March 2025 arXiv papers — page 43

Marco Spanghero, Filip Geib, Ronny Panier, Panos Papadimitratos

Global Navigation Satellite Systems (GNSS) are fundamental in ubiquitously providing position and time to a wide gamut of systems. Jamming remains a realistic threat in many deployment settings, civilian and tactical. Specifically, in Unmanned Aerial Vehicles (UAVs) sustained denial raises safety critical concerns. This work presents a strategy that allows d

Andrea Tramacere, Riccardo Campana, Enrico Massaro, Fabrizio Bocchino

A search for $\gamma$-ray emission from SNRs in the Large Magellanic Cloud (LMC) based on the detection of concentrations in the arrival direction Fermi-LAT images of photons at energies higher than 10 GeV found significant evidence for 9 of these sources. This analysis was based on data collected in the time window since August 4 2008 to August, 4 2020 (12

Runmin Gong, Qiaohua Yang, Shihong Zhang

Frank et al. (J. Funct. Anal., 2022) stated that there is no relation between the reversed Hardy-Littlewood-Sobolev (HLS) inequalities and reverse Sobolev inequalities. However, we demonstrate that reverse Sobolev inequalities of order $\gamma\in(\frac{n}{2},\frac{n}{2}+1)$ on the $n$-sphere can be readily derived from the reversed HLS inequalities. For the

Weiyi You, Mingyang Zhang, Leheng Zhang, Xingyu Zhou

Current diffusion-based super-resolution (SR) approaches achieve commendable performance at the cost of high inference overhead. Therefore, distillation techniques are utilized to accelerate the multi-step teacher model into one-step student model. Nevertheless, these methods significantly raise training costs and constrain the performance of the student mod

Felix Vogel, Walid Bousselham, Anna Kukleva, Nina Shvetsova

Vision-language foundation models have shown impressive capabilities across various zero-shot tasks, including training-free localization and grounding, primarily focusing on localizing objects in images. However, leveraging those capabilities to localize actions and events in videos is challenging, as actions have less physical outline and are usually descr

Mohammad S. Parsa, Lukasz Golab

Migraine literacy among the public is known to be low, and this lack of understanding has a negative impact on migraineurs' quality of life. To understand this impact, we use text mining methods to study migraine discussion on the Reddit social media platform. We summarize the findings in the form of "four things people should know about chronic migraines":

P. Assis, R. Conceição, P. J. Costa, M. Freitas

Measuring the energy spectrum of air shower components crucial for understanding primary cosmic rays and the physical processes governing their interactions in the atmosphere. However, accurately measuring the energy of shower particles reaching the ground is challenging due to the inherent simplicity of typical cosmic ray experiments. This study takes advan

Stéphane Fischler, Tanguy Rivoal

Zeros of Bessel functions $J_\alpha$ play an important role in physics. They are a motivation for studying zeros of exponential polynomials defined over $\overline{\mathbb{Q}}$, and more generally of $E$-functions. In this paper we partially characterize $E$-functions with zeros of the same multiplicity, and prove a special case of a conjecture of Jossen on

Dante D. Sánchez-Gallegos, Diana Carrizales-Espinoza, Alejandro Zequeira, Catherine Torres-Charles

Cloud computing has become a popular solution for organizations implementing Earth Observation Systems (EOS). However, this produces a dependency on provider resources. Moreover, managing and executing tasks and data in these environments are challenges that commonly arise when building an EOS. This paper presents GeoNimbus, a serverless framework for compos

Francesco Micheli, Efe C. Balta, Anastasios Tsiamis, John Lygeros

We address the challenge of sequential data-driven decision-making under context distributional uncertainty. This problem arises in numerous real-world scenarios where the learner optimizes black-box objective functions in the presence of uncontrollable contextual variables. We consider the setting where the context distribution is uncertain but known to lie

Mathieu Oléron, Gregoire Clement, Samuel Hidalgo Caballero, Masoodah Gunny

Droplet generation under steady conditions is a common microfluidic method for producing biphasic systems. However, this process works only over a limited range of imposed pressure: beyond a critical value, a stable liquid jet can instead form. Furthermore, for a given geometry the pressure conditions set both the generation rate of droplets and their volume

Nicole Bäuerle, Tamara Göll

In this paper, we consider $n$ agents who invest in a general financial market that is free of arbitrage and complete. The aim of each investor is to maximize her expected utility while ensuring, with a specified probability, that her terminal wealth exceeds a benchmark defined by her competitors' performance. This setup introduces an interdependence between

Deependra Sharma, Arpit Singh, Md. Samsul Islam, Basanta Nandi

In the present work, O$-$O collisions at $\sqrt{s_{NN}}$ = 7 TeV and p$-$O collisions at $\sqrt{s_{NN}}$ = 9.9 TeV are studied using PYTHIA8/Angantyr model for heavy-ion collisions. The theoretically predicted $\alpha$-cluster structure of oxygen nucleus is implemented in the model to investigate the effect of initial configuration of oxygen nucleus on final

Hugo A. Camargo, Yichao Fu, Viktor Jahnke, Kuntal Pal

A classical dynamical system can be viewed as a probability space equipped with a measure-preserving time evolution map, admitting a purely algebraic formulation in terms of the algebra of bounded functions on the phase space. Similarly, a quantum dynamical system can be formulated using an algebra of bounded operators in a non-commutative probability space

Wei Long, Xingyu Zhou, Leheng Zhang, Shuhang Gu

Transformer-based methods have achieved remarkable results in image super-resolution tasks because they can capture non-local dependencies in low-quality input images. However, this feature-intensive modeling approach is computationally expensive because it calculates the similarities between numerous features that are irrelevant to the query features when o

Yaru Fu, Fuchao He, Zheng Shi, Haijun Zhang

The integration of pinching antenna systems with non-orthogonal multiple access (NOMA) has emerged as a promising technique for future 6G applications. This paper is the first to investigate power minimization for NOMA-assisted pinching antenna systems utilizing multiple dielectric waveguides. We formulate a total power minimization problem constrained by ea

Pierre Pansu

The aim of homotopy theory in topology is to simplify, after continuous deformation, continuous maps between topological spaces. What prevents this from happening are homotopy invariants. This raises quantitative questions: $\bullet$ Is the calculation of invariants possible (decidable)? If so, at what cost? $\bullet$ Is it possible to construct low-complexi

Kazuyuki Sakamoto, Hirotaka Ishikawa, Takashi Wake, Chie Ishimoto

Spatially controlling the Fermi level of topological insulators and keeping its electronic states stable are indispensable processes to put this material into practical use for semiconductor spintronics devices. So far, however, such a method has not been established yet. Here we show a novel method for doping hole into n-type topological insulators Bi$_2$X$

Jan Steckel, Noori BniLam

Accurate knowledge and control of the phase center in antenna arrays is essential for high-precision applications such as Global Navigation Satellite Systems (GNSS), where even small displacements can introduce significant localization errors. Traditional beamforming techniques applied to array antennas often neglect the variation of the phase center, result

Haoyang Ma, Alastair F. Donaldson, Qingchao Shen, Yongqiang Tian

By July 2025, smart contracts collectively manage roughly $120 billion in assets. With Solidity remaining the dominant language for smart contract development, the correctness of Solidity compilers has become critically important. However, Solidity compilers are bug-prone, with a recent study revealing that combinations of qualifiers in Solidity programs are

Weiyan Shi, Xuanzhi Wang, Kai Niu, Leye Wang

Detecting whether a target crosses the given zone (e.g., a door) can enable various practical applications in smart homes, including intelligent security and people counting. The traditional infrared-based approach only covers a line and can be easily cracked. In contrast, reusing the ubiquitous WiFi devices deployed in homes has the potential to cover a lar

Manon Ballu, Zhibin Yao, Bastien Mirmand, David Papoular

We have performed microwave spectroscopy of sodium least-bound molecular states, improving the precision of the knowledge of their energies at zero magnetic field by almost three orders of magnitude. Our experimental observations give us access also to states submitted to predissociation, a phenomenon where a bound molecular state can naturally decay into th

Jiaying Chen, Xian'an Jin, Gang Zhang

Let $G$ be an embedded graph and $A$ an edge subset of $G$. The partial dual of $G$ with respect to $A$, denoted by $G^A$, can be viewed as the geometric dual $G^*$ of $G$ over $A$. If $A=E(G)$, then $G^A=G^*$. Denote by $\gamma(G^A)$ the genus of the embedded graph $G^A$. The maximum partial-dual genus of $G$ is defined as $$^\partial\gamma_{M}(G):=\max_{A

Antoine Bottenmuller, Florent Magaud, Arnaud Demortière, Etienne Decencière

With the aim of estimating the abundance map from observations only, linear unmixing approaches are not always suitable to spectral images, especially when the number of bands is too small or when the spectra of the observed data are too correlated. To address this issue in the general case, we present a novel approach which provides an adapted spatial densi

Martina Gisti, David J. Luitz, Maxime Debertolis

We extend the concept of operator charge in the context of an abelian U (1) symmetry and apply this framework to symmetry-preserving matrix product operators (MPOs), enabling the description of operators projected onto specific sectors of the corresponding symmetry. Leveraging this representation, we study the effect of interactions on the scrambling of info

Yousef Sadegheih, Pratibha Kumari, Dorit Merhof

Traditional brain lesion segmentation models for multi-modal MRI are typically tailored to specific pathologies, relying on datasets with predefined modalities. Adapting to new MRI modalities or pathologies often requires training separate models, which contrasts with how medical professionals incrementally expand their expertise by learning from diverse dat

Abdoulaye Sakho, Emmanuel Malherbe, Carl-Erik Gauthier, Erwan Scornet

This study investigates rare event detection on tabular data within binary classification. Standard techniques to handle class imbalance include SMOTE, which generates synthetic samples from the minority class. However, SMOTE is intrinsically designed for continuous input variables. In fact, despite SMOTE-NC-its default extension to handle mixed features (co

Pierre A Mandrin

We propose a "guide" towards quantisation of gravity based on quantum matter in a statistical mechanics context. On one hand, a statistical mechanics model naturally arises from the thermodynamic interpretation of horizons in Rindler space. On the other hand, the path integral formulation of quantum field theory can be interpreted from the point of view of s

P. G. Silvestrov, Vyacheslavs Kashcheyevs, Patrik Recher

Recent experimental progress in development of on-demand sources of electrons propagating along depleted quantum Hall edge channels has enabled creation and characterization of sufficiently compact single- and two-electron distributions with picosecond scale control and the possibility of measuring details of these distributions. Here, we consider the effect

Junkai Jiang, Ruochen Li, Yibin Yang, Yihe Chen

This paper addresses a generalization problem of Multi-Agent Pathfinding (MAPF), called Collaborative Task Sequencing - Multi-Agent Pathfinding (CTS-MAPF), where agents must plan collision-free paths and visit a series of intermediate task locations in a specific order before reaching their final destinations. To address this problem, we propose a new approa

Ludovic Tuncay, Etienne Labbé, Thomas Pellegrini

AudioSet is one of the most used and largest datasets in audio tagging, containing about 2 million audio samples that are manually labeled with 527 event categories organized into an ontology. However, the annotations contain inconsistencies, particularly where categories that should be labeled as positive according to the ontology are frequently mislabeled

Du Tang, Yingjie Jiang, Ji Luo, Yu Chen

Utilizing the precise reference waveform regenerated by post-forward error correction (FEC) data, the fiber-longitudinal power profile estimation based on the minimum-mean-square-error method (MMSE-PPE) has been validated as an effective tool for absolute power monitoring. However, when post-FEC data is unavailable, it becomes necessary to rely on pre-FEC ha

Hao Ai, Kunyi Wang, Zezhou Wang, Hao Lu

Multimodal large language models (MLLMs) have demonstrated impressive performance in various vision-language (VL) tasks, but their expensive computations still limit the real-world application. To address this issue, recent efforts aim to compress the visual features to save the computational costs of MLLMs. However, direct visual compression methods, e.g. e

Jaeah Lee, Changwoon Choi, Young Min Kim, Jaesik Park

Understanding 3D motion from videos presents inherent challenges due to the diverse types of movement, ranging from rigid and deformable objects to articulated structures. To overcome this, we propose Liv3Stroke, a novel approach for abstracting objects in motion with deformable 3D strokes. The detailed movements of an object may be represented by unstructur

Shih-Wen Ke, Guan-Yu Lai, Guo-Lin Fang, Hsi-Yuan Kao

Large language models (LLMs) are designed to align with human values in their responses. This study exploits LLMs with an iterative prompting technique where each prompt is systematically modified and refined across multiple iterations to enhance its effectiveness in jailbreaking attacks progressively. This technique involves analyzing the response patterns

Yunxiang Ma, Tong Zhou

This paper extends previous identification method to the asynchronous sampling scenario, enabling the simultaneous handling of asynchronous, non-uniform, and slow-rate sampling conditions. Moving beyond lumped systems, the proposed framework targets the identification of interconnection structure of Networked Dynamic Systems (NDS) with descriptor-form subsys

Colin Brisson, Ayoub Kahfy, Marc Bui, Frédéric Constant

We present the Named Entity Recognition system developed by the Edit Dunhuang team for the EvaHan2025 competition. Our approach integrates three core components: (1) Pindola, a modern transformer-based bidirectional encoder pretrained on a large corpus of Classical Chinese texts; (2) a retrieval module that fetches relevant external context for each target s

Qian Wang, Aleksandar Cvejic, Abdelrahman Eldesokey, Peter Wonka

We introduce EditCLIP, a novel representation-learning approach for image editing. Our method learns a unified representation of edits by jointly encoding an input image and its edited counterpart, effectively capturing their transformation. To evaluate its effectiveness, we employ EditCLIP to solve two tasks: exemplar-based image editing and automated edit

Jiahao Qin, Feng Liu, Lu Zong

In the realm of computer graphics, the ability to learn continuously from non-stationary data streams while adapting to new visual patterns and mitigating catastrophic forgetting is of paramount importance. Existing approaches often struggle to capture and represent the essential characteristics of evolving visual concepts, hindering their applicability to d

Akira Masuoka

Recently, Venkatesh extended the category equivalence between affine algebraic groups and Harish-Chandra pairs, which was proved by the author in the supersymmetric context, to the situation of the Verlinde category in positive characteristic. But the proof is incomplete at some basic point, the author thinks. Amending that we refine the result. Our construc

Bargava Subramanian, Naveen Kumarasami, Praveen Shastry, Raghotham Sripadraj

Study Design: This study presents the development of an autonomous AI system for MRI spine pathology detection, trained on a dataset of 2 million MRI spine scans sourced from diverse healthcare facilities across India. The AI system integrates advanced architectures, including Vision Transformers, U-Net with cross-attention, MedSAM, and Cascade R-CNN, enabli

Younès Moussaoui, Diana Mateus, Nasrin Taheri, Saïd Moussaoui

Implicit neural representations (INRs) have demonstrated strong capabilities in various medical imaging tasks, such as denoising, registration, and segmentation, by representing images as continuous functions, allowing complex details to be captured. For image reconstruction problems, INRs can also reduce artifacts typically introduced by conventional recons

Hanwen Liang, Xian Zhong, Wenxuan Liu, Yajing Zheng

Restoring clear frames from rainy videos presents a significant challenge due to the rapid motion of rain streaks. Traditional frame-based visual sensors, which capture scene content synchronously, struggle to capture the fast-moving details of rain accurately. In recent years, neuromorphic sensors have introduced a new paradigm for dynamic scene perception,

Team Wan, Ang Wang, Baole Ai, Bin Wen

This report presents Wan, a comprehensive and open suite of video foundation models designed to push the boundaries of video generation. Built upon the mainstream diffusion transformer paradigm, Wan achieves significant advancements in generative capabilities through a series of innovations, including our novel VAE, scalable pre-training strategies, large-sc

Size Zheng, Jin Fang, Xuegui Zheng, Qi Hou

Large deep learning models have achieved state-of-the-art performance in a wide range of tasks. These models often necessitate distributed systems for efficient training and inference. The fundamental building blocks for distributed model execution are intra-layer parallel operators. The most effective approach to enhancing the performance of intra-layer par

Ben Hudson, Leonid I. Gurvits, Daniel Palumbo, Sara Issaoun

Very Long Baseline Interferometry (VLBI) provides the finest angular resolution of all astronomical observation techniques. However, observations with Earth-based instruments are approaching fundamental limits on angular resolution. These can only be overcome by placing at least one interferometric element in space. In this paper, several concepts of spacebo

Hamid Arian Zad, Michal Jaščur, Azam Zoshki, Ralph Kenna

We investigate various types of quantum entanglement in the octanuclear heterometallic $3d/4f$ complexes denoted as Ni$^{2+}_4$Gd$^{3+}_4$ under an external magnetic field, using the exact diagonalization approach. These molecular magnets, which can be effectively described by Heisenberg spin models, consist of two identical $\{\text{Ni}^{2+}_2\text{Gd}^{3+}

Tao Wu, Tie Luo

Adversarial attacks in black-box settings are highly practical, with transfer-based attacks being the most effective at generating adversarial examples (AEs) that transfer from surrogate models to unseen target models. However, their performance significantly degrades when transferring across heterogeneous architectures -- such as CNNs, MLPs, and Vision Tran

Zitian Wang, Yue Liao, Kang Rong, Fengyun Rao

Preference alignment has emerged as an effective strategy to enhance the performance of Multimodal Large Language Models (MLLMs) following supervised fine-tuning. While existing preference alignment methods predominantly target hallucination factors, they overlook the factors essential for multi-modal comprehension capabilities, often narrowing their improve

Lee Chae-Yeon, Oh Hyun-Bin, Han EunGi, Kim Sung-Bin

Recent advancements in speech-driven 3D talking head generation have made significant progress in lip synchronization. However, existing models still struggle to capture the perceptual alignment between varying speech characteristics and corresponding lip movements. In this work, we claim that three criteria -- Temporal Synchronization, Lip Readability, and

Huang-Jing Zheng, Sheng-Qin Feng

Relativistic heavy-ion collisions generate ultra-strong magnetic fields that interact with the quark-gluon plasma (QGP), a key focus of high-energy physics research.This study investigates QGP energy density evolution under time-dependent magnetic fields within a (1 +1)D relativistic magnetohydrodynamic (RMHD) framework integrated with Bjorken flow. Three ma

Haitong Liu, Kuofeng Gao, Yang Bai, Jinmin Li

Recently, video-based large language models (video-based LLMs) have achieved impressive performance across various video comprehension tasks. However, this rapid advancement raises significant privacy and security concerns, particularly regarding the unauthorized use of personal video data in automated annotation by video-based LLMs. These unauthorized annot

Johan Marguet, Raluca Eftimie, Alexei Lozinski

Transport-dominated partial differential equation models have been used extensively over the past two decades to describe various collective migration phenomena in cell biology and ecology. To understand the behaviour of these models (and the biological systems they describe) different analytical and numerical approaches have been used. While the analytical

Bargava Subramanian, Naveen Kumarasami, Praveen Shastry, Kalyan Sivasailam

Background: Intracranial bleeding (IB) is a life-threatening condition caused by traumatic brain injuries, including epidural, subdural, subarachnoid, and intraparenchymal hemorrhages. Rapid and accurate detection is crucial to prevent severe complications. Traditional imaging can be slow and prone to variability, especially in high-pressure scenarios. Artif

Yu-Bo Hou, Rui-Zhe You, Di-Jia Zhang, Pengbo Li

Quantum transduction is a key technology for connecting different quantum technologies across varied frequencies. However, it remains a major challenge to overcome the high threshold for achieving positive capacity of traditional quantum transduction channels. Recently, an entanglement-assisted transducer was proposed based on a cavity-optic system [Opt. Qua

Yiyu Zhang, Xiaoyu Yu, Boyuan Zheng, Ye Xu

Adherent cells have long been known to display two modes during migration: a faster mode that is persistent in direction and a slower one where they turn. Compared to the persistent mode, the turns are less studied. Here we develop a simple yet effective protocol to isolate the turns quantitatively. With the protocol, we study different adherent cells in dif

Isaac M. Mutie, Santiago del Palacio, Robert J. Beswick, David Williams-Baldwin

The origin of radio emission in radio-quiet (RQ) AGN remains a long-standing mystery. We present a detailed study of the cm to sub-mm emission from the nucleus of the nearby prototypical RQ Seyfert 2 galaxy, NGC 1068. We analyse observations between 4.5-706 GHz using $e$-MERLIN, VLA and ALMA. We restricted all data used for imaging to a matching $uv-$range o

Sunayana Sitaram, Adrian de Wynter, Isobel McCrum, Qilong Gu

Misgendering is the act of referring to someone by a gender that does not match their chosen identity. It marginalizes and undermines a person's sense of self, causing significant harm. English-based approaches have clear-cut approaches to avoiding misgendering, such as the use of the pronoun ``they''. However, other languages pose unique challenges due to b

Jianyang Zhang, Qianli Luo, Guowu Yang, Wenjing Yang

Language Bottleneck Models (LBMs) are proposed to achieve interpretable image recognition by classifying images based on textual concept bottlenecks. However, current LBMs simply list all concepts together as the bottleneck layer, leading to the spurious cue inference problem and cannot generalized to unseen classes. To address these limitations, we propose

Qichen Sun, Yuxing Lu, Kun Xia, Li Chen

Rapid and efficient assessment of the future impact of research articles is a significant concern for both authors and reviewers. The most common standard for measuring the impact of academic papers is the number of citations. In recent years, numerous efforts have been undertaken to predict citation counts within various citation windows. However, most of t

Chen Yang, Shubin Yu, Chun-Lei Tang

We are concerned with $L^2$-constraint minimizers for the Kirchhoff functional $$ E_b(u)=\int_{\Omega}|\nabla u|^2\mathrm{d}x+\frac{b}{2}\left(\int_\Omega|\nabla u|^2\mathrm{d}x\right)^2+\int_\Omega V(x)u^2\mathrm{d}x-\frac{\beta}{2}\int_{\Omega}|u|^4\mathrm{d}x, $$ where $b>0$, $\beta>0$ and $V(x)$ is a trapping potential in a bounded domain $\Omega$ of $\m

Wenqing Lin, Xin Chen, Haoxuan Xie, Sibo Wang

A $k$-clique is a dense graph, consisting of $k$ fully-connected nodes, that finds numerous applications, such as community detection and network analysis. In this paper, we study a new problem, that finds a maximum set of disjoint $k$-cliques in a given large real-world graph with a user-defined fixed number $k$, which can contribute to a good performance o

Jun Sashihara, Teruaki Hayashi

In recent years, the magnitude of consumer-to-consumer (C2C) markets have grown significantly, highlighting the increasing significance of trust between buyers and sellers. However, the specific aspects of product information that facilitate effective communication and trust building in C2C markets remain poorly understood. This study examines the concept of

Alexander Zhuravlev, Juan D. Baena

Different types of network parameters have been used in electronics since long ago. The most typical network parameters, but not the only ones, are $S$, $T$, $ABCD$, $Z$, $Y$ , and $h$ that relate input and output signals in different ways. There exist practical formulas for conversion between them. Due to the development of powerful software tools that can

Yuhan Wang, Suzhi Bi, Ying-Jun Angela Zhang, Xiaojun Yuan

The distortion-perception (DP) tradeoff reveals a fundamental conflict between distortion metrics (e.g., MSE and PSNR) and perceptual quality. Recent research has increasingly concentrated on evaluating denoising algorithms within the DP framework. However, existing algorithms either prioritize perceptual quality by sacrificing acceptable distortion, or focu

Nesrine Cherif, Qurrat-Ul-Ain Nadeem

Unmanned Aerial Vehicles (UAVs) are increasingly used in a plethora of applications such as shipping, surveillance, and search-and-rescue. For UAVs to operate safely, reliable cellular connectivity is essential. Utilizing the terrestrial networks for aerial connectivity has been proposed, but the 3D radiation pattern of base station antennas significantly af

Rongchao Ma

Symmetry packaging is the phenomenon whereby, upon particle creation, all the internal quantum numbers (IQNs) become locked into a single irreducible representation (irrep) block of the gauge group, as required by locality and gauge invariance. The resulting packaged quantum states exhibit characteristic symmetry constraints and entanglement patterns. We dev

Xinghao Wang, Tao Gong, Qi Chu, Bin Liu

Malicious image manipulation poses societal risks, increasing the importance of effective image manipulation detection methods. Recent approaches in image manipulation detection have largely been driven by fully supervised approaches, which require labor-intensive pixel-level annotations. Thus, it is essential to explore weakly supervised image manipulation

Badri Ramanjaneya Reddy, Soumya P. Dash, George C. Alexandropoulos

This paper analyzes the performance of a single-input multiple-output (SIMO) wireless communication system employing one- and two-sided amplitude shift keying (ASK) modulation schemes for data transmission and operating under correlated Rician fading channels. The receiver deploys an optimal noncoherent maximum likelihood detector, which exploits statistical

Man-Chun Lee

In this work, we prove uniqueness for complete non-compact Ricci flow with scaling invariant curvature bound. This generalizes the earlier work of Chen-Zhu, Kotschwar and covers most of the example of Ricci flows with unbounded curvature. In dimension three, we use it to show that complete Ricci flow starting from uniformly non-collapsed, non-negatively curv

Chenwei Zhang, Khanh Dao Duc

Enhancing cryogenic electron microscopy (cryo-EM) 3D density maps at intermediate resolution (4-8 {\AA}) is crucial in protein structure determination. Recent advances in deep learning have led to the development of automated approaches for enhancing experimental cryo-EM density maps. Yet, these methods are not optimized for intermediate-resolution maps and

Siyin Wang, Wenyi Yu, Xianzhao Chen, Xiaohai Tian

This paper explores a novel perspective to speech quality assessment by leveraging natural language descriptions, offering richer, more nuanced insights than traditional numerical scoring methods. Natural language feedback provides instructive recommendations and detailed evaluations, yet existing datasets lack the comprehensive annotations needed for this a

Ivan Sviridov, Amina Miftakhova, Artemiy Tereshchenko, Galina Zubkova

Though Large Vision-Language Models (LVLMs) are being actively explored in medicine, their ability to conduct complex real-world telemedicine consultations combining accurate diagnosis with professional dialogue remains underexplored. This paper presents 3MDBench (Medical Multimodal Multi-agent Dialogue Benchmark), an open-source framework for simulating and

Kaifan Sun, Bingchen Yang, Peter Wonka, Jun Xiao

We present a hierarchical triplet-based indoor relationship learning method, coined HierRelTriple, with a focus on spatial relationship learning. Existing approaches often depend on manually defined spatial rules or simplified pairwise representations, which fail to capture complex, multi-object relationships found in real scenarios and lead to overcrowded o

Cuneyd Ozturk, Cagri Goken

A bistatic milimeter-wave (mmWave) ISAC system utilizing OFDM signaling is considered. For a single-target scnenario, closed-form expressions for the Cramer-Rao bounds (CRBs) of range and velocity estimation are derived for a given pilot pattern. The analysis shows that when the target's range and velocity remain within the maximum unambiguous limits, alloca

Yuhui Wu, Liyi Chen, Ruibin Li, Shihao Wang

Instruction-based video editing allows effective and interactive editing of videos using only instructions without extra inputs such as masks or attributes. However, collecting high-quality training triplets (source video, edited video, instruction) is a challenging task. Existing datasets mostly consist of low-resolution, short duration, and limited amount

Zhenyu Liang, Hao Li, Naiwei Yu, Kebin Sun

Evolutionary multiobjective optimization (EMO) has made significant strides over the past two decades. However, as problem scales and complexities increase, traditional EMO algorithms face substantial performance limitations due to insufficient parallelism and scalability. While most work has focused on algorithm design to address these challenges, little at

Ahmed Shaker Alalaq

This research examines the "Government AI Readines Index" (GARI) issued by Oxford, analyzing data on governmental preparedness for adopting artificial intelligence acros different countrie. It highlights the evaluation criteria used to assess readiness, including technological infrastructure, human resources, supportive policies, and the level of innovation.

Hongye Cao, Fan Feng, Jing Huo, Shangdong Yang

Model-based offline Reinforcement Learning (RL) constructs environment models from offline datasets to perform conservative policy optimization. Existing approaches focus on learning state transitions through ensemble models, rollouting conservative estimation to mitigate extrapolation errors. However, the static data makes it challenging to develop a robust

David Pechersky

We extend recent work of Gurel-Gurevich--Jerison--Nachmias (2020) and Bou-Rabee--Gwynne (2024) by showing that as the mesh of our lattice tends to $0$, we have a polynomial rate of convergence for the Dirichlet problem on orthodiagonal maps with H\"older boundary data to its continuous counterpart. The key idea is that the convolution of a discrete harmonic

Elisabetta Carlini, Athena Picarelli, Francisco J. Silva

We study the numerical approximation of time-dependent, possibly degenerate, second-order Hamilton-Jacobi-Bellman equations in bounded domains with nonhomogeneous Dirichlet boundary conditions. It is well known that convergence towards the exact solution of the equation, considered here in the viscosity sense, holds if the scheme is monotone, consistent, and

Kwonyoung Kim, Jungin Park, Jin Kim, Hyeongjun Kwon

Parameter-efficient tuning (PET) aims to transfer pre-trained foundation models to downstream tasks by learning a small number of parameters. Compared to traditional fine-tuning, which updates the entire model, PET significantly reduces storage and transfer costs for each task regardless of exponentially increasing pre-trained model capacity. However, most P

Chenglong Wang, Pujia Zheng, Jiaping Gui, Cunqing Hua

Network Intrusion Detection Systems (NIDS) are vital for ensuring enterprise security. Recently, Graph-based NIDS (GIDS) have attracted considerable attention because of their capability to effectively capture the complex relationships within the graph structures of data communications. Despite their promise, the reproducibility and replicability of these GI

Changyu Lee, Kiyong Park, Jinwhan Kim

This paper presents a new control barrier function (CBF) designed to improve the efficiency of collision avoidance for nonholonomic vehicles. Traditional CBFs typically rely on the shortest Euclidean distance to obstacles, overlooking the limited heading change ability of nonholonomic vehicles. This often leads to abrupt maneuvers and excessive speed reducti

Sejin Lee, Jian Kim, Haon Park, Ashkan Yousefpour

Large Language Models (LLMs) are increasingly deployed as computer-use agents, autonomously performing tasks within real desktop or web environments. While this evolution greatly expands practical use cases for humans, it also creates serious security exposures. We present SUDO (Screen-based Universal Detox2Tox Offense), a novel attack framework that systema

William Gilpin

Single-cell sequencing technology maps cells to a high-dimensional space encoding their internal activity. Recently-proposed virtual cell models extend this concept, enriching cells' representations based on patterns learned from pretraining on vast cell atlases. This review explores how advances in understanding the structure of natural language embeddings

Boan Zhang, Hang Dong, Jiongge Zhang, Long Tian

Traditional range-instantaneous Doppler (RID) methods for rigid-body target imaging often suffer from low resolution due to the limitations of time-frequency analysis (TFA). To address this challenge, our primary focus is on obtaining high resolution time-frequency representations (TFRs) from their low resolution counterparts. Recognizing that the curve feat

Zhipeng Yang, Yuanyang Yu

In this paper, we consider the following critical fractional Kirchhoff equation \begin{equation*} \Big(a+b{\int_{\mathbb{R}^{N}}}|(-\Delta)^{\frac{s}{2}}u|^2dx\Big)(-\Delta)^su=|u|^{2^*_s-2}u,\quad \text{in}\ \mathbb{R}^{N}, \end{equation*} where $a,b>0$, $\frac{N}{4}<s<1$, $2^*_s=\frac{2N}{N-2s}$ and $(-\Delta )^s$ is the fractional Laplacian. We prove the

Taku Nishino, Yoshiyuki Onishi, Takayuki Ishizaki

This paper shows that a necessary and sufficient condition for the small-signal stability of an inverter-integrated power system can be expressed in terms of semidefinite matrix inequalities determined only by the synchronous reactance of the components, the susceptance matrix of the transmission network, and the stationary values of the power flow distribut

Jing Wang, Chao Li, Taolei Wang, Jinyang Guo

The growing scale of data requires efficient memory subsystems with large memory capacity and high memory performance. Disaggregated architecture has become a promising solution for today's cloud and edge computing for its scalability and elasticity. As a critical part of disaggregation, disaggregated memory faces many design challenges in many dimensions, i

Aoran Liu, Weidong Mei, Peilan Wang, Dong Wang

Terahertz (THz) communication systems suffer severe blockage issues, which may significantly degrade the communication coverage and quality. Bending beams, capable of adjusting their propagation direction to bypass obstacles, have recently emerged as a promising solution to resolve this issue by engineering the propagation trajectory of the beam. However, tr

Ao Fu, Ziqi Ni, Yi Zhou

The generation of audio-driven talking head videos is a key challenge in computer vision and graphics, with applications in virtual avatars and digital media. Traditional approaches often struggle with capturing the complex interaction between audio and facial dynamics, leading to lip synchronization and visual quality issues. In this paper, we propose a nov

Ryotaro Koshoji

Mathematical crystal chemistry views crystal structures as the optimal solutions of mathematical optimization problem formalizing inorganic structural chemistry. This paper introduces the minimum and maximum atomic radii depending on the types of geometrical constraints, extending the concept of effective atomic sizes. These radii define permissible interato

Haoqin Tu, Weitao Feng, Hardy Chen, Hui Liu

Process-supervised reward models serve as a fine-grained function that provides detailed step-wise feedback to model responses, facilitating effective selection of reasoning trajectories for complex tasks. Despite its advantages, evaluation on PRMs remains less explored, especially in the multimodal domain. To address this gap, this paper first benchmarks cu

Yanqing Yang, Nan Zhang, Jinfeng Ge, Yan Xu

This paper identifies the impact of China-U.S. science and technology (S&T) friction on knowledge flows in different fields, using data on invention patent applications from China, the U.S., Europe, and the World Patent Office (WPO) along with machine-learning-based econometric methods. The empirical results find that the negative impacts of China-U.S. S&T f

Abdullah Guvendi, Omar Mustafa, Abdulkerim Karabulut

We analyze the behavior of spin-1 vector bosons in helical spacetime, focusing on photonic modes in helical graphene structures. We model the helical graphene surface as a smooth, continuous, and distortion-free manifold, effectively adopting the continuum approximation. By solving the fully covariant vector boson equation, we derive exact solutions that des

Kenan Tian, Yuanji Sheng, Rui Li, Lei Wang

Light bosons, beyond the standard model and as prominent candidates for dark matter, can mediate velocity and spin dependent exotic interaction between electron spins and nucleons. At short ranges, it remains an open challenge to test this exotic interaction with high precision. Here, we present a method based on diamagnetic-levitated force sensor to detect

Olexandr Polishchuk, Dmytro Polishchuk

The main types of simultaneous targeted group attacks on complex network systems and processes of intersystem interactions are discussed in the article. On the basis of structural model of multilayer network system (MLNS) and its aggregate-network, the most important components from a structural point of view, namely the cores of various types, whose damage

Ziran Zhang, Xiaohui Li, Yihao Liu, Yujin Wang

Video frame interpolation (VFI) in scenarios with large motion remains challenging due to motion ambiguity between frames. While event cameras can capture high temporal resolution motion information, existing event-based VFI methods struggle with limited training data and complex motion patterns. In this paper, we introduce Event-Guided Video Diffusion Model

Fanxin Wang, Haolong Jiang, Chuyuan Tao, Wenbin Wan

Optimizing trajectory costs for nonlinear control systems remains a significant challenge. Model Predictive Control (MPC), particularly sampling-based approaches such as the Model Predictive Path Integral (MPPI) method, has recently demonstrated considerable success by leveraging parallel computing to efficiently evaluate numerous trajectories. However, MPPI