Chenjia Zhao, Lingyun Xiong, Shanshan Su

Chronic wound infections are sustained by dynamic 3D biofilm cycles involving maturation, dispersal, and recolonisation, yet existing in vitro models fail to reproduce these temporal and structural complexities. Here, we report a strategy that co-assembles a designed protease-inhibitory peptide amphiphile (PA-GF) with patient-derived wound fluid (WF) to reco

Camille Bader, Rémy Gilardet, Nicolas Rinder, Victoria Herridge

One of the greatest challenges of terrestrial locomotion is resisting gravity. The morphological adaptive features of the limb long-bones of extant elephants, the heaviest living terrestrial animals, have previously been highlighted; however, their bone microanatomy remains largely unexplored. Here we investigate the microanatomy of the six limb long-bones i

Mohammed Ahmed Adam Abdalrahman, Huijian Zhu, Jiu Ding, Qianglian Huang

We solve the Yang-Baxter-like matrix equation $AXA = XAX$ for a general given matrix $A$ to get all anti-commuting solutions, by using the Jordan canonical form of $A$ and applying some new facts on a general homogeneous Sylvester equation. Our main result provides all the anti-commuting solutions of the nonlinear matrix equation.

Ryo Yoshida, Yoshihiro Hayashi, Hidemine Furuya, Ryohei Hosoya

Developing large-scale foundational datasets is a critical milestone in advancing artificial intelligence (AI)-driven scientific innovation. However, unlike AI-mature fields such as natural language processing, materials science, particularly polymer research, has significantly lagged in developing extensive open datasets. This lag is primarily due to the hi

Yong Chen

Using the inner product formula of the canonical Hilbert space of fractional Brownian motion on an interval $[0,T]$ with Hurst parameter $H\in (0,1)$ given by Alazemi et al., we show the asymptotic expansion of the norm of $f_T(s,t):=e^{-|t-s|}\mathbf{1}_{\{0\le s,t\le T\}}$ up to the term $T^{4H-4}$. As applications, we show that the existence of the obliqu

Takuro Abe, Shota Maehara, Gerhard Roehrle, Sven Wiesner

The study of universal derivations for arbitrary multiarrangements and multiplicity functions was initiated by Abe, R\"ohrle, Stump, and Yoshinaga in 2024 which focused on arrangements arising from (well-generated) reflection groups. In this paper we provide a criterion for determining whether a derivation is universal along with a characterization of univer

Grigory Kovalev, Mikhail Tikhomirov

This work investigates distillation methods for large language models (LLMs) with the goal of developing compact models that preserve high performance. Several existing approaches are reviewed, with a discussion of their respective strengths and limitations. An improved method based on the ShortGPT approach has been developed, building upon the idea of incor

José Gómez-Torrecillas, F. J. Lobillo, Gabriel Navarro, Paolo Santonastaso

Skew polynomial rings provide a fundamental example of noncommutative principal ideal domains. Special quotients of these rings yield matrix algebras that play a central role in the theory of rank-metric codes. Recent breakthroughs have shown that specific subsets of these quotients produce the largest known families of maximum rank distance (MRD) codes. In

S. Vanlangendonck, D. Atanasov, B. Blank, X. Fléchard

This work presents optical calculations and simulations for scintillation detectors used in precision measurements of beta-particle energy spectra. Particular attention is given to Cherenkov photons and the impact of the light detection efficiency in the detector ensemble. We present an approach to estimate this light detection efficiency from the measured e

Yiming Xie, Hua Dai, Mingfeng Jiang, Pengyue Li

Neural embedding models are extensively employed in the table union search problem, which aims to find semantically compatible tables that can be merged with a given query table. In particular, multi-vector models, which represent a table as a vector set (typically one vector per column), have been demonstrated to achieve superior retrieval quality by captur

Stefan Hoffelner

We present a method which allows the combination of forcing uniformization on the $Π$- and the $Σ$-side of the projective hierarchy to a certain extent. Using this method we construct a universe where $Π^1_3$-reduction holds, $Π^1_3$-uniformization fails, yet $Σ^1_n$ uniformization is true for $n \ge 4$. We also construct a universe where $Π^1_3$-uniformizat

P. Bilha Githinji, Aikaterini Melliou, Zeming Liang, Lian Zhang

The growing public demand for accessible biomedical information calls for scalable text simplification. While large language models (LLMs) offer solutions, they too struggle with balancing improved readability against preservation of meaning. This report empirically compares how two LLMs - instruction-tuned Mistral-Small 3 24B and the reasoning-augmented QWe