May 2025 arXiv papers — page 123

Karine Fouchet

We compute an asymptotic formula for the supremum of the resolvent norm ($\zeta$ -T ) -1 over |$\zeta$| $\ge$ 1 and contractions T acting on an n-dimensional Hilbert space, whose spectral radius does not exceed a given r $\in$ (0, 1). We prove that this supremum is achieved on the unit circle by an analytic Toeplitz matrix.

Shuyang Hou, Zhangxiao Shen, Huayi Wu, Jianyuan Liang

Geospatial code generation is emerging as a key direction in the integration of artificial intelligence and geoscientific analysis. However, there remains a lack of standardized tools for automatic evaluation in this domain. To address this gap, we propose AutoGEEval, the first multimodal, unit-level automated evaluation framework for geospatial code generat

Johannes Kloibhofer, Yde Venema

The two-way modal mu-calculus is the extension of the (standard) one-way mu-calculus with converse (backward-looking) modalities. For this logic we introduce two new sequent-style proof calculi: a non-wellfounded system admitting infinite branches and a finitary, cyclic version of this that employs annotations. As is common in sequent systems for two-way mod

Zhaobin Li, Xiaolei Yang

Active wake control (AWC) has emerged as a promising strategy for enhancing wind turbine wake recovery, but accurately modelling its underlying fluid mechanisms remains challenging. This study presents a computationally efficient wake model that provides end-to-end prediction capability from rotor actuation to wake recovery enhancement by capturing the coupl

Virgile Troude, Didier Sornette

We bring together three key amplification mechanisms in linear dynamical systems: spectral criticality, resonance, and non-normality. We present a unified linear framework that both distinguishes and quantitatively links these effects through two fundamental parameters: (i) the spectral distance to a conventional bifurcation or to a resonance and (ii) a non-

Piotr Borycki, Magdalena Trędowicz, Szymon Janusz, Jacek Tabor

Explainable AI (XAI) methods generally fall into two categories. Post-hoc approaches generate explanations for pre-trained models and are compatible with various neural network architectures. These methods often use feature importance visualizations, such as saliency maps, to indicate which input regions influenced the model's prediction. Unfortunately, they

Xigui Li, Yuanye Zhou, Feiyang Xiao, Xin Guo

Intracranial aneurysms (IAs) are serious cerebrovascular lesions found in approximately 5\% of the general population. Their rupture may lead to high mortality. Current methods for assessing IA risk focus on morphological and patient-specific factors, but the hemodynamic influences on IA development and rupture remain unclear. While accurate for hemodynamic

Chenxi Liu, Yongqiang Chen, Tongliang Liu, James Cheng

System 2 reasoning is one of the defining characteristics of intelligence, which requires slow and logical thinking. Human conducts System 2 reasoning via the language of thoughts that organizes the reasoning process as a causal sequence of mental language, or thoughts. Recently, it has been observed that System 2 reasoning can be elicited from Large Languag

Gerrit Roellinghoff, Samuel T. Spencer, Stefan Funk

A significant source of noise for Imaging Atmospheric Cherenkov Telescopes (IACTs), which are designed to measure air showers caused by astrophysical gamma rays, is optical light emitted from the night sky. This Night Sky Background (NSB) influences IACT operating times and their sensitivity. Thus, for scheduling observations and instrument simulation, an ac

Daniel Rothschild

Daniel Dennett speculated in *Kinds of Minds* 1996: "Perhaps the kind of mind you get when you add language to it is so different from the kind of mind you can have without language that calling them both minds is a mistake." Recent work in AI can be seen as testing Dennett's thesis by exploring the performance of AI systems with and without linguistic train

Andrew Wells, Geraldine Henningsen, Brice Bolane Tchinde Kengne

We present a semi-supervised approach that disaggregates refugee statistics from administrative boundaries to 0.5-degree grid cells across 25 Sub-Saharan African countries. By integrating UNHCR's ProGres registration data with satellite-derived building footprints from Google Open Buildings and location coordinates from OpenStreetMap Populated Places, our la

Le Cheng, Peican Zhu, Yangming Guo, Keke Tang

Hypergraphs offer superior modeling capabilities for social networks, particularly in capturing group phenomena that extend beyond pairwise interactions in rumor propagation. Existing approaches in rumor source detection predominantly focus on dyadic interactions, which inadequately address the complexity of more intricate relational structures. In this stud

Ondřej F. K. Kalenda

We compare several versions of the quantitative Schur property of Banach spaces. We establish their equivalence up to multiplicative constants and provide examples clarifying when the change of constants is necessary. We also give exact results on preservation of the quantitative Schur property by finite or infinite direct sums. We further prove a sufficient

Kobiljon Abdurasulov, Abror Khudoyberdiyev, Feruza Toshtemirova

The geometric classifications of complex $4$-dimensional nilpotent Lie-Yamaguti algebras, $4$-dimensional nilpotent Bol algebras, and $4$-dimensional nilpotent compatible Lie algebras are given.

Victor Morel, Farzaneh Karegar, Cristiana Santos

The rise of cookie paywalls ('pay-or-ok' models) has prompted growing debates around the right to privacy and data protection, monetisation, and the legitimacy of user consent. Despite their increasing use across sectors, limited research has explored how users perceive these models or what shapes their decisions to either consent to tracking or pay. To addr

Francesca Tonolo, Hubert Jóźwiak, Luca Bizzocchi, Mattia Melosso

We present the first experimental determination of room-temperature N2 pressure broadening, speed dependent broadening, and pressure shift coefficients of the three lowest rotational lines of HCN. The experimental results served to assess the accuracy of a low-cost yet accurate computational strategy, which relies on a simplified characterization of the HCN-

Shaohang Wei, Wei Li, Feifan Song, Wen Luo

Temporal reasoning is pivotal for Large Language Models (LLMs) to comprehend the real world. However, existing works neglect the real-world challenges for temporal reasoning: (1) intensive temporal information, (2) fast-changing event dynamics, and (3) complex temporal dependencies in social interactions. To bridge this gap, we propose a multi-level benchmar

Ege Özsoy, Chantal Pellegrini, David Bani-Harouni, Kun Yuan

Surgical procedures unfold in complex environments demanding coordination between surgical teams, tools, imaging and increasingly, intelligent robotic systems. Ensuring safety and efficiency in ORs of the future requires intelligent systems, like surgical robots, smart instruments and digital copilots, capable of understanding complex activities and hazards

Maria Francesca Abbate, Pierre Toxe, Nicolas Maestrali, Marie Gagnaire

The identification and validation of therapeutic antibodies is critical for developing effective treatments for many diseases. We present a computational approach for identifying antibodies targeting GFRAL-specific receptors, receptors implicated in appetite regulation. Using humanized Trianni mice, we conducted a longitudinal study with repeated blood sampl

Chandan Mondal, Satvir Kaur, Jiatong Wu, Siqi Xu

We obtain the deuteron's wave functions as eigenstates of the light-front quantum chromodynamics (QCD) Hamiltonian using a fully relativistic and nonperturbative approach based on light-front quantization, without an explicit confining potential. These eigenstates include six-quark and six-quark--one-gluon components. The deuteron wave function consists of b

Jialun Zhong, Yanzeng Li, Sen Hu, Yang Zhang

Medication recommendations have become an important task in the healthcare domain, especially in measuring the accuracy and safety of medical dialogue systems (MDS). Different from the recommendation task based on electronic health records (EHRs), dialogue-based medication recommendations require research on the interaction details between patients and docto

Sathya Krishnan Suresh, Tanmay Surana, Lim Zhi Hao, Eng Siong Chng

Code-switching (CS) poses a significant challenge for Large Language Models (LLMs), yet its comprehensibility remains underexplored in LLMs. We introduce CS-Sum, to evaluate the comprehensibility of CS by the LLMs through CS dialogue to English summarization. CS-Sum is the first benchmark for CS dialogue summarization across Mandarin-English (EN-ZH), Tamil-E

Junzhi Ning, Cheng Tang, Kaijing Zhou, Diping Song

The scarcity of high-quality, labelled retinal imaging data, which presents a significant challenge in the development of machine learning models for ophthalmology, hinders progress in the field. Existing methods for synthesising Colour Fundus Photographs (CFPs) largely rely on predefined disease labels, which restricts their ability to generate images that

Zhongxiang Sun, Qipeng Wang, Haoyu Wang, Xiao Zhang

Large Reasoning Models (LRMs) have shown impressive capabilities in multi-step reasoning tasks. However, alongside these successes, a more deceptive form of model error has emerged--Reasoning Hallucination--where logically coherent but factually incorrect reasoning traces lead to persuasive yet faulty conclusions. Unlike traditional hallucinations, these err

Blaž Bertalanič, Matej Vnučec, Carolina Fortuna

In today's world, modern infrastructures are being equipped with information and communication technologies to create large IoT networks. It is essential to monitor these networks to ensure smooth operations by detecting and correcting link failures or abnormal network behaviour proactively, which can otherwise cause interruptions in business operations. Thi

Atsushi Inoie, Yoshiaki Inoue

The age of information (AoI) has been studied actively in recent years as a performance measure for systems that require real-time performance, such as remote monitoring systems via communication networks. The theoretical analysis of the AoI is usually formulated based on explicit system modeling, such as a single-server queueing model. However, in general,

Chundra Cathcart

The numeral systems of Indo-Aryan languages such as Hindi, Gujarati, and Bengali are highly unusual in that unlike most numeral systems (e.g., those of English, Chinese, etc.), forms referring to 1--99 are highly non-transparent and cannot be constructed using straightforward rules for forming combinations of tens and digits. As an example, Hindi/Urdu {\it i

Yuanze Hu, Zhaoxin Fan, Xinyu Wang, Gen Li

Lightweight Vision-Language Models (VLMs) are indispensable for resource-constrained applications. The prevailing approach to aligning vision and language models involves freezing both the vision encoder and the language model while training small connector modules. However, this strategy heavily depends on the intrinsic capabilities of the language model, w

Yudong Wang, Hongjiong Tian

This paper investigates the approximation of stochastic delay differential equations (SDDEs) via the backward Euler-Maruyama (BEM) method under generalized monotonicity and Khasminskii-type conditions in the infinite horizon. First, by establishing the uniform moment boundedness and finite-time strong convergence of the BEM method, we prove that for sufficie

Hao Wang, Jindong Han, Wei Fan, Weijia Zhang

Data Assimilation (DA) plays a critical role in atmospheric science by reconstructing spatially continous estimates of the system state, which serves as initial conditions for scientific analysis. While recent advances in diffusion models have shown great potential for DA tasks, most existing approaches remain purely data-driven and often overlook the physic

Yuanye Zhou, Zhaokun Wang, Kai Zhou, Hui Tang

Physics-informed neural networks (PINNs) have emerged as a powerful meshless tool for topology optimization, capable of simultaneously determining optimal topologies and physical solutions. However, conventional PINNs rely on density-based topology descriptions, which necessitate manual interpolation and limit their applicability to complex geometries. To ad

Marcello Passaro, Guillaume Dodet, Fabrice Ardhuin, Paolo Cipollini

The latest version of the European Space Agency's Sea State Climate Change Initiative database adopts a dedicated algorithm (retracker) to reprocess two decades of satellite altimetry measurements and provide long time series of significant wave height in the global ocean. This paper describes the main characteristics of this algorithm, called WHALES, and an

Maksim Zhdanov, Nabil Iqbal, Erik Bekkers, Patrick Forré

Conformal symmetries, i.e.\ coordinate transformations that preserve angles, play a key role in many fields, including physics, mathematics, computer vision and (geometric) machine learning. Here we build a neural network that is equivariant under general conformal transformations. To achieve this, we lift data from flat Euclidean space to Anti de Sitter (Ad

Yeonsu Kim, Junhan Lee, Bingran Wang, John T. Hwang

Forward uncertainty quantification in dynamical systems is challenging due to non-smooth or locally oscillating nonlinear behaviors. Spline dimensional decomposition (SDD) addresses such nonlinearity by partitioning input coordinates via knot placement, but its accuracy is highly sensitive to internal knot locations. Optimizing knots using sequential quadrat

Yingjie Kuang, Tianchen Zhang, Zhen-Wei Huang, Zhongjie Zeng

Accurately predicting customers' purchase intentions is critical to the success of a business strategy. Current researches mainly focus on analyzing the specific types of products that customers are likely to purchase in the future, little attention has been paid to the critical factor of whether customers will engage in repurchase behavior. Predicting wheth

Xiwei Wu, Yueyang Feng, Xiaoyang Lu, Tianchuan Lin

As software systems increase in size and complexity dramatically, ensuring their correctness, security, and reliability becomes an increasingly formidable challenge. Despite significant advancements in verification techniques and tools, their practical application to complex, real-world systems is often hindered by critical gaps in both automation and expres

Zhiguo Ding, Wei Xiong, Qifan Zhang

For any prime power $q$, a polynomial $f(X)\in\F_q[X]$ is ``exceptional'' if it induces bijections of $\F_{q^k}$ for infinitely many $k$; this condition is known to be equivalent to $f(X)$ inducing a bijection of $\F_{q^k}$ for at least one $k$ with $q^k\ge \deg(f)^4$. In this paper, we introduce the notion of an ``exceptional'' extension of local fields of

Davide Bruni, Marco Avvenuti, Nicola Tonellotto, Maurizio Tesconi

Retrieval-augmented generation (RAG) systems are widely used in question-answering (QA) tasks, but current benchmarks lack metadata integration, limiting their evaluation in scenarios requiring both textual data and external information. To address this, we present AMAQA, a new open-access QA dataset designed to evaluate tasks combining text and metadata. Th

Lucio Anderlini, Alessandro Bombini, Clarissa Buti, Djunes Janssens

Future experiments at hadron colliders require an evolution of the tracking sensors to ensure sufficient radiation hardness as well as space and time resolution to handle unprecedented particle fluxes. 3D diamond sensors with laser-graphitized electrodes are promising candidates due to their strong binding energy, small atomic number, and high carrier mobili

Rishi Goel, Casey R. Myers, Sally Shrapnel

Modern machine learning (ML) methods typically fail to adequately capture causal information. Consequently, such models do not handle data distributional shifts, are vulnerable to adversarial examples, and often learn spurious correlations. Causal ML, or causal inference, aims to solve these issues by estimating the expected outcome of counterfactual events,

Maytus Piriyajitakonkij, Rujikorn Charakorn, Weicheng Tao, Wei Pan

Language is a powerful communicative and cognitive tool. It enables humans to express thoughts, share intentions, and reason about complex phenomena. Despite our fluency in using and understanding language, the question of how it arises and evolves over time remains unsolved. A leading hypothesis in linguistics and anthropology posits that language evolved t

Zi Liang, Haibo Hu, Qingqing Ye, Yaxin Xiao

Low rank adaptation (LoRA) has emerged as a prominent technique for fine-tuning large language models (LLMs) thanks to its superb efficiency gains over previous methods. While extensive studies have examined the performance and structural properties of LoRA, its behavior upon training-time attacks remain underexplored, posing significant security risks. In t

Zhan Fa, H. -Q. He

The composite geometry and spectral anisotropy of the solar wind turbulence are very important topics in the investigations of solar wind. In this work, we use the magnetic field and plasma data from Wind spacecraft measured during 1995 January to 2023 December, which covers more than two solar cycles, to systematically investigate these subjects in the cont

Koki Wakiyama, Tomohiro I, Hiroshi Sakamoto

Feature selection is a technique that extracts a meaningful subset from a set of features in training data. When the training data is large-scale, appropriate feature selection enables the removal of redundant features, which can improve generalization performance, accelerate the training process, and enhance the interpretability of the model. This study pro

Marin Šola, Peter Bühlmann, Xinwei Shen

Distributional robustness is a central goal of prediction algorithms due to the prevalent distribution shifts in real-world data. The prediction model aims to minimize the worst-case risk among a class of distributions, a.k.a., an uncertainty set. Causality provides a modeling framework with a rigorous robustness guarantee in the above sense, where the uncer

Ruancun Li, Luis C. Ho, Chang-Hao Chen

The early growth of high-redshift quasars and their host galaxies raises critical questions about their cosmic evolution. We exploit the angular resolution and sensitivity of NIRCam to investigate the host galaxies of 31 quasars at $4\lesssim z\lesssim7$ drawn from multiple JWST surveys. Using a new multi-band forward-modeling code (\textsc{GalfitS}) that in

Alfred Wagner

The second domain variation of the $p$-capacity and the $q$ - torsional rigidity for compact sets in $R^d, d\geq3$ with $1<p<d$ is computed. Conditions on $p$ and $q>1$ are given such that the ball is a local minimzer or maximizer of the product.

Claire Hilaire, Martin Milanič, Đorđe Vasić

We continue the study of $(tw,\omega)$-bounded graph classes, that is, hereditary graph classes in which large treewidth is witnessed by the presence of a large clique, and the relation of this property to boundedness of the tree-independence number, a graph parameter introduced independently by Yolov in 2018 and by Dallard, Milani\v{c}, and \v{S}torgel in 2

Jinke Cao, Qi Guo, Huatang Tan

We propose an optimal control scheme for generating quantum entanglement between two optically-levitated nanoparticles in free space. Specifically, we consider that the mechanical motion frequencies of the two levitated particles are modulated by adjusting the amplitude of the trapping beam. The two particles are coupled through Coulomb interaction, and the

Yu Fan, Jingwei Ni, Jakob Merane, Yang Tian

Long-form legal reasoning remains a key challenge for large language models (LLMs) in spite of recent advances in test-time scaling. To address this, we introduce LEXam, a novel benchmark derived from 340 law exams spanning 116 law school courses across a range of subjects and degree levels. The dataset comprises 7,537 law exam questions in English and Germa

Jongmin Jung, Dongmin Kim, Sihun Lee, Seola Cho

Music exists in various modalities, such as score images, symbolic scores, MIDI, and audio. Translations between each modality are established as core tasks of music information retrieval, such as automatic music transcription (audio-to-MIDI) and optical music recognition (score image to symbolic score). However, most past work on multimodal translation trai

Zhou He, Ning Li, Ning Ran, Liang Li

Scheduling is a key decision-making process to improve the performance of flexible manufacturing systems. Place-timed Petri nets provide a formal method for graphically modeling and analyzing such systems. By generating reachability graphs and combining intelligent search algorithms, operation sequences from the initial state to the target state can be found

Jiaqi Tan, Xu Zheng, Yang Liu

Multi-modal semantic segmentation (MMSS) faces significant challenges in real-world applications due to incomplete, degraded, or missing sensor data. While current MMSS methods typically use self-distillation with modality dropout to improve robustness, they largely overlook inter-modal correlations and thus suffer significant performance degradation when no

Wenbo Yang, Zhongling Wang, Zhou Wang

Image degradation synthesis is highly desirable in a wide variety of applications ranging from image restoration to simulating artistic effects. Existing models are designed to generate one specific or a narrow set of degradations, which often require user-provided degradation parameters. As a result, they lack the generalizability to synthesize degradations

Lucas Georges Gabriel Charpentier, Pierre Lison

Documents revealing sensitive information about individuals must typically be de-identified. This de-identification is often done by masking all mentions of personally identifiable information (PII), thereby making it more difficult to uncover the identity of the person(s) in question. To investigate the robustness of de-identification methods, we present a

M. Tahir Abbas, M. Szymczak, M. Drozd, D. Szymanski

One of the key parameters determining the performance of a luminescent thermometer is its relative sensitivity. In ratiometric luminescence thermometry, high relative sensitivity to temperature variations is typically achieved when the two monitored emission bands exhibit opposite thermal monotonicity. However, realizing a thermal enhancement in the luminesc

Clara Lasaosa, Marcos Fernández, Iván Vila, Jordi Duarte-Campderros

Three-dimensional (3D) pixel sensors are a promising technology for implementing the 4D-tracking paradigm in high-radiation environments. Despite their advantages in radiation tolerance, 3D pixel sensors exhibit non-uniform electric and weighting fields that can degrade timing performance. This study explores the impact of pixel cell geometry on the timing c

Jordi Altayo, Paul Delestrac, David Novo, Simey Yang

As the size of artificial intelligence and machine learning (AI/ML) models and datasets grows, the memory bandwidth becomes a critical bottleneck. The paper presents a novel extended memory hierarchy that addresses some major memory bandwidth challenges in data-parallel AI/ML applications. While data-parallel architectures like GPUs and neural network accele

Le Qui Danh, Trinh Thanh Deo

Let $D$ be a division ring with center $F$, $f(x_1,x_2,\dots, x_m)$ a non-central multilinear polynomial over $F$, and $w(x_1,x_2,\dots,x_m)$ a non-trivial word. In this paper, we investigate conditions under which there exists an element $a \in D$ such that the subfield $F(a)$ generated by $a$ is a maximal subfield of $D$. Specifically, we prove that there

Anna Maschek, David C. Schedl

Detecting an athlete's position on a route and identifying hold usage are crucial in various climbing-related applications. However, no climbing dataset with detailed hold usage annotations exists to our knowledge. To address this issue, we introduce a dataset of 22 annotated climbing videos, providing ground-truth labels for hold locations, usage order, and

Lian Remme, Alexander Weinert, Andre Waschk

Quantum computers do not run in isolation; rather, they are embedded in quantum-classical hybrid architectures. In these setups, a quantum processing unit communicates with a classical device in near-real time. To enable efficient hybrid computations, it is mandatory to optimize quantum-classical hybrid code. To the best of our knowledge, no previous work on

S. Hubrig, A. Vigna-Gómez, S. P. Järvinen, M. Schöller

The system TIC 470710327 is comprised of three main-sequence OB stars, with an inner compact 1.10 d eclipsing binary and a non-eclipsing tertiary on a 52.04 d orbit. With the tertiary mass of 14.5-16 $M_{\odot}$ and both components in the inner eclipsing binary with individual masses of 6--7 and 5.5-6.3 $M_{\odot}$, it is currently the most massive compact s

Yanhua Wen, Lu Ai, Gang Liu, Chuang Li

Byzantine attacks during model aggregation in Federated Learning (FL) threaten training integrity by manipulating malicious clients' updates. Existing methods struggle with limited robustness under high malicious client ratios and sensitivity to non-i.i.d. data, leading to degraded accuracy. To address this, we propose FLTG, a novel aggregation algorithm int

Sota Arakawa, Mikito Furuichi, Daisuke Nishiura

Hierarchical granular piles composed of aggregates are key structural features in both geoscience and planetary science, from fault gouge in seismic zones to the internal structures of comets. Although experimental studies have suggested a multi-step evolution in their packing structure, this hypothesis has lacked numerical validation. In this study, we perf

Ben Liu, Zhen Qin

Image generation models have achieved widespread applications. As an instance, the TarFlow model combines the transformer architecture with Normalizing Flow models, achieving state-of-the-art results on multiple benchmarks. However, due to the causal form of attention requiring sequential computation, TarFlow's sampling process is extremely slow. In this pap

Adarsh Singh

The development of novel pharmaceuticals represents a significant challenge in modern science, with substantial costs and time investments. Deep generative models have emerged as promising tools for accelerating drug discovery by efficiently exploring the vast chemical space. However, this rapidly evolving field lacks standardized evaluation protocols, imped

Ioana Ciotir, Franco Flandoli, Dan Goreac

This work establishes a scaling limit theorem for the Stefan problem incorporating a mushy region, demonstrating that solutions to stochastic variants with turbulent transport terms converge to the solution to a deterministic partial differential equation. The analysis builds upon recent advances in stochastic phase-change modeling and turbulent flow mathema

Pavel Exner, Léo Morin

We investigate a two-dimensional magnetic Laplacian with two radially symmetric magnetic wells. Its spectral properties are determined by the tunneling between them. If the tunneling is weak and the wells are mirror symmetric, the two lowest eigenfunctions are localized in both wells being distributed roughly equally. In this note we show that an exponential

Ruopei Sun, Jianfeng Cai, Jinhua Zhu, Kangwen Zhao

RLHF has emerged as a predominant approach for aligning artificial intelligence systems with human preferences, demonstrating exceptional and measurable efficacy in instruction following tasks; however, it exhibits insufficient compliance capabilities when confronted with complex multi-instruction tasks. Conventional approaches rely heavily on human annotati

Shuo Sun, Yimin Zhao, Christina Dao Wen Lee, Jiawei Sun

As the field progresses toward Artificial General Intelligence (AGI), there is a pressing need for more comprehensive and insightful evaluation frameworks that go beyond aggregate performance metrics. This paper introduces a unified rating system that jointly models the difficulty of individual test cases and the competency of AI models (or humans) across vi

Zheng Wu, Pengzhou Cheng, Zongru Wu, Lingzhong Dong

Graphical user interface (GUI) agents have recently emerged as an intriguing paradigm for human-computer interaction, capable of automatically executing user instructions to operate intelligent terminal devices. However, when encountering out-of-distribution (OOD) instructions that violate environmental constraints or exceed the current capabilities of agent

Yi C. Huang, Iskander A. Taimanov

We describe the Ozawa solution to the Davey--Stewartson II equation from the point of view of surface theory by presenting a soliton deformation of surfaces which is ruled by the Ozawa solution. The Ozawa solution blows up at certain moment and we describe explicitly the corresponding singularity of the deformed surface.

Jingyuan Li

This paper introduces and formally verifies a novel geometric framework for first-order stochastic dominance (FSD) in $N$ dimensions using the Lean 4 theorem prover. Traditional analytical approaches to multi-dimensional stochastic dominance rely heavily on complex measure theory and multivariate calculus, creating significant barriers to formalization in pr

Boya Fan, Ruipeng Shen

In this work we consider the wave equation with a repulsive potential, either on the half line ${\mathbb R}^+$ or the Euclidean space ${\mathbb R}^d$ with $d\geq 3$. We combine the operator theory and the inward/outward energy theory to deduce a modified wave operator for repulsive potentials decaying like $|x|^{-\beta}$ with $\beta>1/3$. In particular the r

Christian Braun, Alexander Lilienbeck, Daniel Mentjukov

Legal contracts possess an inherent, semantically vital structure (e.g., sections, clauses) that is crucial for human comprehension but whose impact on LLM processing remains under-explored. This paper investigates the effects of explicit input text structure and prompt engineering on the performance of GPT-4o and GPT-4.1 on a legal question-answering task u

Muhamed Kuric, Martin Zach, Andreas Habring, Michael Unser

We consider the problem of sampling from a product-of-experts-type model that encompasses many standard prior and posterior distributions commonly found in Bayesian imaging. We show that this model can be easily lifted into a novel latent variable model, which we refer to as a Gaussian latent machine. This leads to a general sampling approach that unifies an

Hengxing Cai, Jinhan Dong, Jingjun Tan, Jingcheng Deng

Unmanned Aerial Vehicle (UAV) Vision-and-Language Navigation (VLN) is vital for applications such as disaster response, logistics delivery, and urban inspection. However, existing methods often struggle with insufficient multimodal fusion, weak generalization, and poor interpretability. To address these challenges, we propose FlightGPT, a novel UAV VLN frame

Avinash Kumar, Kyeolhee Kang, Ammar ul Hassan, Jaeyoung Choi

Handwritten fonts have a distinct expressive character, but they are often difficult to read due to unclear or inconsistent handwriting. FontFusionGAN (FFGAN) is a novel method for improving handwritten fonts by combining them with printed fonts. Our method implements generative adversarial network (GAN) to generate font that mix the desirable features of ha

Zhuo Yang, Daolang Wang, Lingli Ge, Beilun Wang

Many real-world scientific and industrial applications require the optimization of expensive black-box functions. Bayesian Optimization (BO) provides an effective framework for such problems. However, traditional BO methods are prone to get trapped in local optima and often lack interpretable insights. To address this issue, this paper designs Reasoning BO,

Md Sultanul Islam Ovi

Efficiently scaling deep neural networks across GPU clusters requires navigating complex trade-offs between computational throughput, memory utilization, and synchronization overhead. This paper presents a unified empirical evaluation of three dominant distributed training paradigms: Distributed Data Parallel (DDP), Fully Sharded Data Parallel (FSDP), and th

Zifeng Cheng, Zhonghui Wang, Yuchen Fu, Zhiwei Jiang

Extracting sentence embeddings from large language models (LLMs) is a practical direction, as it requires neither additional data nor fine-tuning. Previous studies usually focus on prompt engineering to guide LLMs to encode the core semantic information of the sentence into the embedding of the last token. However, the last token in these methods still encod

Neethu Kuriakose, Arun Ashok, Christian Grewing, André Zambanini

Memristors are promising devices for scalable and low power, in-memory computing to improve the energy efficiency of a rising computational demand. The crossbar array architecture with memristors is used for vector matrix multiplication (VMM) and acts as kernels in neuromorphic computing. The analog conductance control in a memristor is achieved by applying

Hiroshi Nozaki, Masanori Sawa

A weighted $t$-design in $\mathbb{R}^d$ is a finite weighted set that exactly integrates all polynomials of degree at most $t$ with respect to a given probability measure. A fundamental problem is to construct weighted $t$-designs with as few points as possible. Victoir (2004) proposed a method to reduce the size of weighted $t$-designs while preserving the

Xuejie Liu, Haoming Zheng, Dianyong Chen, Hongxia Huang

Since the discovery of the $T_{cc}$ double-charm tetaquark by the LHCb collaboration, the field of the theoretical research on heavy quarks has advanced rapidly, with increasing interest in exploring the light quark sector. In this study, the quark model is employed to systematically analyze the double-strange tetraquark system. Both the meson-meson configur

Jian Wu, Ulrich Sander, Carol Flannagan, Minxiang Zhao

The use of representative pre-crash scenarios is critical for assessing the safety impact of driving automation systems through simulation. However, a gap remains in the robust evaluation of the similarity between synthetic and real-world pre-crash scenarios and their crash characteristics. Without proper validation, it cannot be ensured that the synthetic t

Jianfeng Cai, Wengang Zhou, Zongmeng Zhang, Jiale Hong

Multimodal large language models (MLLMs) have achieved remarkable progress in video understanding.However, hallucination, where the model generates plausible yet incorrect outputs, persists as a significant and under-addressed challenge in the video domain. Among existing solutions, activation engineering has proven successful in mitigating hallucinations in

Qin-Cheng Zheng, Shao-Qun Zhang, Shen-Huan Lyu, Yuan Jiang

Isolation Forest (iForest) stands out as a widely-used unsupervised anomaly detector, primarily owing to its remarkable runtime efficiency and superior performance in large-scale tasks. Despite its widespread adoption, a theoretical foundation explaining iForest's success remains unclear. This paper focuses on the inductive bias of iForest, which theoretical

Renato Leme, Carlos Olarte, Elaine Pimentel, Marcelo E. Coniglio

We present a non-deterministic semantic framework for all modal logics in the modal cube, extending prior works by Kearns and others. Our approach introduces modular and uniform multi-valued non-deterministic matrices (Nmatrices) for each logic, where necessitation is captured by the systematic use of level valuations. The semantics is grounded in an eight-v

Jing Liu, Haozheng Wang, Yueheng Li

Large language models struggle with representing and generating rare tokens despite their importance in specialized domains. In this study, we identify neuron structures with exceptionally strong influence on language model's prediction of rare tokens, termed as rare token neurons, and investigate the mechanism for their emergence and behavior. These neurons

Han Sun, Zhen Sun, Zongmin Zhang, Linzhao Jia

Large Language Models (LLMs) are emerging as dominant forces for textual style transfer. However, for arbitrary style transfer, LLMs face two key challenges: (1) considerable reliance on manually-constructed prompts and (2) rigid stylistic biases inherent in LLMs. In this paper, we propose a novel Synthesize-then-Decode (SynDec) approach, which automatically

Hulin Li

Multi-head detectors typically employ a features-fused-pyramid-neck for multi-scale detection and are widely adopted in the industry. However, this approach faces feature misalignment when representations from different hierarchical levels of the feature pyramid are forcibly fused point-to-point. To address this issue, we designed an independent hierarchy py

Alfonso Maiellaro, Francesco Romeo, Mattia Trama, Irene Gaiardoni

The interplay between spin and charge degrees of freedom in low-dimensional systems is a cornerstone of modern spintronics, where achieving all-electrical control of spin currents is a major goal. Spin-orbit interactions provide a promising mechanism for such control, yet understanding how spin and charge transport emerge from microscopic principles remains

Ranjan Kushwaha, S. Sarkar, Gautam Biswas

This study utilizes Large Eddy Simulation (LES) to investigate the impact of longitudinal triangular riblets on the laminar-to-turbulent transition in boundary layer flow. Five cases are examined: one involving a flat plate and four with ribbed plates. Among the ribbed cases, three use a riblet aspect ratio of two, whereas one has an aspect ratio of one. Arr

Zhi-Zhang Peng, Zu-Cheng Chen, Lang Liu

The recent measurements from the Atacama Cosmology Telescope (ACT) favor a higher value of the scalar spectral index $n_s$ compared to the Planck data, challenging many well-established inflationary models. In this work, we investigate the viability of polynomial potential inflation in light of the latest ACT data, systematically analyzing cases from $n=2$ t

Wenjiao Feng, Rongxing Xiao, Zonghang Li, Hongfang Yu

Node and link churn in multi-party, cross-region clusters over wide-area networks (WANs) often disrupts distributed training. However, checkpoint-based recovery and cloud-centric autoscaling react slowly and assume centralized control, which is misaligned with the self-governed setup where institutions can freely join and leave. This paper proposes Chaos, a

Xilong Cheng, Yunxiao Qin, Yuting Tan, Zhengnan Li

Existing LLM-based role-playing methods often rely on superficial textual descriptions or simplistic metrics, inadequately modeling both intrinsic and extrinsic character dimensions. Additionally, they typically simulate character memory with implicit model knowledge or basic retrieval augment generation without explicit memory alignment, compromising memory

James A. Sellers, Roberto Tauraso

A century ago, P. A. MacMahon introduced two families of generating functions, $$ \sum_{1\leq n_1<n_2<\cdots<n_t}\prod_{k=1}^t\frac{q^{n_k}}{(1-q^{n_k})^2} \quad\text{ and } \sum_{\substack{1\leq n_1<n_2<\cdots<n_t\\ \text{$n_1,n_2,\dots,n_t$ odd}}}\prod_{k=1}^t\frac{q^{n_k}}{(1-q^{n_k})^2}, $$ which connect sum-of-divisors functions and integer partitions.

Joseph T. A. Peterson, Vishala Arya, John L. Junkins

A geometric interpretation of the equinoctial elements is given with a connection to orthogonal rotations and attitude dynamics in Euclidean 3-space. An identification is made between the equinoctial elements and classic Rodrigues parameters. A new set of equinoctial elements are developed using the modified Rodrigues parameters, thereby removing the coordin

Wei-Chen Liao, Ti-Rong Wu, I-Chen Wu

Multi-agent reinforcement Learning (MARL) is often challenged by the sight range dilemma, where agents either receive insufficient or excessive information from their environment. In this paper, we propose a novel method, called Dynamic Sight Range Selection (DSR), to address this issue. DSR utilizes an Upper Confidence Bound (UCB) algorithm and dynamically

Samy Abbes, Vincent Jugé

A concurrent system is defined as a monoid action of a trace monoid on a finite set of states. Concurrent systems represent state models where the state is distributed and where state changes are local. Starting from a spectral property on the combinatorics of concurrent systems, we prove the existence and uniqueness of a Markov measure on the space of infin