March 2026 arXiv papers — page 36

Duy-Minh Dang, Hao Zhou

We present a strictly monotone, provably convergent two-dimensional (2D) integration method for multi-period mean-conditional value-at-risk (mean-CVaR) reward-risk stochastic control in models whose one-step increment law is specified via a closed-form characteristic function (CF). When the transition density is unavailable in closed form, we learn a nonnega

Yixin Cao, Xianfeng Cheng, Yijie Liu

Transfer-based anti-money laundering (AML) systems monitor token flows through transaction-graph abstractions, implicitly assuming that economically meaningful value migration is sufficiently encoded in transfer-layer connectivity. In this paper, we demonstrate that this assumption, the bedrock of current industrial forensics, fundamentally collapses in comp

Debojyoti Saha

T. Kambayashi had shown that $\mathbb{A}^2$-forms over separable field extensions are necessarily polynomial rings. However, there exist inseparable $\mathbb{A}^2$-forms which are not necessarily polynomial rings. In this paper, we give a structure theorem for $\mathbb{A}^2$-forms over arbitrary field extensions admitting a nontrivial $\mathbb{G}_a$-action.

Sampriti Roy, Pritam Sen, Satyanarayan Mukhopadhyay

We study the next-to-leading order (NLO) virtual and thermal corrections to relativistic $2 \rightarrow 2$ scattering processes involving scalar particles in the early Universe thermal plasma. Taking the example of freeze-in production of scalar dark matter pairs through these scatterings, we evaluate the impact of the NLO corrections to the annihilation rat

Mukul Dwivedi, Jesse Railo, Andreas Rupp

We study a numerical reconstruction strategy for the potential in the fractional Calder\'on problem from a single partial exterior measurement. The forward model is the fractional Schr\"odinger equation in a bounded domain, with prescribed exterior Dirichlet datum and corresponding measurement of the exterior flux in an open observation set. Motivated by sin

Saurabh Pathak, Elahe Arani, Mykola Pechenizkiy, Bahram Zonooz

Generative video models achieve high visual fidelity but often violate basic physical principles, limiting reliability in real-world settings. Prior attempts to inject physics rely on conditioning: frame-level signals are domain-specific and short-horizon, while global text prompts are coarse and noisy, missing fine-grained dynamics. We present PhysVid, a ph

Petr Novak, Jan Koloros, Stanislav Haviar, Jiri Rezek

Ga2O3 thin films were deposited by reactive magnetron sputtering from a liquid gallium target. The influence of deposition temperature, substrate type, and discharge parameters on the structural and electrical properties was systematically investigated. Films deposited on silicon and quartz glass exhibit polycrystalline growth, whereas sapphire substrates en

Prithwish Ghosh, Kajal Krishna Dey, Golam Ali Sekh

We consider spin-orbit coupled Bose-Einstein condensates with cubic-quintic nonlinear interaction within the framework of second quantization formulation and find eigen states using numerical simulation and mean-field approximation. We show that two low-lying Schrodinger cat states remain degenerate up to a certain value of Raman coupling strength and these

Yangjie Tian, Xungang Gu, Yun Zhao, Jiale Yang

Large language models (LLMs) are increasingly used in scientific writing but struggle with book-length tasks, often producing inconsistent structure and unreliable citations. We introduce CoAuthorAI, a human-in-the-loop writing system that combines retrieval-augmented generation, expert-designed hierarchical outlines, and automatic reference linking. The sys

Gastón Blatter, Xiao Zhang, Jeroen van den Brink, Mengli Hu

Controlling physical responses through symmetry breaking is a central paradigm in quantum materials, enabling novel functionalities. Here we determine the effects of spin-group-symmetry breaking on nonlinear optical responses of collinear altermagnetic insulators. Using shear strain as an example, we show that the direction of symmetry-breaking induced compo

Taro Nagao

Two-dimensional Coulomb gases on an annulus at a special inverse temperature $\beta = 2$ are studied by using the orthogonal polynomial method borrowed from the theory of random matrices. The correlation functions among the Coulomb gas molecules are written in determinant forms and their asymptotic forms in the thermodynamic limit are evaluated. When the Cou

Aleksei Kislitsyn

In this work we show that in general there is no Courant-like bound for Neumann domain count. In order to do that we construct a sequence of domains $\Omega^n$ such that the first Dirichlet eigenfunction for $\Omega^n$ has at least $n$ Neumann domains. Also a special case of convex domains is considered and sufficient conditions for existence of Courant-like

Ryota Tamura, Tomoya Kashimata, Yohei Hamakawa, Kosuke Tatsumura

A large-scale quantum circuit can be partitioned into multiple subcircuits through circuit cutting, where each subcircuit is executed multiple times and the expectation value of the original circuit is reconstructed by classical post-processing from their measurement (sampling) results. In this process, appropriate cut locations are identified after the user

Rosalia Tufano, Federica Pepe, Fiorella Zampetti, Antonio Mastropaolo

The availability of generative Artificial Intelligence (AI) tools such as ChatGPT or GitHub Copilot is reshaping the way in which software is developed, evolved, and maintained. Oftentimes, developers leave traces of such an usage in software artifacts. This allows not only to understand how AI is used in software development, but also to let others be aware

A. Gordon Emslie, Eduard P. Kontar

The impulsive phase of a solar flare is known to generate strong turbulence and to transfer magnetic energy into accelerated electrons. Recognizing the importance of angular diffusion on the dynamics of the accelerated electrons, we extend previous treatments by deriving analytic solutions for the electron flux and associated energy deposition in two regimes

Manuel Santos-Gutierrez, Valerio Lucarini, John Moroney, Niccolo Zagli

The transient time correlation function (TTCF) method is widely used in molecular fluids to compute non-equilibrium transport quantities, providing improved signal-to-noise ratios in ensemble averages without requiring prohibitively large sample sizes. In spite of its success in molecular and turbulent fluid systems, the method has not been systematically ex

Cosmin Farcău

Colloidal plasmonic-photonic crystals represent a class of hybrid materials composed of a dielectric colloidal spheres photonic lattice and a metal plasmonic film. In this work, the optical properties of a linear array colloidal plasmonic-photonic crystal consisting of silver films deposited over linear arrays of polystyrene microspheres are analysed in deta

Jiaxi Gu, Bao-Shan Wang, Wai Sun Don, Jae-Hun Jung

We propose a simple yet effective local smoothness indicator for the downwind stencil in central-upwind weighted essentially non-oscillatory (WENO) schemes of even order for hyperbolic conservation laws. Starting from an odd-order upwind WENO scheme, we construct an even-number-of-points stencil by incorporating a downwind substencil whose smoothness indicat

Paula Daudén-Oliver, David Agost-Beltran, Emilio Sansano-Sansano, Raul Montoliu

This work analyzes the RAID dataset to evaluate human responses to affine image distortions, including rotation, translation, scaling, and Gaussian noise. Using Mean Squared Error (MSE), the study establishes human detection thresholds for these distortions, enabling comparison across types. Statistical analysis with ANOVA and Tukey Kramer tests reveals that

Matteo Vorabbi, Michael Gennari, Paolo Finelli, Carlotta Giusti

We apply to the nucleon-nucleus inelastic process a fully coherent microscopic multiple scattering approach. Our study addresses the complexities inherent in characterizing inelastic scattering events, offering a comprehensive theoretical model grounded in the reaction theory. The approach is based on the distorted-wave approximation and requires the knowled

Shuyi Gao, Stavros Orfanoudakis, Shengren Hou, Peter Palensky

Optimal dispatch of energy storage systems (ESSs) in distribution networks involves jointly improving operating economy and voltage security under time-varying conditions and possible topology changes. To support fast online decision making, we develop a topology-aware Reinforcement Learning architecture based on Twin Delayed Deep Deterministic Policy Gradie

Tomoya Miyawaki, Kazuto Nakashima, Yumi Iwashita, Ryo Kurazume

LiDAR-based semantic segmentation is a key component for autonomous mobile robots, yet large-scale annotation of LiDAR point clouds is prohibitively expensive and time-consuming. Although simulators can provide labeled synthetic data, models trained on synthetic data often underperform on real-world data due to a data-level domain gap. To address this issue,

Zhixin Cheng, Jiacheng Deng, Xinjun Li, Bohao Liao

Image-to-point cloud registration methods typically follow a coarse-to-fine pipeline, extracting patch-level correspondences and refining them into dense pixel-to-point matches. However, in scenes with repetitive patterns, images often lack sufficient 3D structural cues and alignment with point clouds, leading to incorrect matches. Moreover, prior methods us

Xujing Tao, Chuxin Wang, Yubo Ai, Zhixin Cheng

Open-vocabulary 3D semantic segmentation aims to segment arbitrary categories beyond the training set. Existing methods predominantly rely on distilling knowledge from 2D open-vocabulary models. However, aligning 3D features to the 2D representation space restricts intrinsic 3D geometric learning and inherits errors from 2D predictions. To address these limi

Antoine Edy, Max Conti, Quentin Macé

While Late Interaction models exhibit strong retrieval performance, many of their underlying dynamics remain understudied, potentially hiding performance bottlenecks. In this work, we focus on two topics in Late Interaction retrieval: a length bias that arises when using multi-vector scoring, and the similarity distribution beyond the best scores pooled by t

David Hagerman, Roman Naeem, Erik Brorsson, Fredrik Kahl

We present ARTA, a mixed-resolution coarse-to-fine vision transformer for efficient dense feature extraction. Unlike models that begin with dense high-resolution (fine) tokens, ARTA starts with low-resolution (coarse) tokens and uses a lightweight allocator to predict which regions require more fine tokens. The allocator iteratively predicts a semantic (clas

Yangzhou Liu

In 2022, V. O. Manturov and I. M. Nikonov \cite{Man22} constructed two composite maps, one of them is following: $$PB_{n+1} \overset{p_k}{\rightarrow} CPB_{n} \overset{f_d}{\rightarrow} VCB_{n}\overset{\rho}{\rightarrow} GL_n(\mathbb{Z}[t^{\pm 1},s^{\pm 1}])$$ In this paper, we prove that M-N is unfaithful if $k\geq 6$ since Burau kernel is a subgroup of M-N

D. Batic, D. Dutykh, M. Essa Sukaiti

We construct static, spherically symmetric wormhole solutions with a nontrivial redshift function, inspired by noncommutative geometry, in which point sources are replaced by Gaussian smearing of minimal length, yielding a regular shape function. Within this framework, we derive model-independent relations that isolate the role of the redshift function in co

Paul Greule, Wantong Huang, Máté Stark, Kwan Ho Au-Yeung

Electron spin resonance scanning tunneling microscopy (ESR-STM) has become a powerful tool for probing spin dynamics and coherence of individual atoms and molecules on surfaces. In this work, we perform Rabi oscillation and Hahn echo pulse protocols on individual iron phthalocyanine (FePc) molecules on MgO/Ag(001) using ESR-STM. While Hahn echo protocols are

Marion Taconné, Valentina D. A. Corino, Annamaria Del Franco, Sara Giovani

Hypertrophic cardiomyopathy (HCM) requires accurate risk stratification to inform decisions regarding ICD therapy and follow-up management. Current established models, such as the European Society of Cardiology (ESC) score, exhibit moderate discriminative performance. This study develops a robust, explainable machine learning (ML) risk score leveraging routi

Muhammad Apriandito Arya Saputra, Andry Alamsyah, Dian Puteri Ramadhani, Thomhert Suprapto Siadari

Big data research in Indonesia is constrained by a fundamental fragmentation: relevant data is scattered across social media, news portals, e-commerce platforms, review sites, and academic databases, each with different formats, access methods, and noise characteristics. Researchers must independently build collection pipelines, clean heterogeneous data, and

Lan Xiao, Catherine Holloway

AI accessibility tools have mostly been designed for individual use, helping one person overcome a specific functional barrier. But for many people with disabilities, complex tasks are accomplished through collaboration with others who bring complementary abilities, not solitary effort. We propose a three-layer framework, Channelling, Coordinating, and Co-Cr

Jiangdong Ai, Yizhe Ji, Xiaopan Lian, Kun Yang

Let $T$ be a finite tree with leaf set $\dO$ as the boundary and let $\lambda_2$ be the first nontrivial Steklov eigenvalue. Let $D$ and $\ell$ be the maximum vertex degree and the number of leaves, respectively. Motivated by the spectral influence of neck-stretching on Riemannian manifolds, we investigate a discrete counterpart--edge-stretching--and its eff

Yida Lin, Bing Xue, Mengjie Zhang, Sam Schofield

Autonomous tree pruning with unmanned aerial vehicles (UAVs) is a safety-critical real-world task: the onboard perception system must estimate the metric distance from a cutting tool to thin tree branches in real time so that the UAV can approach, align, and actuate the pruner without collision. We address this problem by training five variants of DEFOM-Ster

Parshva Daftari, Khush Patel, Shreyas Kapale, Jithin George

LLM agents lack persistent memory, causing conversations to reset each session and preventing personalization over time. We present Lyzr Cognis, a unified memory architecture for conversational AI agents that addresses this limitation through a multi-stage retrieval pipeline. Cognis combines a dual-store backend pairing OpenSearch BM25 keyword matching with

Pascal Henrich, Jonas Sievers, Maximilian Beichter, Thomas Blank

Transformer-based reinforcement learning has emerged as a strong candidate for sequential control in residential energy management. In particular, the Decision Transformer can learn effective battery dispatch policies from historical data, thereby increasing photovoltaic self-consumption and reducing electricity costs. However, transformer models are typical

Chihiro Taguchi, Yukinori Takubo, David Chiang

Language endangerment poses a major challenge to linguistic diversity worldwide, and technological advances have opened new avenues for documentation and revitalization. Among these, automatic speech recognition (ASR) has shown increasing potential to assist in the transcription of endangered language data. This study focuses on Ikema, a severely endangered

Luca Castelli

This paper focuses on random projection operators when the subspace of projection is estimated. We derive non-asymptotic upper bounds on the error between the projection onto the estimated subspace and the projection onto the underlying subspace. The provided upper bounds depend on the noise and on intrinsic properties of the estimated subspace. Several scen

Shashi Kumar, Esaú Villatoro-Tello, Sergio Burdisso, Kadri Hacioglu

Standard LLM-based speech recognition systems typically process utterances in isolation, limiting their ability to leverage conversational context. In this work, we study whether multimodal context from prior turns improves LLM-based ASR and how to represent that context efficiently. We find that, after supervised multi-turn training, conversational context

Mouad Elaarabi, Domenico Borzacchiello, Philippe Le Bot, Nathan Lauzeral

In a previous work (Elaarabi et al., 2025b), the Sequence Encoder for online dynamical system identification (Elaarabi et al., 2025a) and its combination with PINN (PINN-SE) were introduced and tested on both synthetic and real data case scenarios. The sequence encoder is able to effectively encode time series into feature vectors, which the PINN then uses t

Luu Tu Nguyen, Thi Bich Phuong Man, Vu Tram Anh Khuong, Thanh Ha Le

Micro-expression recognition is vital for affective computing but remains challenging due to the extremely brief, low-intensity facial motions involved and the high-dimensional nature of 4D mesh data. To address these challenges, we introduce a dual-view optical flow approach that simplifies mesh processing by capturing each micro-expression sequence from tw

Tobias Eisenreich, Husein Jusic, Stefan Wagner

Domain-driven design (DDD) is a powerful design technique for architecting complex software systems. This paper introduces a prompting framework that automates core DDD activities through structured large language model (LLM) interactions. We decompose DDD into five sequential steps: (1) establishing an ubiquitous language, (2) simulating event storming, (3)

Robbie G. Hunt, Gunnar K. Pálsson, Matías P. Grassi, Victoria Kabanova

Hydrogen-based magneto-ionics is a promising approach for rapid magnetoelectric control of spintronic devices. Most investigations so far into the magneto-ionic manipulation of rare-earth transition-metal alloys have used electrochemical methods for evaluating the magnetoelectric properties, but this technique makes it difficult to discriminate between the e

Cosmin Farcău

Metal-coated microsphere monolayers (MCM) are a class of plasmonic crystals consisting of noble metal films over arrays of self-assembled colloidal microspheres. Despite their ease of fabrication and tunable plasmonic response, their optical sensing potential has been scarcely explored. Here, silver coated polystyrene sphere monolayers are proposed as surfac

Sheyla Leyva-Sánchez, Fabian Linde, Meem Arafat Manab, María Poveda-Villalón

The EU Data Act establishes comprehensive rules governing data access and sharing across business-to-consumer (B2C), business-to-business (B2B), and business-to-government (B2G) contexts. This paper presents a comprehensive ontology for the EU Data Act, enabling reasoning over data sharing agreements through machine-readable representations. The DAOnt ontolo

Andrew Wilhelm, Josie Hughes

Robot swarms offer inherent robustness and the capacity to execute complex, collaborative tasks surpassing the capabilities of single-agent systems. Co-designing these systems is critical, as marginal improvements in individual performance or unit cost compound significantly at scale. However, under traditional frameworks, this scale renders co-design intrac

Felix Glaser, Christian M. Fromm, Luca Ricci, Yosuke Mizuno

Relativistic jets are among the most fascinating objects in the Universe, and recent high-resolution Very Long Baseline Interferometric (VLBI) observations, including the Global mm-VLBI Array and the Event Horizon Telescope (EHT), are able to resolve their structure close to their launching site. These observations reveal strongly limb-brightened jet structu

Szymon Kurkowski, Kayn A Forbes

Structured light carrying orbital angular momentum enables new regimes of nonlinear light-matter interaction. Here we develop a molecular quantum electrodynamics description of third-harmonic generation (THG) driven by focused Laguerre-Gaussian beams in isotropic molecular media. We show that the nonparaxial longitudinal field components of a tightly focused

Weifeng Hou, Zhangpeng Sun, Wenqi Yao, Liupeng Wang

The compact finite difference method is a powerful tool for discretizing conservation laws, owing to its inherent flexibility in developing high-resolution and highly stable schemes. In this paper, we propose a framework for the design of genuine globally conservative compact finite difference schemes, which addresses a critical requirement in conservation l

Uri Z. Kialy, Avi Shtarkberg, Ayal Klein

While multilingual language models successfully transfer factual and syntactic knowledge across languages, it remains unclear whether they process culture-specific pragmatic registers, such as slang, as isolated language-specific memorizations or as unified, abstract concepts. We study this by probing the internal representations of Gemma-2-9B-IT using Spars

Beatrice Alex, Claire Grover, Arlene Casey, Richard Tobin

We present GS-BrainText, a curated dataset of 8,511 brain radiology reports from the Generation Scotland cohort, of which 2,431 are annotated for 24 brain disease phenotypes. This multi-site dataset spans five Scottish NHS health boards and includes broad age representation (mean age 58, median age 53), making it uniquely valuable for developing and evaluati

Konstantinos Bessas, Serena Guarino Lo Bianco, Roberta Schiattarella

We establish a pointwise limit theorem for a broad class of pa\-ra\-me\-ter-\-de\-pen\-dent BMO-type seminorms as the parameter tends to zero. By introducing novel BMO-type seminorms, we provide a unified framework that extends several existing results and yields non-distributional characterizations of Sobolev-type spaces, both in the scalar and in the vecto

Po-Hsuan Huang, Xie-Ru Li, Chi Chuang, Chia-Heng Tu

Quantum Approximate Optimization Algorithm (QAOA) has emerged as a promising solution for combinatorial optimization problems using a hybrid quantum-classical framework. Among combinatorial optimization problems, the Maximum Cut (Max-Cut) problem is particularly important due to its broad applicability in various domains. While QAOA-based Max-Cut solvers hav

Abdelkrim Alahyane, Céline Comte, Matthieu Jonckheere

Synchronous federated learning scales poorly due to the straggler effect. Asynchronous algorithms increase the update throughput by processing updates upon arrival, but they introduce two fundamental challenges: gradient staleness, which degrades convergence, and bias toward faster clients under heterogeneous data distributions. Although algorithms such as A

Shoji Nagamiya

In this article, I trace the early historical developments that ultimately led to the creation of the atomic bomb. Even after the completion of weapons, many scientists continued to argue that nuclear armaments were indispensable for maintaining the global balance of political power [1]. This study focuses on several scientists who confronted profound moral

Maarten Kwaaitaal, Daniel Lourens, Carl S. Davies, Andrei Kirilyuk

Short mid-infrared laser pulses efficiently facilitate ultrafast manipulation of ferroic order parameters, including full reversal of magnetization or ferroelectric polarization, with the invoked mechanisms relating to the properties of polar phonons in ionic crystals. Much less is known, however, about the behaviour of such order parameters in response to a

Thi da Cam Pham, Marc Peigné, Doan Thai Son

We study the asymptotic behavior of a nonlattice random walk in a general cone of $R^d$ . Following the approach initiated by D. Denisov and V. Wachtel in [8], we use a strong approximation of random walks by the Brownian motion and prove local limit theorems, combining integral theorems for random walks in cones with classical theorems for unrestricted rand

Ayaka Sakata, Haruka Tanzawa

We study privacy-preserving sparse linear regression in the high-dimensional regime, focusing on the LASSO estimator. We analyze two widely used mechanisms for differential privacy: output perturbation, which injects noise into the estimator, and objective perturbation, which adds a random linear term to the loss function. Using approximate message passing (

Joy Das Bairagya, Udipta Chakraborti, Sumana Annagiri, Sagar Chakraborty

Braess's paradox -- where adding network capacity increases travel time -- is typically attributed to selfish agents. Although eusocial colonies maximize collective fitness, we find experimentally that \emph{Diacamma indicum} ants exhibit this paradox: Leaders favour the shortest path even when it slows the colony. We present a quantitative model of the expl

Karl Sawaya, Sofia Olhede

Multiplex networks are a powerful framework for representing systems with multiple types of interactions among a common set of entities. Understanding their structure requires statistical tools capturing higher-order cross-layer correlations. We develop a comprehensive framework for estimating and testing dependence in exchangeable multiplex networks through

Yongyang Lv, Xiaohong Li, Ruitao Feng, Xinyu Li

The vigorous development of the Internet has spurred exponential data growth, yet data is predominantly stored in isolated user entities, hampering its full value realization. In large-scale deployment of ``AI+industries'' such as smart medical care, intelligent transportation and smart homes, the gap between data supply and demand continues to widen, and es

Iqra Tariq

This paper investigated the applied science domains and subjects depicted in Marvel Cinematic Universe (MCU) movies and assessed the relationship between technological portrayal and box office success. The study looked at 164 publications in academic literature that employed MCU movies. In addition to the foregoing, the study discovered that MCU movies have

Song-Xiao Li, Su-Dan Wang

Applying the $q$-Zeilberger algorithm, we establish a unified $q$-analogue of the (C.2) and (G.2) supercongruences of Van Hamme, which can be viewed as a refinement of several previously known results. As consequences, we obtain a $q$-analogue of supercongruence involving Bernoulli numbers, as well as a refinement of (G.2) supercongruence.

Jinzhen Han, JinByeong Lee, Yuri Shim, Jisung Kim

Most LLM-driven GIS assistants solve narrow single-step tasks tightly coupled to proprietary platforms such as ArcGIS or QGIS, limiting their use for the multi-step, cross-format pipelines that define professional geospatial analysis. We present GISclaw, a comprehensive open-source agent system that performs realistic GIS analysis end to end - spatial joins,

Thibaut Lescure

We establish a long exact sequence for the homotopy K-theory groups of the algebraic Cuntz-Pimsner rings introduced by Carlsen and Ortega [CO11] by adapting Pimsner's original proof [Pim97] to Cuntz's formalism.

Shiping Chen, Qin Wang, Guangsheng Yu, Xu Wang

Open agentic systems combine LLM-based planning with external capabilities, persistent memory, and privileged execution. They are used in coding assistants, browser copilots, and enterprise automation. OpenClaw is a visible instance of this broader class. Without much attention yet, their security challenge is fundamentally different from that of traditional

Yanzhi Gui, Ling-Bing He, Liu Liu

This work addresses a central challenge in the numerical analysis of the cutoff spatially homogeneous Boltzmann equation: the development of rigorously justified, accurate numerical schemes. We present (i) a novel Fourier spectral method for the equation with Maxwellian and hard potentials, (ii) the derivation of the first rigorous error estimates for the pr

Cesare Davide Pace, Alessandro Marco De Nunzio, Claudio De Stefano, Francesco Fontanella

Markerless biomechanics increasingly relies on 3D skeletal keypoints extracted from video, yet downstream biomechanical mappings typically treat these estimates as deterministic, providing no principled mechanism for frame-wise quality control. In this work, we investigate predictive uncertainty as a quantitative measure of confidence for mapping 3D pose key

Xuemei Fu, Laurence T. Yang, Na Song, Jinxiong Gao

With the continuous advancement of intelligent vehicle technology, the image data generated by vehicles has become increasingly critical in various applications, including driver assistance, traffic monitoring, and safety warning systems. However, this growing reliance on image data also raises pressing concerns regarding its security and privacy protection.

Yi Cai, Alain Blaustein, Tao Xiong, Francis Filbet

We develop and analyze a class of structure-preserving discontinuous Galerkin schemes for the nonlinear Vlasov-Poisson-Fokker-Planck model, reformulated as a hyperbolic system through a Hermite expansion in the velocity variable. We discretize the Vlasov-Fokker-Planck equation with the discontinuous Galerkin method, while the Poisson equation is approximated

Matthias Löwe, Franck Vermet

Generalized Hopfield models with higher-order or exponential interaction terms are known to have substantially larger storage capacities than the classical quadratic model. On the other hand, associative memories for sparse patterns, such as the Willshaw and Amari models, already outperform the classical Hopfield model in the sparse regime. In this paper we

Shuaixin Yang, Yijia Li, Yue Xiao, Yong Liang Guan

Fluid antenna (FA) systems offer novel spatial degrees of freedom (DoFs) with the potential for significant performance gains. Compared to existing works focusing solely on optimizing FA positions at discrete time instants, we introduce the concept of continuous-trajectory fluid antenna (CTFA), which explicitly considers the antenna element's movement trajec

Krishnendu Chatterjee, Ehsan Kafshdar Goharshady, Đorđe Žikelić

Differential privacy (DP) has established itself as one of the standards for ensuring privacy of individual data. However, reasoning about DP is a challenging and error-prone task, hence methods for formal verification and refutation of DP properties have received significant interest in recent years. In this work, we present a novel method for automated for

Jungho Ahn, Tala Eagling-Vose, Felicia Lucke, David Manlove

In a colouring of a graph, a vertex is b-chromatic if it is adjacent to a vertex of every other colour. We consider four well-studied colouring problems: b-Chromatic Number, Tight b-Chromatic Number, Fall Chromatic Number and Fall Achromatic Number, which fit into a framework based on whether every colour class has (i) at least one b-chromatic vertex, (ii) e

Pierre Epron, Adrien Coulet, Mehwish Alam

Despite their strong linguistic capabilities, Large Language Models (LLMs) are computationally demanding and require substantial resources for fine-tuning, which is unadapted to privacy and budget constraints of many healthcare settings. To address this, we present an experimental analysis focused on Biomedical Named Entity Recognition using lightweight LLMs

C. -Y. Dai, J. Quirola-Vásquez, Y. -H. Wang, H. -L. Li

The collapse of massive stars drives explosions that power relativistic fireballs. If only a small amount of matter is entrained, such clean fireballs can expand with Lorentz factors $\Gamma> 100$, accounting for gamma-ray bursts (GRBs). It has been hypothesized that energetic explosions with more baryon contamination, dubbed ``dirty fireballs'', may exist i

Daria Botvynko, Carlos Granero-Belinchon, Simon Van Gennip, Abdesslam Benzinou

We assess the influence of different Eulerian geophysical input fields on Lagrangian drift simulations using DriftNet, a learning-based method designed to simulate Lagrangian drift on the sea surface. Two experiments are conducted: a fully numerical experiment (Benchmark B1) and a real-world drifters-based experiment (Benchmark B2). Both experiments are perf

Shrinidhi Kumbhar, Haofu Liao, Srikar Appalaraju, Kunwar Yashraj Singh

Autoregressive (AR) vision-language models (VLMs) have long dominated multimodal understanding, reasoning, and graphical user interface (GUI) grounding. Recently, discrete diffusion vision-language models (DVLMs) have shown strong performance in multimodal reasoning, offering bidirectional attention, parallel token generation, and iterative refinement. Howev

Rayane Bakari, Olivier Le Blouch, Nicolas Gengembre, Nicholas Evans

Voice anonymisation is used to conceal voice identity while preserving linguistic content. Even if anonymisation seems strong, non-timbral cues such as accent that remain post-anonymisation can help re-identification and reveal sensitive socio-demographic traits. We report a study of residual accent information involving multiple anonymisation systems. We hi

Víctor Hugo Yañez

A topological group $G$ is said to have no small subgroup (resp. no small normal subgroup) if it admits an open neighbourhood of the identity containing no non-trivial subgroup (resp. normal subgroup) of $G$. These properties are usually denoted by NSS (and respectively NSnS). The NSS property plays an important historical role in the solution to the fifth p

Marius Lemm, Carla Rubiliani

We review recent progress on state-dependent Lieb--Robinson bounds for Bose--Hubbard Hamiltonians. In particular, Kuwahara, Vu, and Saito established that, for general bounded-density initial states, the Lieb--Robinson velocity is bounded by $t^{d-1}$ for large times, where $d$ denotes the lattice dimension. We present a shorter proof of the weaker, but stil

E. Nigou, B. Godard, P. Guillard, G. Pineau Des Forêts

Context. A statistically significant sampling of H2 rotational excitation in the diffuse interstellar medium (ISM) is essential to identifying its excitation mechanisms and assessing the importance of H2 in the cooling of the gas and the regulation of thermal pressure. Aims. To complement the statistics provided by ancillary telescopes, we conducted a search

Jumbly Grindrod

Does Large Language Model (LLM) technology suggest a meta-semantic picture i.e. a picture of how words and complex expressions come to have the meaning that they do? One modest approach explores the assumptions that seem to be built into how LLMs capture the meanings of linguistic expressions as a way of considering their plausibility (Grindrod, 2026a, 2026b

Ningyuan Huang, Zhiheng Li, Zheng Fang

Place recognition is crucial for loop closure detection and global localization in robotics. Although mainstream algorithms typically rely on cameras and LiDAR, these sensors are susceptible to adverse weather conditions. Fortunately, the recently developed 4D millimeter-wave radar (4D radar) offers a promising solution for all-weather place recognition. How

Yao Ma, Jia-Ying Xiong

We establish a Bayesian analysis framework with a general Walecka-type relativistic mean-field model to study dense nuclear matter under constraints from nuclear matter properties and neutron star observations. With experimental and observational data well described, we find that pure hadronic descriptions can generate a peak structure in sound velocity by $

S. N. Brandenberger, M. Sanchez, N. Van der Marel, A. A. Vidotto

Close-in rocky planets are the most common type of exoplanets around late M dwarfs, ranging from more temperate worlds to highly irradiated lava planets with molten surfaces, and many theoretical studies have attempted to explain their formation. However, the origin of rocky planets with orbital periods shorter than one day, known as ultra-short-period (USP)

James J. Cusick

Technology change happens quickly such that new trends tend to crowd out the focus on what was new just yesterday. In this paper the peak popularity of the confluence of Object Technologies with early Web adoption is explored through the content of a seminar held in 1999. Distributed architectures were undergoing significant change at this point, and deeper

Tom Potthink, Jasmin Raissy

In this paper, we investigate the bulging of escaping or oscillating Fatou components on invariant fibers for general skew-products, with a focus on the dependence on the perturbation. We show that any orbitally unbounded component is non-bulging for an appropriate choice of perturbation, whereas sufficiently well-behaved perturbations can render it bulging

Haoran Qi, Guohao Xi, Yuan-Biao Zhou, Xinrong Liu

Information units are progressively approaching the fundamental physical limits of the integration density, including in terms of extremely small sizes, multistates and probabilistic traversal. However, simultaneously encompassing all of these characteristics in a unit remains elusive. Here, via real-time in situ electrical monitoring, we clearly observed st

Huda Adam Sirag Mekki, Hui Yuan, Mohanad M. G. Hassan, Zejia Chen

Reliable transmission of 3D point clouds over wireless channels is challenging due to time-varying signal-to-noise ratio (SNR) and limited bandwidth. This paper introduces sensitivity-aware filtering and transmission (SAFT), a learned transmission framework that integrates a Point-BERT-inspired encoder, a sensitivity-guided token filtering (STF) unit, a quan

P. Bianchini, A. L. Varri, A. Askar, A. Marklund

Internal rotation has emerged as a fundamental feature of globular clusters (GCs), yet its origin and long-term evolution remain poorly understood. We explore the evolution of rotating GCs over a Hubble time under the combined influence of two-body relaxation, tidal field, and stellar evolution. We introduce the ROLLIN' simulations, a suite of 25 N-body mode

Isabella Graßl, Gordon Fraser, Daniela Damian

Creative approaches to attract students to software engineering at an early age are emerging, yet their differential impact on gender remains unclear. This study investigates whether design thinking's empathy-driven approach addresses the documented gender gap in interest in software engineering. In a 10-week curriculum-integrated design thinking software de

Ronak B. Dudhat, Vinodray J. Kaneria, Kalpesh M. Popat

We extend the notions of the m-splitting graph Sm(G) and the m-shadow graph Dm(G) to introduce two new graph operations: the (p, q)-generalized splitting graph Sp,q(G) and the (c, k)-shadow-splitting graph Hc,k(G). We derive the adjacency energy of these constructions and as an application, identify several new infinite families of equienergetic and borderen

Xinhang Gao, Junlin Guan, Shuhan Luo, Wenzhuo Li

Interactive video generation has significant potential for scene simulation and video creation. However, existing methods often struggle with maintaining scene consistency during long video generation under dynamic camera control due to limited contextual information. To address this challenge, we propose MemCam, a memory-augmented interactive video generati

Xuerui Zhang, Xuehao Wang, Zhan Zhuang, Linglan Zhao

Lifelong learning aims to preserve knowledge acquired from previous tasks while incorporating knowledge from a sequence of new tasks. However, most prior work explores only streams of homogeneous tasks (\textit{e.g.}, only classification tasks) and neglects the scenario of learning across heterogeneous tasks that possess different structures of outputs. In t

Siyuan Dong, Jinghuai Gao, Yunduo Li, Zhaoqi Gao

Complex salt geometries and strong velocity contrasts pose significant challenges for velocity model building and subsalt imaging. Although full waveform inversion (FWI) provides high-resolution velocity models, its performance strongly depends on the accuracy of initial model. On the other hand, gravity focusing inversion (GFI) can recover compact density d

Rangya Zhang, Jiaping Xiao, Lu Bai, Yuhang Zhang

Continual learning seeks to maintain stable adaptation under non-stationary environments, yet this problem becomes particularly challenging in object detection, where most existing methods implicitly assume relatively balanced visual conditions. In extreme-sparsity regimes, such as those observed in space-based resident space object (RSO) detection scenarios

András Némethi, Gergő Schefler

The general construction of lattice (co)homology assigns to a lattice $\mathbb{Z}^r$ and a weight function $w:\mathbb{Z}^r \to \mathbb{Z}$ a bigraded $\mathbb{Z}[U]$-module $\mathbb{H}_*$. The weight function $w$ is often obtained from some geometric data as the difference of two `height functions'. In this paper we consider the case when these height functi

Rui Wang, Huisi Wu, Jing Qin

Accurate and temporally consistent segmentation of the left ventricle from echocardiography videos is essential for estimating the ejection fraction and assessing cardiac function. However, modeling spatiotemporal dynamics remains difficult due to severe speckle noise and rapid non-rigid deformations. Existing linear recurrent models offer efficient in-conte

Masaki Kashima, Shun-ichi Maezawa, Xuding Zhu

Assume $L$ is a $k$-assignment of a graph $G$. An $L$-packing $\phi$ of $G$ is a sequence $\phi=(\phi_1, \ldots, \phi_k)$ of $k$-mappings such that each $\phi_i$ is an $L$-coloring of $G$, and for each vertex $v$ of $G$, $\{\phi_1(v), \ldots, \phi_k(v)\} = L(v)$ (and hence $\phi_i(v) \ne \phi_j(v)$ when $i \ne j$). We say $G$ is list $k$-packable if for any