November 2025 arXiv papers — page 67

Jiajie Guo, Qingpeng Zhu, Jin Zeng, Xiaolong Wu

Multimodal large language models (MLLMs) have achieved significant progress in image and language tasks due to the strong reasoning capability of large language models (LLMs). Nevertheless, most MLLMs suffer from limited spatial reasoning ability to interpret and infer spatial arrangements in three-dimensional space. In this work, we propose a novel vision e

Jonghwan Rhee, Richard Dodson, Alexander Williamson, Martin Meyer

The data storage requirements for deep spectral line observations with next-generation radio interferometers like the Australian Square Kilometre Array Pathfinder (ASKAP) and the Square Kilometre Array (SKA) are challenging. The default strategy is to reduce data after each daily observation and stack the resulting images. Although computationally efficient,

Xiongjun Guan, Zhiyu Pan, Jianjiang Feng, Jie Zhou

Finger pose offers promising opportunities to expand human computer interaction capability of touchscreen devices. Existing finger pose estimation algorithms that can be implemented in portable devices predominantly rely on capacitive images, which are currently limited to estimating pitch and yaw angles and exhibit reduced accuracy when processing large-ang

Matt Landreman, Humberto Torreblanca, Antoine Cerfon

In fusion reactor design, steels under consideration for the blanket are ferromagnetic, so the steel's effect on the plasma physics must be examined. For efficient calculation of these fields, we can exploit the fact that the magnetic material gives a small perturbation relative to the fields from the electromagnetic coils and plasma. Moreover the magnetizat

Jian'an Zhang

We study reinforcement learning (RL) on volatility surfaces through the lens of Scientific AI. We ask whether axiomatic no-arbitrage laws, imposed as soft penalties on a learned world model, can reliably align high-capacity RL agents, or mainly create Goodhart-style incentives to exploit model errors. From classical static no-arbitrage conditions we build a

Timmie M. R. Lagermann, Kristina Sophia Carter, Su Mei Gwen Ho, Luís Cruz

We examine per action energy consumption across four web user interface (UI) automation testing frameworks to determine whether consistent tendencies can guide energy-aware test design. Using a controlled client-server setup with external power metering, we repeat each UI action (refresh, click variants, checkbox, drag&drop, input-text, scroll) 35 times. Acr

Zeyu Hu, Wenrui Li, Jun Yan, Panpan Zhang

Community detection is a central task in network analysis, with applications in social, biological, and technological systems. Traditional algorithms rely primarily on network topology, which can fail when community signals are partly encoded in node-specific attributes. Existing covariate-assisted methods often assume the number of clusters is known, involv

Koena Ronny Mabokela, Tim Schlippe, Matthias Wölfel

Sentiment analysis can aid in understanding people's opinions and emotions on social issues. In multilingual communities sentiment analysis systems can be used to quickly identify social challenges in social media posts, enabling government departments to detect and address these issues more precisely and effectively. Recently, large-language models (LLMs) h

Wenrui Zhang, Xinggang Wang, Bin Feng, Wenyu Liu

Optical Chemical Structure Recognition (OCSR) plays a pivotal role in modern chemical informatics, enabling the automated conversion of chemical structure images from scientific literature, patents, and educational materials into machine-readable molecular representations. This capability is essential for large-scale chemical data mining, drug discovery pipe

Artem Frenk, Roee Shraga

Our work introduces SAVeD (Semantically Aware Version Detection), a contrastive learning-based framework for identifying versions of structured datasets without relying on metadata, labels, or integration-based assumptions. SAVeD addresses a common challenge in data science of repeated labor due to a difficulty of similar work or transformations on datasets.

Julius P. J. Krebbekx, Eder Baron-Prada, Roland Tóth, Amritam Das

Scaled Relative Graphs (SRGs) provide a novel graphical frequency-domain method for the analysis of nonlinear systems, where Linear Time-Invariant (LTI) systems are the fundamental building block. To analyze feedback loops with unstable LTI components, the hard SRG is required, since it aptly captures the input/output behavior on the extended $L_2$ space. In

Jozef Strecka, Michal Nemcik

Magnetic, thermodynamic, and magnetocaloric properties of a spin-1/2 Heisenberg octahedral chain with three distinct exchange interactions are investigated in an external magnetic field using the variational method, extended localized-magnon approach, and exact diagonalization. Variational arguments rigorously establish two distinct fragmented phases in the

Patrick Bammer, Lothar Banz, Miriam Schönauer, Andreas Schröder

In this paper, we consider a class of systems of nonlinear equations, which arise in discretized mixed formulations of problems in solid mechanics by $hp$-finite elements. We introduce a semismooth Newton solver for this specific class and prove its well-definedness and local convergence. Thereby, the analysis heavily relies on a special eigenvalue interplay

David Ribar, Clifford E Woodward, Jan Forsman

We explore interactions between equally charged surfaces, in the presence of simple salt and either neutral or monovalently charged polyampholytes. We consider the possibility of using these charged polymers as crude models of ion clusters. The latter have been hypothesised to form in concentrated aqueous salt solutions, and are possibly related to anomalous

Thorsten Buss, Henry Day-Hall, Frank Gaede, Gregor Kasieczka

The physics programs of current and future collider experiments necessitate the development of surrogate simulators for calorimeter showers. While much progress has been made in the development of generative models for this task, they have typically been evaluated in simplified scenarios and for single particles. This is particularly true for the challenging

Leonhard Held, Fadoua Balabdaoui, Saverio Fontana, Samuel Pawel

Reducing the number of experimental units is one of the three pillars of the 3R principles (Replace, Reduce, Refine) in animal research. At the same time, statistical error rates need to be controlled to enable reliable inferences and decisions. This paper proposes to adopt diagnostic likelihood ratios and the diagnostic odds ratio to statistical hypothesis

Marii Ojastu, Hele-Andra Kuulmets, Aleksei Dorkin, Marika Borovikova

In this paper, we present a localized and culturally adapted Estonian translation of the test set from the widely used commonsense reasoning benchmark, WinoGrande. We detail the translation and adaptation process carried out by translation specialists and evaluate the performance of both proprietary and open source models on the human translated benchmark. A

Sabrina Sadiekh, Elena Ericheva, Chirag Agarwal

Advances in unsupervised probes such as Contrast-Consistent Search (CCS), which reveal latent beliefs without relying on token outputs, raise the question of whether these methods can reliably assess model alignment. We investigate this by examining the sensitivity of CCS to harmful vs. safe statements and by introducing Polarity-Aware CCS (PA-CCS), a method

Ryuji Tanimoto

Let $k$ be an algebraically closed field of positive characteristic $p$ and let $\mathbb{G}_a$ denote the additive group of $k$. Let $n \geq 1$ and let ${\rm Mat}(n, k[T])^E$ denote the set of all exponential matrices of ${\rm Mat}(n, k[T])$. Let $\mathbb{E}_{\geq 0}(n, k)$ denote the set of all group homomorphisms from $(\mathbb{Z}/p\mathbb{Z})^r$ to ${\rm

V. V. Kiselev

At high energies a form of fragmentation function for a heavy quark into a hadron is substantiated to agree with a reciprocity relation to the distribution of heavy quark as the virtual parton in the hadron. The relevance of the relation is analysed in its application to empirical data.

Krzysztof Kutak, Michał Praszałowicz

In this contribution we report on recent extension of one dimensional dipole cascade models to account for saturation and transition to vacuum \cite{Kutak:2025syp}. We analyze properties of the models using Quantum Information tools. Furthermore, we present a description of the hadronic entropy measured by LHCb and predictions for the purity measurement. %we

Andrei V. Korol, Andrey V. Solov'yov

This paper presents a quantitative analysis of the impact of inelastic collisions with atoms in a crystalline environment on the channeling efficiency and intensity of the channeling radiation for high-energy electrons and positrons passing through oriented crystalline targets. This analysis is based on numerical simulations of the channeling process, which

Sofiane Ben Amor, Guillaume Guerard, Loup-Noé Levy

Smart grid technological advances present a recent class of complex interdisciplinary modeling and increasingly difficult simulation problems to solve using traditional computational methods. To simulate a smart grid requires a systemic approach to integrated modeling of power systems, energy markets, demand-side management, and much other resources and asse

Andrea Medaglia

We present a Direct Simulation Monte Carlo (DSMC) method for the spatially homogeneous multispecies Landau-Fokker-Planck equation. The scheme is derived from a first-order approximation of the multispecies Boltzmann operator in the grazing collision limit and employs a regularized, easy-to-sample scattering kernel that removes the need for iterative solvers

Shuai-Kang Yang, Bei You, Niek Bollemeijer, Phil Uttley

We present an analysis of the covariance spectrum of the black hole X-ray binary MAXI J1820+070 during its hard state. For the first time, we extend coherence and covariance studies into the hard X-ray band up to 150 keV. We detect a clear drop in coherence above 30 keV on both short- and long-timescales relative to the 2-10 keV reference band. To investigat

Anita Behme, Markus Riedle, Shend Thaqi

This article studies regularity properties of multiplicative stochastic processes on infinite-dimensional Lie groups. We investigate conditions under which these processes admit c\`adl\`ag modifications and derive bounds on their local behavior. Our approach builds on the local equivalence of Banach-Lie groups and Banach spaces via the exponential and logari

Ilja Siroš, Jakob Heirwegh, Dave Singelée, Bart Preneel

With the rapid growth of IoT, secure and efficient mesh networking has become essential. Thread has emerged as a key protocol, widely used in smart-home and commercial systems, and serving as a core transport layer in the Matter standard. This paper presents ThreadFuzzer, the first dedicated fuzzing framework for systematically testing Thread protocol implem

Chuancheng Shi, Shangze Li, Shiming Guo, Simiao Xie

Multilingual text-to-image (T2I) models have advanced rapidly in terms of visual realism and semantic alignment, and are now widely utilized. Yet outputs vary across cultural contexts: because language carries cultural connotations, images synthesized from multilingual prompts should preserve cross-lingual cultural consistency. We conduct a comprehensive ana

Xavier Bardina, Salim Boukfal

In the present paper we show that the processes $X_n = \{X_n(t) \colon t \in [0,1]\}$, $n \in \mathbb{N}$, defined by $X_n(t) = \sqrt{n}C\int_0^t (-1)^{L(nu)} du$, where $L = \{L(t) \colon t \geq 0\}$ is a renewal processes whose inter-arrival times satisfy some integrability conditions and $C > 0$ is some normalizing constant, weakly converge, in the space

Xavier Bardina, Salim Boukfal, Marc Cano, Carles Rovira

In previous works, Bardina and Rovira (2023) constructed a family of processes that converge strongly towards Brownian motion, defined from renewal processes, are constructed. In this paper we prove that some of these processes can be utilized to build approximations of Gaussian processes such as fractional Brownian motion or multiple Stratonovich integrals

Stéphanie M. C. Abo, Ruth E. Baker

Cell populations invade through a combination of proliferation and motility. Proliferation depends on the internal timing of cell division: how long cells take to complete the cell cycle. This timing varies substantially within (and across) cell types, creating age structure where cells at different times since their last division have different propensities

Johan F. Triana, Felipe Herrera

Controlling bond breaking is a long-standing goal in molecular physics. Infrared nanocavities are currently being developed for reaching exotic coupling regimes of cavity QED with a few molecules, but it is not well understood how chemical reactions would proceed in such systems. To address this, we study infrared laser photodissociation of a single CS$_{2}$

Xingyue Yang, Shibo Fang, Zongmeng Yang, Pin Ho

Altermagnetism, characterized by zero net magnetization and symmetry-protected spin-split band structures, has recently emerged as a promising platform for spintronics. In altermagnetic tunnel junctions (AMTJs), the suppression of tunneling in the antiparallel configuration relies on the mismatch between spin-polarized conduction channels in momentum space.

Tom Nahrendorf, Stefan Minner, Helfried Binder, Richard Zinck

Premium automotive manufacturers face increasingly complex forecasting challenges due to high product variety, sparse variant-level data, and volatile market dynamics. This study addresses monthly automobile demand forecasting across a multi-product, multi-market, and multi-level hierarchy using data from a German premium manufacturer. The methodology combin

Zsombor Fehér

We describe a Python module that we developed to calculate cobordism maps induced on Khovanov homology. As applications of our program, we compute these maps for all incompressible Seifert surfaces for prime knots up to 10 crossings, and distinguish many ribbon disks arising from symmetries of the boundary knots.

Jonas Conneryd, Yassine Ghannane, Shuo Pang

We present a generic way to obtain level lower bounds for (promise) CSP hierarchies from degree lower bounds for algebraic proof systems. More specifically, we show that pseudo-reduction operators in the sense of Alekhnovich and Razborov [Proc. Steklov Inst. Math. 2003] can be used to fool the cohomological $k$-consistency algorithm. As applications, we prov

Sebastian Böhm, Florian Sattler, Norbert Siegmund, Sven Apel

Performance is a volatile property of a software system and frequent performance profiling is required to keep the knowledge about a software system's performance behavior up to date. Repeating all performance measurements after every revision is a cost-intensive task, especially in the presence of configurability, where one has to measure multiple configura

Tatsuro Kawakami, Teppei Takamatsu, Shou Yoshikawa

In this paper, we apply Fedder-type criteria for quasi-$F$-splitting to provide explicit computations of quasi-$F$-split heights for Calabi-Yau hypersurfaces, bielliptic surfaces, Fano varieties, and rational double points. We also find interesting phenomena concerned with inversion of adjunction, fiber products, Fano varieties, and general fibers of fibrati

Suchetan G. Uppur, Hemant Kumar, Vaibhav Kumar

Training autonomous driving and navigation systems requires large and diverse point cloud datasets that capture complex edge case scenarios from various dynamic urban settings. Acquiring such diverse scenarios from real-world point cloud data, especially for critical edge cases, is challenging, which restricts system generalization and robustness. Current me

Zi Wang, Xingqiao Wang, Sangah Lee, Xiaowei Xu

The rapid expansion of scholarly literature presents significant challenges in synthesizing comprehensive, high-quality academic surveys. Recent advancements in agentic systems offer considerable promise for automating tasks that traditionally require human expertise, including literature review, synthesis, and iterative refinement. However, existing automat

L. Correia, C. Bot, J. Chastenet, A. Rymar

Compared to the well-studied infrared and radio domains, galaxy emission in the millimeter (mm) - centimeter (cm) range has been less observed. In this domain, galaxy emission consists of thermal dust, free-free and synchrotron emissions with a possible additional contribution from anomalous microwave emission (AME) peaking near 1 cm.The aim of this study is

Abderraouf Bounjad, Aoran Wu, Cyril Chevarin, Patrick Guenoun

The filtration membranes are often elaborated through a phase separation process where a polymer rich phase and a polymer poor phase spontaneously form through spinodal decomposition. One process that is still not well understood from a theoretical point of view is the Non-Solvent induced phase separation where a thermodynamically stable film of a a polymer

Leone Costi, Dario Izzo

In this work, we propose a simulator, based on the open-source physics engine MuJoCo, for the design and control of soft robotic nets for the autonomous removal of space debris. The proposed simulator includes net dynamics, contact between the net and the debris, self-contact of the net, orbital mechanics, and a controller that can actuate thrusters on the f

Shady Agwa, Yikang Shen, Shiwei Wang, Themis Prodromakis

Nowadays, we are witnessing an Artificial Intelligence revolution that dominates the technology landscape in various application domains, such as healthcare, robotics, automotive, security, and defense. Massive-scale AI models, which mimic the human brain's functionality, typically feature millions and even billions of parameters through data-intensive matri

Daowen Qiu

Multi-stack machines and Turing machines can simulate to each other. In this note, we give a succinct definition of multi-stack machines, and from this definition it is clearly seen that pushdown automata and deterministic finite automata are special cases of multi-stack machines. Also, with this mode of definition, pushdown automata and deterministic pushdo

Ibtsam A. R. Alroily, Brahim Chaourar

Let $n$ be a nonnegative integer, and $f(n)$ the number of unlabeled finite topologies on $n$ points. We prove that $f(n+m) \geq f(n) f(m)$ both for the labeled and unlabeled cases. Moreover, we prove a similar inequality for labeled and unlabeled $T_0$ topologies.

Jinfeng Wen, Yuehan Sun

Serverless computing has rapidly emerged as a popular cloud computing paradigm. It enables developers to implement function-level tasks, i.e., serverless functions, without managing infrastructure. While reducing operational overhead, it poses challenges, especially for novice developers. Developing functions from scratch requires adapting to heterogeneous,

The CMS Electromagnetic Calorimeter Group

The performance of the CMS electromagnetic calorimeter upgraded readout electronics, developed for the High-Luminosity phase of the LHC, is discussed. Data collected in two beam test campaigns conducted in 2018 and 2021 at the H4 and H2 beam lines of the CERN SPS are analyzed. Time and energy resolutions are measured on a $5\times 5$ matrix of lead tungstate

François-Xavier Wicht, Zhengwei Tong, Shunfan Zhou, Hang Yin

Private BitTorrent trackers enforce upload-to-download ratios to prevent free-riding, but suffer from three critical weaknesses: reputation cannot move between trackers, centralized servers create single points of failure, and upload statistics are self-reported and unverifiable. When a tracker shuts down, users lose their contribution history and cannot pro

Omer Rochman, Gilles Louppe

Neural PDE solvers used for scientific simulation often violate governing equation constraints. While linear constraints can be projected cheaply, many constraints are nonlinear, complicating projection onto the feasible set. Dynamical PDEs are especially difficult because constraints induce long-range dependencies in time. In this work, we evaluate two trai

Aymeric Allemand, Anne-Laure Biance, Christophe Ybert, Laurent Joly

Nanofluidic transport is ubiquitous in natural systems from extra-cellular communication in biology to geological phenomena, and promotes the emergence of new technologies such as energy harvesting and water desalination. While experimental access to ultraconfined fluids has advanced rapidly, their behavior challenges conventional theoretical descriptions ba

Haijiang Liu, Jinguang Gu, Xun Wu, Daniel Hershcovich

As Large Language Models (LLMs) increasingly influence high-stakes decision-making across global contexts, ensuring their alignment with diverse cultural values has become a critical governance challenge. This study presents a Multi-Layered Auditing Platform for Responsible AI that systematically evaluates cross-cultural value alignment in China-origin and W

Bulat Khaertdinov, Mirela Popa, Nava Tintarev

Large vision-language models (VLMs) enable intuitive visual search using natural language queries. However, improving their performance often requires fine-tuning and scaling to larger model variants. In this work, we propose a mechanism inspired by traditional text-based search to improve retrieval performance at inference time: relevance feedback. While re

Jiaye Qian, Ge Zheng, Yuchen Zhu, Sibei Yang

Despite their impressive performance across a wide range of tasks, Large Vision-Language Models (LVLMs) remain prone to hallucination. In this study, we propose a comprehensive intervention framework aligned with the transformer's causal architecture in LVLMs, integrating the effects of different intervention paths on hallucination. We find that hallucinatio

Yuming Yang, Michael K. Ng, Zhigang Jia, Wei Wang

In this work, we address the challenging problem of blind deconvolution for color images. Existing methods often convert color images to grayscale or process each color channel separately, which overlooking the relationships between color channels. To handle this issue, we formulate a novel quaternion fidelity term designed specifically for color image blind

Johannes Nicklaus, Lea Brass, Gunnar Schubert

We study linear policy approximations for the risk-conscious operation of an industrial energy system with uncertain wind power, significant and variable electricity demand, and high thermal output, as found in a modern foundry. The system incorporates thermal storage and operates under rolling forecasts, leading to a sequential decision-making framework. To

Lucas Darius Konrad

In this paper I propose a micro-based innovation driven general equilibrium growth-model allowing for endogenous entry and exit as well as three different types of research. I make the novel distinction between three types of firms, namely basic and applied research where applied research is again differentiated into high and low type research to account for

Evgeniya Mutsenik, Aidar Sultanov, Leonie Kaczmarek, Matthias Schmelz

We report the first experimental realization of a scalable basic cell for quantum routing, enabling coherent control and exchange of microwave photons between two spatially separated superconducting waveguides coupled via a single transmon qubit. The cell was characterized at 10 mK with an average input signal of approximately 1 photon at approximately 6 GHz

Riccardo Tedoldi, Ola Engkvist, Patrick Bryant, Hossein Azizpour

Sampling useful three-dimensional molecular structures along with their most favorable conformations is a key challenge in drug discovery. Current state-of-the-art 3D de-novo design flow matching or diffusion-based models are limited to generating a single conformation. However, the conformational landscape of a molecule determines its observable properties

Hang Gong, Alexey Bobrick, Francisco Garzón, Deven Bhakta

We present the results of deep near-infrared imaging of the recently discovered helium star pulsar binary J1928$+$1815 situated in the Galactic plane. Our observations did not achieve significant detections, providing limiting magnitudes of J=23.7 and H=22.2, which are both 2.4\,magnitudes deeper than the expected J and H magnitudes for a modeled stripped he

Fernando Diaz-Diaz, Elena Candellone, Miguel A. Gonzalez-Casado, Emma Fraxanet

Signed networks provide a principled framework for representing systems in which interactions are not merely present or absent but qualitatively distinct: friendly or antagonistic, supportive or conflicting, excitatory or inhibitory. This polarity reshapes how we think about structure and dynamics in complex systems: a negative tie is not simply a missing po

Zeyu Huang, Zuyu Xu, Yuanhao Zhang, Chengzhong Liu

Scenic Live Streams (SLS), capturing real-world scenic sites from fixed cameras without streamers, have gained increasing popularity recently. They afford unique real-time lenses into remote sites for viewers' synchronous and collective engagement. Foregrounding its lack of dynamism and interactivity, we aim to maximize the potential of SLS by making it inte

Kohei Suzuki

Simulated annealing (SA) is a key algorithm for solving combinatorial optimization problems, which model numerous real-world systems. While SA is commonly used to solve quadratic unconstrained binary optimization (QUBO) problems, many practical problems are more naturally formulated using integer variables. We therefore study quadratic and higher-order uncon

Aleksandr V. Karpenko, Andrey B. Matsko, Sergey P. Vyatchanin

Optomechanical generation of entangled optical beams is usually hindered by thermal noise. We present a theoretical study of low frequency entanglement generation between two optical harmonics emitted from a cavity optomechanical system operating in the resolved-sideband regime. The system comprises three nearly equidistant optical modes in a high-finesse ca

Dongjun Wu, Yankai Lin

This paper presents a new interpretation of the Lyapunov and Riccati equations from the perspective of positive system theory. We show it is possible to construct positive systems related to these equations, and then certain conclusions -- such as the existence and uniqueness of solutions -- can be drawn from positive systems theory. Specifically, under stan

Mohammed Alnemari

This paper presents a novel framework combining group equivariant convolutional neural networks (G-CNNs) with equivariant-aware structured pruning to produce compact, transformation-invariant models for resource-constrained environments. Equivariance to rotations is achieved through the C4 cyclic group via the e2cnn library,enabling consistent performance un

Anshul Singh, Rohan Chaudhary, Gagneet Singh, Abhay Kumary

The impressive performance of VLMs is largely measured on benchmarks that fail to capture the complexities of real-world scenarios. Existing datasets for tabular QA, such as WikiTableQuestions and FinQA, are overwhelmingly monolingual (English) and present tables in a digitally perfect, clean format. This creates a significant gap between research and practi

Alessio Saccuti, Riccardo Monica, Jacopo Aleotti

In this paper a novel ROS2 driver for UR robot manipulators is presented, based on the ur_rtde C++ library. The proposed driver aims to be a flexible solution, adaptable to a wide range of applications. The driver exposes the high-level commands of Universal Robots URScripts, and custom commands can be added using a plugin system. Several commands have been

Rohit Prasad

The increasing diversity and complexity of transformer workloads at the edge present significant challenges in balancing performance, energy efficiency, and architectural flexibility. This paper introduces NX-CGRA, a programmable hardware accelerator designed to support a range of transformer inference algorithms, including both linear and non-linear functio

Diego Berti, Gian Marco Canneori, Roberto Ciccarelli, Irene De Blasi

In this paper, we consider periodic solutions of the $n$-body problem that satisfy symmetry constraints, expressed through invariance under finite group actions. We focus on their stability properties and present algorithms specifically designed for the computation of Floquet multipliers and Morse indices. Numerical results are provided to illustrate our met

Bing Guo, Wanfeng Qi

We study the constructions of piecewise rational interpolation kernels that are supported on the interval $[-2,2]$, and present one novel rational cubic/linear and five quartic/linear interpolation kernels. All proposed kernels are symmetric, $C^1$ continuous, and possess certain degrees of approximation order. The proposed quartic/linear interpolation kerne

Atmane Ayoub Mansour Bahar, Andrés Alayón Glazunov, Romaric Duvignau

Privacy concerns around 5G, the latest generation of mobile networks, are growing, with fears that its deployment may increase exposure to privacy risks. This perception is largely driven by the use of denser deployments of small antenna systems, which enable highly accurate data collection at higher speeds and closer proximity to mobile users. At the same t

Jiaxin Chen, Hongsheng Zheng, Hongliang Chen, Qia Shen

The symmetry of a material fundamentally governs its spin transport properties. While unconventional spin transport phenomena have been predominantly explored in low-symmetry systems (e.g., $C_{1v}$ symmetry), high-symmetry crystals--which constitute the majority of industry-compatible materials--are generally expected to exhibit only conventional spin-trans

Sota Takagi, Miki Saijo, Takumi Ohashi

Community Supported Agriculture (CSA) has been recognized globally as a promising framework that embeds agriculture within social relations, yet its diffusion remains limited in contexts such as Japan. Existing studies have largely focused on either consumer or producer participation in isolation, offering fragmented insights and leaving unexplored how their

Sunit Ghosh, Jitendriya Swain

Let $\mathcal{L}$ be the special Hermite operator on $\mathbb{C}^n$. As a continuation of the recent results in \cite{SG}, we establish new Strichartz estimates for systems of orthonormal functions associated with general flows of the form $e^{-it\phi(\mathcal{L})}$, where $ \phi : \mathbb{R}^{+} \to \mathbb{R} $ is a smooth function. Our approach relies on

Yufei Luo, Xiang Gu, Jian Sun

Transition states (TSs) are crucial for understanding reaction mechanisms, yet their exploration is limited by the complexity of experimental and computational approaches. Here we propose TS-DFM, a flow matching framework that predicts TSs from reactants and products. By operating in molecular distance geometry space, TS-DFM explicitly captures the dynamic c

Xudong Wu, Guangxu Yang, Penghui Yao

We investigates a model of hybrid classical-quantum communication complexity, in which two parties first exchange classical messages and subsequently communicate using quantum messages. We study the trade-off between the classical and quantum communication for composed functions of the form $f\circ G^n$, where $f:\{0,1\}^n\to\{\pm1\}$ and $G$ is an inner pro

Zhangyu Ge, Xu He, Lingfei Mo, Xiaolin Meng

The brain's Path Integration (PI) mechanism offers substantial guidance and inspiration for Brain-Inspired Navigation (BIN). However, the PI capability constructed by the Continuous Attractor Neural Networks (CANNs) in most existing BIN studies exhibits significant computational redundancy, and its operational efficiency needs to be improved; otherwise, it w

Stefan Ivić, Siniša Družeta, Luka Grbčić

Benchmarking optimization algorithms is fundamental for the advancement of computational intelligence. However, widely adopted artificial test suites exhibit limited correspondence with the diversity and complexity of real-world engineering optimization tasks. This paper presents a new benchmark suite comprising 235 bounded, continuous, unconstrained optimiz

Shanshan Li, Da Huang, Yu He, Yanwei Fu

In daily life, people often move through spaces to find objects that meet their needs, posing a key challenge in embodied AI. Traditional Demand-Driven Navigation (DDN) handles one need at a time but does not reflect the complexity of real-world tasks involving multiple needs and personal choices. To bridge this gap, we introduce Task-Preferenced Multi-Deman

Amir Abboud, Ron Safier, Nathan Wallheimer

We initiate the study of combinatorial algorithms for Triangle Detection in $H$-free graphs. The goal is to decide if a graph that forbids a fixed pattern $H$ as a subgraph contains a triangle, using only "combinatorial" methods that notably exclude fast matrix multiplication. Our work aims to classify which patterns admit a subcubic speedup, working towards

Charbel Moussa, Pierre Montmitonnet

The present paper is a short introduction to metal forming. The paper highlights the different disciplines that should be considered when analyzing metal forming. Hence, mechanical flow, heat flow, mechanical and thermal contact, and microstructure evolution are presented within the perspective of metal forming. For every aspect, well-established knowledge i

Yusuf Çelebi, Özay Ezerceli, Mahmoud El Hussieni

This study presents PARROT (Persuasion and Agreement Robustness Rating of Output Truth), a robustness focused framework designed to measure the degradation in accuracy that occurs under social pressure exerted on users through authority and persuasion in large language models (LLMs) the phenomenon of sycophancy (excessive conformity). PARROT (i) isolates cau

Tomas Javurek, Michal Gregor, Sebastian Kula, Marian Simko

The paper introduces DelTriC (Delaunay Triangulation Clustering), a clustering algorithm which integrates PCA/UMAP-based projection, Delaunay triangulation, and a novel back-projection mechanism to form clusters in the original high-dimensional space. DelTriC decouples neighborhood construction from decision-making by first triangulating in a low-dimensional

Florian Krötz, Xiao-Ting Michelle To, Korbinian Staudacher, Dieter Kranzlmüller

We present a practical course targeting graduate students with prior knowledge of the basics of quantum computing. The practical aims to deepen students' understanding of fundamental concepts in quantum computing by implementing quantum circuit simulators. Through hands-on experience, students learn about different methods to simulate quantum computing, incl

Chaowei Fang, Bolin Fu, De Cheng, Lechao Cheng

Realistic image super-resolution (SR) focuses on transforming real-world low-resolution (LR) images into high-resolution (HR) ones, handling more complex degradation patterns than synthetic SR tasks. This is critical for applications like surveillance, medical imaging, and consumer electronics. However, current methods struggle with limited real-world LR-HR

Jureeporn Yuennan, Farruh Atamurotov, Phongpichit Channuie

The combination of the data from the Dark Energy Spectroscopic Instrument (DESI) with the recent measurements from the Atacama Cosmology Telescope (ACT) indicate that the scalar spectral index \( n_s \) has a larger value than the Planck 2018 which leads to tension within standard inflationary models. In this study in order to explain the new data, We consid

Mordecai Waegell

A recent experiment raises a supposed challenge to Bohmian mechanics, claiming to observe stationary states, which should have zero Bohm velocity, while indirectly measuring a nonzero speed based on how an evanescent wavefunction spreads from one waveguide to another coupled waveguide. There were numerous problems with this experiment and how it was interpre

Yining Ding, Kihun Nam, Jiaqiang Wen

In this paper, we study a class of real-valued mean-field backward stochastic differential equations (BSDEs) with generators of quadratic growth in the control variable and the mean-field term. Under this assumption, together with a bounded terminal condition, we establish the existence and uniqueness of solutions. Our approach departs from classical fixed-p

Alex Casarotti, Søren Gammelgaard, Alex Massarenti

We study the unirationality of surface conic bundles $\pi\colon S\to\mathbb P^1$ over an arbitrary field $k$ with discriminant degree $d_S=8$, the first case beyond the del Pezzo range. We divide these surfaces in four families and produce explicit rational multisections via tangent constructions and Cremona transformations. Over $C_1$ fields we obtain Zaris

Lisa-Marie Schilling, Christian Bornkessel, Anna-Malin Schiffarth, Thanh Tam Julian Ta

The introduction of 5G New Radio networks with massive MIMO technology has complicated electromagnetic field exposure assessments for radiation protection. Massive MIMO transmission enables beamforming, beam steering, and spatial multiplexing across multiple transmission layers, with the number of simultaneous transmission paths depending on the rank of the

Kai Ryen Bush, Kjetil Børkje

Entanglement between remote quantum mechanical systems enables a range of quantum information tasks in communication, computation and distributed sensing. Large numbers of entangled subsystems also require experimentally accessible and practically feasible methods of verifying the genuine, i.e., simultaneous, entanglement of all subsystems. We have derived a

Shubham Sonarghare, Prasad Deshpande, Ciaran Hogan, Deepika-Rani Kaliappan-Mahalingam

Accurate BEV semantic segmentation from fisheye imagery remains challenging due to extreme non-linear distortion, occlusion, and depth ambiguity inherent to wide-angle projections. We present a distortion-aware BEV segmentation framework that directly processes multi-camera high-resolution fisheye images,utilizing calibrated geometric unprojection and per-pi

Cris Claessens, Christiaan Viviers, Giacomo D'Amicantonio, Egor Bondarev

We introduce SPECTRE, a fully transformer-based foundation model for volumetric computed tomography (CT). Our Self-Supervised & Cross-Modal Pretraining for CT Representation Extraction (SPECTRE) approach utilizes scalable 3D Vision Transformer architectures and modern self-supervised and vision-language pretraining strategies to learn general-purpose CT repr

Sizhe Zhou, Jiawei Han

LLM-based conversational agents still struggle to maintain coherent, personalized interaction over many sessions: fixed context windows limit how much history can be kept in view, and most external memory approaches trade off between coarse retrieval over large chunks and fine-grained but fragmented views of the dialogue. Motivated by neo-Davidsonian event s

Kunyi Li, Michael Niemeyer, Sen Wang, Stefano Gasperini

Recent advances in dense 3D reconstruction have demonstrated strong capability in accurately capturing local geometry. However, extending these methods to incremental global reconstruction, as required in SLAM systems, remains challenging. Without explicit modeling of global geometric consistency, existing approaches often suffer from accumulated drift, scal

Jiayi Chen, Jieqi Shi, Jing Huo, Chen Wu

The rapid progress of Large Language Models (LLMs) has brought substantial computational and memory demands, spurring the adoption of low-bit quantization. While 8-bit and 4-bit formats have become prevalent, extending quantization to 2 bits remains challenging due to severe accuracy degradation. To address this, we propose Residual Refinement Quantization (

G. Bertrand, C. Buil, M. Le Lain, V. Desnoux

We present the results of a STAROS monitoring campaign on the bright eclipsing binary star alpha Draconis. Over 200 high-resolution spectra were obtained by an international group of amateur astronomers. We were able to calculate an homogeneously covered radial velocity curve and redetermine the orbital elements of the alpha Draconis system. From the data se

Tao Yuan, Haoli Bai, Yinfei Pan, Xuyang Cao

With the increasing size of large language models, layer pruning has gained increased attention as a hardware-friendly approach for model compression. However, existing layer pruning methods struggle to simultaneously address key practical deployment challenges, including performance degradation, high training costs, and limited acceleration. To overcome the

Yang-Hui He

We argue how AI can assist mathematics in three ways: theorem-proving, conjecture formulation, and language processing. Inspired by initial experiments in geometry and theoretical physics in 2017, we summarize how this emerging field has grown over the past years, and show how various machine-learning algorithms can help with pattern detection across discipl