October 2024 arXiv papers — page 100

Stein Andreas Bethuelsen, Matthias Birkner, Andrej Depperschmidt, Timo Schlüter

In this work we extend the quenched local limit theorem obtained by the authors in [BBDS23]. More precisely, we consider a directed random walk on the backbone of the supercritical oriented percolation cluster in dimensions $d+1$ with $d\geq 1$ being the spatial dimension. In [BBDS23] an annealed local central limit theorem was proven for all $d\geq 1$ and a

Stanislaw Jaworski, Wojciech Zielinski

The problem is in the estimation of the fraction of population with a sensitive characteristic. We consider the Item Count Technique an indirect method of questioning designed to protect respondents' privacy. The exact confidence interval for the sensitive fraction is constructed. The length of the proposed CI depends on both the given parameter of the model

Deke Li, Qingxuan Wang

We focus on the ground state of the cubic-quintic nonlinear Schr\"{o}dinger energy functional \begin{gather*} \begin{aligned} {E}(\varphi)=\frac{1}{2}\int_{\mathbb{R}^d}\left(|\nabla \varphi|^2+V(x)|\varphi|^2\right)\,dx \pm\frac{1}{4}\int_{\mathbb{R}^d}|\varphi|^4\,dx +\frac{1}{6}\int_{\mathbb{R}^d}|\varphi|^6\,dx, (d=1,2,3) \end{aligned} \end{gather*} unde

Shion Yamashika, Pasquale Calabrese, Filiberto Ares

We study the non-equilibrium dynamics of bosons in a two-dimensional optical lattice after a sudden quench from the superfluid phase to the free-boson regime. The initial superfluid state is described approximately using both the Bogoliubov theory and the Gaussian variational principle. The subsequent time evolution remains Gaussian, and we compare the resul

Christian Cella, Marco Faroni, Andrea Zanchettin, Paolo Rocco

The collaboration between humans and robots re-quires a paradigm shift not only in robot perception, reasoning, and action, but also in the design of the robotic cell. This paper proposes an optimization framework for designing collaborative robotics cells using a digital twin during the pre-deployment phase. This approach mitigates the limitations of experi

Slobodan Zdravković, Aleksandr N. Bugay, Slobodan Zeković, Dragana Ranković

In the present work, we study the nonlinear dynamics of a microtubule, an important part of the cytoskeleton. We use a two-component model of the relevant system. A crucial nonlinear differential equation is solved with semi-discrete approximation, yielding some localised modulated solitary waves called the breathers. A detailed estimation of the existing pa

Giuseppe Mignemi, Yunxiao Chen, Irini Moustaki

Peer grading is an educational system in which students assess each other's work. It is commonly applied under Massive Open Online Course (MOOC) and offline classroom settings. With this system, instructors receive a reduced grading workload, and students enhance their understanding of course materials by grading others' work. Peer grading data have a comple

Vicente J. Bolos, Rafael Benitez, Vicente Coll-Serrano

We construct a new family of chance constrained directional models in stochastic data envelopment analysis, generalizing the deterministic directional models and the chance constrained radial models. We prove that chance constrained directional models define the same concept of stochastic efficiency as the one given by chance constrained radial models and, a

L. V. Thinh, H. T. Tuan

This paper is devoted to the study of the asymptotic behavior of solutions to multi-order fractional cooperative systems. First, we demonstrate the boundedness of solutions to fractional-order systems under certain conditions imposed on the vector field. We then prove the global attractivity and the convergence rate of solutions to such systems (in the case

Kati Asikainen, Matti Alatalo, Marko Huttula, S. Assa Aravindh

Two-dimensional (2D) heterostructures reveal novel physicochemical phenomena at different length scales, that are highly desirable for technological applications. We present a comprehensive density functional theory study of van der Waals (vdW) heterostructures constructed by stacking 2D TiO2 and 2D MoSSe monolayers to form TiO2-MoSSe heterojunction. The het

Rémi Abgrall, Miaosen Jiao, Yongle Liu, Kailiang Wu

We propose a bound-preserving (BP) Point-Average-Moment PolynomiAl-interpreted (PAMPA) scheme by blending third-order and first-order constructions. The originality of the present construction is that it does not need any explicit reconstruction within each element, and therefore the construction is very flexible. The scheme employs a classical blending appr

Weizhe Liu, Sylvain Veilleux, Swetha Sankar, David S. N. Rupke

Quasar feedback may play a key role in the evolution of massive galaxies. The dust-reddened quasar, F2M110648.35$+$480712 at $z = 0.4352$ is one of the few cases at its redshift that exhibits powerful quasar feedback through bipolar outflows. Our new observation with the integral field unit mode of Near-infrared Spectrograph onboard JWST opens a new window t

Franziska Barkhausen, Laura Ares Santos, Stefan Schumacher, Jan Sperling

Common notions of entanglement are based on well-separated subsystems. However, obtaining such independent degrees of freedom is not always possible because of physical constraints. In this work, we explore the notion of entanglement in the context of dependent degrees of freedom. As a physically relevant application, we specifically study quantum correlatio

Alfred Malengo Kondoro

This paper proposes the creation of a Swahili Question Answering (QA) benchmark dataset, aimed at addressing the underrepresentation of Swahili in natural language processing (NLP). Drawing from established benchmarks like SQuAD, GLUE, KenSwQuAD, and KLUE, the dataset will focus on providing high-quality, annotated question-answer pairs that capture the ling

Y. Ashlea Alava, K. Kumar, C. Harsas, P. Mehta

The study of phonon coupling in doped semiconductors via electrical transport measurements is challenging due to unwanted temperature-induced effects such as dopant ionisation and parallel conduction. Here, we study phonon scattering in 2D electrons and holes in the $1.6-92.5$K range without the use of extrinsic doping, where both acoustic and longitudinal o

Gajraj Kuldeep, Qi Zhang

In recent years, multiple sensor-based devices and systems have been deployed in smart agriculture, industrial automation, E-Health, etc. The diversity of sensor data types and the amount of data pose critical challenges for data transmission and storage. The conventional data compression methods are tuned for a data type, e.g., OGG for audio. Due to such li

Claudia Fevola, Guilherme L. Pimentel, Anna-Laura Sattelberger, Tom Westerdijk

Cosmological correlators encode statistical properties of the initial conditions of our universe. Mathematically, they can often be written as Mellin integrals of a certain rational function associated to graphs, namely the flat space wavefunction. The singularities of these cosmological integrals are parameterized by binary hyperplane arrangements. Using di

Zigui Zhang, Zibo Miao, Xiu-Hao Deng

Efficient and systematic numerical methods for robust control design are crucial in quantum systems due to inevitable uncertainties or disturbances. We propose a novel approach that models uncertainties as random variables and quantifies robustness using the expectation of infidelity by reformulating it as a weighted tensor product quadrature. We employ the

Yugandhar Reddy Gogireddy, Jithendra Reddy Gogireddy

The difficulties of underwater image degradation due to light scattering, absorption, and fog-like particles which lead to low resolution and poor visibility are discussed in this study report. We suggest a sophisticated hybrid strategy that combines Multi-Scale Retinex (MSR) defogging methods with Super-Resolution Convolutional Neural Networks (SRCNN) to ad

Benedetta Casavecchia, Umberto Maio, Céline Péroux, Benedetta Ciardi

The latest ALMA and JWST observations provide new information on the birth and evolution of galaxies in the early Universe, at the epoch of reionization. Of particular importance are measurements at redshift $ z > 5$ of their cold-gas budget, which is known to be the main fuel for star formation. A powerful tool for probing the physics characterising galaxie

Bin Lin, Yanzhen Yu, Jianhao Ye, Ruitao Lv

Existing audio-driven facial animation methods face critical challenges, including expression leakage, ineffective subtle expression transfer, and imprecise audio-driven synchronization. We discovered that these issues stem from limitations in motion representation and the lack of fine-grained control over facial expressions. To address these problems, we pr

Asma Yamani, Nehal Al-Otaiby, Haifa Al-Shemmeri, Imane Boudellioua

Efficient identification of the root causes of drill bit failure is crucial due to potential impacts such as operational losses, safety threats, and delays. Early recognition of these failures enables proactive maintenance, reducing risks and financial losses associated with unforeseen breakdowns and prolonged downtime. Thus, our study investigates various c

Tonglong Wei, Yan Lin, Youfang Lin, Shengnan Guo

Spatiotemporal trajectory data is crucial for various applications. However, issues such as device malfunctions and network instability often cause sparse trajectories, leading to lost detailed movement information. Recovering the missing points in sparse trajectories to restore the detailed information is thus essential. Despite recent progress, several cha

Gökmen Polat, Eric Jeckelmann

We investigate the Emery model on several ladder-like lattices including two legs of copper d-orbitals and various numbers of oxygen p-orbitals. Pair binding energy, pair spatial structure, density distribution, and pairing correlation functions are calculated using the density matrix renormalization group (DMRG). We show that a Luther-Emery phase with enhan

Yuhao Wan, Peng-Tao Jiang, Qibin Hou, Hao Zhang

We present ControlSR, a new method that can tame Diffusion Models for consistent real-world image super-resolution (Real-ISR). Previous Real-ISR models mostly focus on how to activate more generative priors of text-to-image diffusion models to make the output high-resolution (HR) images look better. However, since these methods rely too much on the generativ

Drilon Zenelaj, Peter Samuelsson, Patrick P. Potts

Semiconductor double quantum dots (DQD) coupled to superconducting microwave resonators offer a promising platform for the detection of single microwave photons. In previous works, the photodetection was studied for a monochromatic source of microwave photons. Here, we theoretically analyze the photodetection of single microwave pulses. The photodetection in

Kiminori Hattori, Kenyu Chikamori, Hayato Iizuka, Ata Yamaguchi

The Rice-Mele model consists of a one-dimensional lattice with two sublattice sites in each unit cell subjected to a staggered sublattice potential. The onsite potential constitutes a mass term that breaks chiral symmetry. In this paper, we show that a topological phase transition is induced in this model by disordering intracell and intercell hopping energi

Ching Ming Samuel Lau, Weiqi Wang, Haochen Shi, Baixuan Xu

Knowledge Editing (KE) aims to correct and update factual information in Large Language Models (LLMs) to ensure accuracy and relevance without computationally expensive fine-tuning. Though it has been proven effective in several domains, limited work has focused on its application within the e-commerce sector. However, there are naturally occurring scenarios

A. Astillero, J. J. Ruiz-Lorenzo

We study the critical dynamics of the three-dimensional Heisenberg model with random cubic anisotropy in the out-of-equilibrium and equilibrium regimes. Analytical approaches based on field theory predict that the universality class of this model is that of the three-dimensional site-diluted Ising model. We have been able to estimate the dynamic critical exp

Vicente J. Bolos, Rafael Benitez

In this work we present the wavScalogram R package, which contains methods based on wavelet scalograms for time series analysis. These methods are related to two main wavelet tools: the windowed scalogram difference and the scale index. The windowed scalogram difference compares two time series, identifying if their scalograms follow similar patterns at diff

Jie Zhang, Dongrui Liu, Chen Qian, Linfeng Zhang

Protecting the intellectual property of open-source Large Language Models (LLMs) is very important, because training LLMs costs extensive computational resources and data. Therefore, model owners and third parties need to identify whether a suspect model is a subsequent development of the victim model. To this end, we propose a training-free REEF to identify

Neeldhara Misra, Aditi Sethia

We consider the complexity of finding envy-free allocations for the class of graphical valuations. Graphical valuations were introduced by Christodoulou et. al.(2023) as a structured class of valuations that admit allocations that are envy-free up to any item (EFX). These are valuations where every item is valued by two agents, lending a (simple) graph struc

Snigdha Sharma, Dhanoj Gupta

Elucidating the significance of low-energy electrons in the rupture of DNA/RNA and the process involved in it is crucial in the field of radiation therapy. Capturing of the incident electron in one of the empty molecular orbitals and the formation of a temporary negative ion (TNI) is considered to be a stepping stone towards the lesion of DNA/RNA. This TNI f

Uttam Suman, Mariya Mamajiwala, Mukul Saxena, Ankit Tyagi

Our proposal is on a new stochastic optimizer for non-convex and possibly non-smooth objective functions typically defined over large dimensional design spaces. Towards this, we have tried to bridge noise-assisted global search and faster local convergence, the latter being the characteristic feature of a Newton-like search. Our specific scheme -- acronymed

Christopher Holder, Anthony Bagnall, Jason Lines

There is a long history of research into time series clustering using distance-based partitional clustering. Many of the most popular algorithms adapt k-means (also known as Lloyd's algorithm) to exploit time dependencies in the data by specifying a time series distance function. However, these algorithms are often presented with k-means configured in variou

Chen Zhang, Meizhi Zhong, Qimeng Wang, Xuantao Lu

Long-context efficiency has recently become a trending topic in serving large language models (LLMs). And mixture of depths (MoD) is proposed as a perfect fit to bring down both latency and memory. In this paper, however, we discover that MoD can barely transform existing LLMs without costly training over an extensive number of tokens. To enable the transfor

Daniel J. F. Fox, Vladimir G. Tkachev

Hsiang algebras are a class of nonassociative algebra defined in terms of a relation quartic in elements of the algebra. This class arises naturally in relation to the construction of real algebraic minimal cones. Additionally, Hsiang algebras were crucial in the construction of singular (trulsy viscosity) solutions of nonlinear uniformly elliptic partial di

Costanza Aricò, Rainer Helmig, Ivan Yotov

We develop $H$(div)-conforming mixed finite element methods for the unsteady Stokes equations modeling single-phase incompressible fluid flow. A projection method in the framework of the incremental pressure correction methodology is applied, where a predictor and a corrector problems are sequentially solved, accounting for the viscous effects and incompress

Oliverio Theophilus Nathanael, Jonathan Samuel Lumentut, Nicholas Hans Muliawan, Edbert Valencio Angky

In recent years, personalized diffusion-based text-to-image generative tasks have been a hot topic in computer vision studies. A robust diffusion model is determined by its ability to perform near-perfect reconstruction of certain product outcomes given few related input samples. Unfortunately, the current prominent diffusion-based finetuning technique falls

Benedict Flade, Simon Kohaut, Julian Eggert

Future advanced driver assistance systems and autonomous vehicles rely on accurate localization, which can be divided into three classes: a) viewpoint localization about local references (e.g., via vision-based localization), b) absolute localization about a global reference system (e.g., via satellite navigation), and c) hybrid localization, which presents

Francesco Gili, Geurt Jongbloed, Aad van der Vaart

We consider nonparametric estimation of the distribution function $F$ of squared sphere radii in the classical Wicksell problem. Under smoothness conditions on $F$ in a neighborhood of $x$, in \cite{21} it is shown that the Isotonic Inverse Estimator (IIE) is asymptotically efficient and attains rate of convergence $\sqrt{n / \log n}$. If $F$ is constant on

Ted Kwartler, Matthew Berman, Alan Aqrawi

This study explores the ability of Large Language Model (LLM) agents to detect and correct hallucinations in AI-generated content. A primary agent was tasked with creating a blog about a fictional Danish artist named Flipfloppidy, which was then reviewed by another agent for factual inaccuracies. Most LLMs hallucinated the existence of this artist. Across 4,

Xiaocun Zong, Binchao Zhang, Fan Yang, Shenheng Xu

This paper analyzes the working principle of four-switch cross-shaped reconfigurable intelligent surface (RIS) in detail and reveals the different types of RIS that can be designed based on this structure. Combined with the design examples using this structure in the currently published articles, this paper summarizes and organizes them, and also points out

Zhongjun Ni, Jelrik Hupkes, Petra Eriksson, Gustaf Leijonhufvud

This study showcases the digitalization of L\"ofstad Castle in Sweden to contribute to preserving its heritage values. The castle and its collections are deteriorating due to an inappropriate indoor climate. To address this, thirteen cloud-connected sensor boxes, equipped with 84 sensors, were installed throughout the main building, from the basement to the

Zihao Cheng, Li Zhou, Feng Jiang, Benyou Wang

The rapid development of large language models (LLMs), like ChatGPT, has resulted in the widespread presence of LLM-generated content on social media platforms, raising concerns about misinformation, data biases, and privacy violations, which can undermine trust in online discourse. While detecting LLM-generated content is crucial for mitigating these risks,

Yoshihito Kuno, Takahiro Orito, Ikuo Ichinose

Discovering quantum orders in mixed many-body systems is an ongoing issue. Very recently, the notion of an intrinsic mixed state topologically-ordered (IMTO) state was proposed. As a concrete example, we observe the emergence of IMTO by studying the toric code system under stochastic maximal decoherence by $ZX$-diagonal type projective measurement without mo

Zhibin Wang, Shipeng Li, Yuhang Zhou, Xue Li

User experience is a critical factor Large Language Model (LLM) serving systems must consider, where service level objectives (SLOs) considering the experience of individual requests and system level metrics (SLMs) considering the overall system performance are two key performance measures. However, we observe two notable issues in existing metrics: 1) manua

A. Provata, J. Hizanidis, K. Anesiadis, O. E. Omel'chenko

Networks of nonlocally coupled leaky Integrate-and-Fire neurons exhibit a variety of complex collective behaviors, such as partial synchronization, frequency or amplitude chimeras, solitary states and bump states. In particular, the bump states consist of one or many regions of asynchronous elements within a sea of subthreshold (quiescent) elements. The asyn

Xiang Hu, Hongyu Fu, Jinge Wang, Yifeng Wang

Scientific innovation is pivotal for humanity, and harnessing large language models (LLMs) to generate research ideas could transform discovery. However, existing LLMs often produce simplistic and repetitive suggestions due to their limited ability in acquiring external knowledge for innovation. To address this problem, we introduce an enhanced planning and

Daniel Riccio, Genoveffa Tortora, Mara Sangiovanni

In many application domains, the proliferation of sensors and devices is generating vast volumes of data, imposing significant pressure on existing data analysis and data mining techniques. Nevertheless, an increase in data volume does not inherently imply an increase in informational content, as a substantial portion may be redundant or represent noise. Thi

Josef Grus, Claire Hanen, Zdeněk Hanzálek

We tackle the problem of non-preemptive periodic scheduling with a harmonic set of periods. Problems of this kind arise within domains of periodic manufacturing and maintenance, and also during the design of industrial, automotive, and avionics communication protocols, where efficient scheduling of messages is crucial for the performance of a time-triggered

Xiaocun Zong, Fan Yang, Shenheng Xu, Maokun Li

In the new perspective of spatial quantization, this article systematically studies the advantages of reconfigurable reflectarray (RRA) designed with closely spaced elements in terms of sidelobe level (SLL), scanning accuracy and scan loss, including theoretical analysis and simulation verification. This article sequentially studies RRAs with element periods

Ziqi Yin, Mingxin Zhang, Daisuke Kawahara

Large Language Models (LLMs) offer powerful capabilities for natural language understanding, enabling more intelligent smart home assistants. However, existing systems often rely on cloud-based LLMs, raising concerns around user privacy and system dependency on external connectivity. In this work, we present Harmony, a privacy-preserving and robust smart hom

Shuo Tang, Xianghe Pang, Zexi Liu, Bohan Tang

Post-training is essential for enabling large language models (LLMs) to follow human instructions. However, its effectiveness depends on high-quality instruction data, which is challenging to obtain in the real world due to privacy concerns, data scarcity, and high annotation costs. To fill this gap, inspired by the recent success of using LLMs to simulate h

Rui Liu, Wenguan Wang, Yi Yang

Vision-language navigation (VLN) requires an agent to execute actions following human instructions. Existing VLN models are optimized through expert demonstrations by supervised behavioural cloning or incorporating manual reward engineering. While straightforward, these efforts overlook the accumulation of errors in the Markov decision process, and struggle

Anton Bredenbeck, Teaya Yang, Salua Hamaza, Mark W. Mueller

Aerial robots are a well-established solution for exploration, monitoring, and inspection, thanks to their superior maneuverability and agility. However, in many environments, they risk crashing and sustaining damage after collisions. Traditional methods focus on avoiding obstacles entirely, but these approaches can be limiting, particularly in cluttered spa

Olga Loginova, Oleksandr Bezrukov, Ravi Shekhar, Alexey Kravets

Evaluating Video Language Models (VLMs) is a challenging task. Due to its transparency, Multiple-Choice Question Answering (MCQA) is widely used to measure the performance of these models through accuracy. However, existing MCQA benchmarks fail to capture the full reasoning capabilities of VLMs due to selection bias, when models disproportionately favor cert

Liuquan Yao, Pei Yang, Zhichao Liu, Wenyan Li

With the development of information technology, requirements for data flow have become diverse. When multi-type data flow (MDF) is used, games, videos, calls, etc. are all requirements. There may be a constant switch between these requirements, and also multiple requirements at the same time. Therefore, the demands of users change over time, which makes trad

Jimin Dai, Yingzhen Zhang, Shuo Chen, Jian Yang

Diffusion models (DMs) have been successfully applied to real image editing. These models typically invert images into latent noise vectors used to reconstruct the original images (known as inversion), and then edit them during the inference process. However, recent popular DMs often rely on the assumption of local linearization, where the noise injected dur

Chetan Lodha, Ajay Kumar Rai

We investigate the mass spectra and decay properties of pions and all light tetraquarks using both semi-relativistic and non-relativistic frameworks. By applying a Cornell-like potential and a spin-dependent potential, we generate the mass spectra. The decay properties of tetraquarks are evaluated using the annihilation model and the spectator model. Potenti

Vlassis Fotis, Ioannis Romanelis, Georgios Mylonas, Athanasios Kalogeras

In this paper we study the problem of shape part retrieval in the point cloud domain. Shape retrieval methods in the literature rely on the presence of an existing query object, but what if the part we are looking for is not available? We present Part Retrieval Pipeline (PReP), a pipeline that creatively utilizes metric learning techniques along with a train

Nir Livne, Ady Vaknin, Oded Agam

Motile bacteria can migrate along chemical gradients in a process known as chemotaxis. When exposed to uniform environmental stress, Escherichia coli cells coordinate their chemotactic responses to form millimeter-sized condensates containing hundreds of thousands of motile cells. In this study, we combined experiments with mathematical modeling based on mod

Kaoru Mizuta, Tatsuhiko N. Ikeda, Keisuke Fujii

Product formula (PF), which approximates the time evolution under a many-body Hamiltonian by the product of local time evolution operators, is one of the central approaches for simulating quantum dynamics by quantum computers. It has been of great interest whether PFs have a bound of the error from the exact time evolution, which is expressed by commutators

Zia-ur-Rehman, Arif Mahmood, Wenxiong Kang

Self-supervised learning systems have gained significant attention in recent years by leveraging clustering-based pseudo-labels to provide supervision without the need for human annotations. However, the noise in these pseudo-labels caused by the clustering methods poses a challenge to the learning process leading to degraded performance. In this work, we pr

Hao Chen, Yu Yang, Yuanchen Bei, Zefan Wang

The cold start problem in recommender systems remains a critical challenge. Current solutions often train hybrid models on auxiliary data for both cold and warm users/items, potentially degrading the experience for the latter. This drawback limits their viability in practical scenarios where the satisfaction of existing warm users/items is paramount. Althoug

Manuel Brenner, Christoph Jürgen Hemmer, Zahra Monfared, Daniel Durstewitz

Dynamical systems (DS) theory is fundamental for many areas of science and engineering. It can provide deep insights into the behavior of systems evolving in time, as typically described by differential or recursive equations. A common approach to facilitate mathematical tractability and interpretability of DS models involves decomposing nonlinear DS into mu

Jonas Hahnfeld, Jakob Blomer, Thorsten Kollegger

High Energy Physics (HEP) experiments, for example at the Large Hadron Collider (LHC) at CERN, store data at exabyte scale in sets of files. They use a binary columnar data format by the ROOT framework, that also transparently compresses the data. In this format, cells are not necessarily atomic but they may contain nested collections of variable size. The f

Enqi Liu, Liyuan Pan, Yan Yang, Yiran Zhong

Fine-grained video action recognition can be conceptualized as a video-text matching problem. Previous approaches often rely on global video semantics to consolidate video embeddings, which can lead to misalignment in video-text pairs due to a lack of understanding of action semantics at an atomic granularity level. To tackle this challenge, we propose a mul

Runjia Li, Qiwei Di, Quanquan Gu

Score-based diffusion models have emerged as powerful techniques for generating samples from high-dimensional data distributions. These models involve a two-phase process: first, injecting noise to transform the data distribution into a known prior distribution, and second, sampling to recover the original data distribution from noise. Among the various samp

Bin Zhang, Junli Wang

ICD(International Classification of Diseases) coding involves assigning ICD codes to patients visit based on their medical notes. Considering ICD coding as a multi-label text classification task, researchers have developed sophisticated methods. Despite progress, these models often suffer from label imbalance and may develop spurious correlations with demogr

Gaurav Arora, Srujana Merugu, Shreya Jain, Vaibhav Saxena

Reasoning and linguistic skills form the cornerstone of human intelligence, facilitating problem-solving and decision-making. Recent advances in Large Language Models (LLMs) have led to impressive linguistic capabilities and emergent reasoning behaviors, fueling widespread adoption across application domains. However, LLMs still struggle with complex reasoni

Jesper Larsson Träff

The reduce-scatter collective operation in which $p$ processors in a network of processors collectively reduce $p$ input vectors into a result vector that is partitioned over the processors is important both in its own right and as building block for other collective operations. We present a surprisingly simple, but non-trivial algorithm for solving this pro

Hideki Okawa, Xian-Zhe Tao, Qing-Guo Zeng, Man-Hong Yung

Jet clustering or reconstruction is a crucial component at high energy colliders, a procedure to identify sprays of collimated particles originating from the fragmentation and hadronization of quarks and gluons. It is a complicated combinatorial optimization problem and requires intensive computing resources. In this study, we formulate jet reconstruction as

Ahmad Obeid, Said Boumaraf, Anabia Sohail, Taimur Hassan

Recent years witnessed remarkable progress in computational histopathology, largely fueled by deep learning. This brought the clinical adoption of deep learning-based tools within reach, promising significant benefits to healthcare, offering a valuable second opinion on diagnoses, streamlining complex tasks, and mitigating the risks of inconsistency and bias

Johannes Niederhauser, Chad E. Brown, Cezary Kaliszyk

Dependent type theory gives an expressive type system facilitating succinct formalizations of mathematical concepts. In practice, it is mainly used for interactive theorem proving with intensional type theories, with PVS being a notable exception. In this paper, we present native rules for automated reasoning in a dependently-typed version (DHOL) of classica

Zhen Tao, Zhiyu Li, Runyu Chen, Dinghao Xi

Large language models (LLMs) have transformed human writing by enhancing grammar correction, content expansion, and stylistic refinement. However, their widespread use raises concerns about authorship, originality, and ethics, even potentially threatening scholarly integrity. Existing detection methods, which mainly rely on single-feature analysis and binary

Mrinal Rawat, Hithesh Sankararaman, Victor Barres

Deriving value from a conversational AI system depends on the capacity of a user to translate the prior knowledge into a configuration. In most cases, discovering the set of relevant turn-level speaker intents is often one of the key steps. Purely unsupervised algorithms provide a natural way to tackle discovery problems but make it difficult to incorporate

Josef Grus, Zdeněk Hanzálek

The suboptimal physical design of the integrated circuits may not only increase the manufacturing costs due to the larger size of the chip but can also impact its performance by placing interconnected rectangular devices too far from each other. In the domain of Analog and Mixed-Signal Integrated Circuits (AMS ICs), placement automation is lacking behind its

Antonio A. Casilli, Paola Tubaro, Maxime Cornet, Clément Le Ludec

Labor plays a major, albeit largely unrecognized role in the development of artificial intelligence. Machine learning algorithms are predicated on data-intensive processes that rely on humans to execute repetitive and difficult-to-automate, but no less essential, tasks such as labeling images, sorting items in lists, recording voice samples, and transcribing

Julien Poisat

The purpose of this short note is to establish a connection between a one-dimensional random walk in a random sparse environment and the random pinning model. We show that the grand canonical partition function of the pinning model coincides with the mean number of returns to the origin for a random walk in a random sparse environment averaged on the randomn

Yanxiang Wang, Yiran Shen, Kenuo Xu, Guangrong Zhao

Passive visible light communication (VLC) modulates light propagation or reflection to transmit data without directly modulating the light source. Thus, passive VLC provides an alternative to conventional VLC, enabling communication where the light source cannot be directly controlled. There have been ongoing efforts to explore new methods and devices for mo

Gilles Bertrand

In this paper, we develop the notion of a Morse sequence, which provides an alternative approach to discrete Morse theory, and which is both simple and effective. A Morse sequence on a finite simplicial complex is a sequence composed solely of two elementary operations, that is, expansions (the inverse of a collapse), and fillings (the inverse of a perforati

Nicolas Rivoallan, Marc Mueller, Timothée Baudequin, Pascale Vigneron

Thick honeycomb-like electrospun scaffold with nanoparticles of hydroxyapatite (nHA) recently demonstrated its potential to promote proliferation and differentiation of a murine embryonic cell line (C3H10T1/2) to osteoblasts. In order to distinguish the respective effects of the structure and the composition on cell differentiation, beads-on-string fibers we

Josef Grus, Zdeněk Hanzálek

This paper presents a heuristic approach for solving the placement of Analog and Mixed-Signal Integrated Circuits. Placement is a crucial step in the physical design of integrated circuits. During this step, designers choose the position and variant of each circuit device. We focus on the specific class of analog placement, which requires so-called pockets,

Laurent-Stéphane Didier, Nadia Mrabet, Léa Glandus, Jean-Marc Robert

This paper presents software implementations of batch computations, dealing with multi-precision integer operations. In this work, we use the Single Instruction Multiple Data (SIMD) AVX512 instruction set of the x86-64 processors, in particular the vectorized fused multiplier-adder VPMADD52. We focus on batch multiplications, squarings, modular multiplicatio

Li Yuan, Yi Cai, Junsheng Huang

Joint Multimodal Entity-Relation Extraction (JMERE) is a challenging task that aims to extract entities and their relations from text-image pairs in social media posts. Existing methods for JMERE require large amounts of labeled data. However, gathering and annotating fine-grained multimodal data for JMERE poses significant challenges. Initially, we construc

Vinjamoori Vikas, Kuntal Deka, A. Rajesh

Code-domain non-orthogonal multiple access (CD-NOMA) systems offer key benefits such as high spectral efficiency, low latency, high reliability, and massive connectivity. NOMA's ability to handle overloading allows multiple devices to share a single resource element (RE) for data transmission. In CD-NOMA, different users are assigned distinct codewords, whic

Chayan Maitra, Rajat K. De

Visualizing high-dimensional datasets through a generalized embedding has been a challenge for a long time. Several methods have shown up for the same, but still, they have not been able to generate a generalized embedding, which not only can reveal the hidden patterns present in the data but also generate realistic high-dimensional samples from it. Motivate

Marie Puren

In 2015, the Annales journal, traditionally open to interdisciplinary approaches in history, referred to 'the current historiographical moment [as] call [ing] for an experimentation of approaches'. 1 Although this observation did not exclusively refer to the new possibilities offered by the technological advancements of the time -particularly in the field of

Martin Donati

In this paper, we control the growth of the support of particular solutions to the Euler two-dimensional equations, whose vorticity is concentrated near special vortex crystals. These vortex crystals belong to the classical family of regular polygons with a central vortex, where we choose a particular intensity for the central vortex to have strong stability

D. Choudhary, S. Nag

Total-Body PET (TB-PET) scanners represent a significant advancement in medical diagnostics, exemplified by the uEXPLORER, the world's first TB-PET system with an axial span of 194 cm, which exhibits exceptional sensitivity and spatial resolution. This study employs the Monte Carlo simulation toolkit Geant4 to evaluate various configurations and materials of

Sushmita Paul, Jinqiang Yu, Jip J. Dekker, Alexey Ignatiev

Despite the practical success of Artificial Intelligence (AI), current neural AI algorithms face two significant issues. First, the decisions made by neural architectures are often prone to bias and brittleness. Second, when a chain of reasoning is required, neural systems often perform poorly. Neuro-symbolic artificial intelligence is a promising approach t

Alexander Venner, Qier An, Chelsea X. Huang, Timothy D. Brandt

As exoplanet surveys reach ever-higher sensitivities and durations, planets analogous to the solar system giant planets are increasingly within reach. HD 28185 is a Sun-like star known to host a $m\sin i=6 M_J$ planet on an Earth-like orbit; more recently, a brown dwarf with a more distant orbit has been claimed. In this work we present a comprehensive reana

K. V. Nikolaev, V. Soltwisch, M. A. Botchev, A. Fernández Herrero

In this article, we derive a theoretical formalism that unifies the rigorous coupled wave analysis and the dynamical diffraction theory. Based on this formalism, we design a computational approach for the diffraction calculation for the nanoscale lamellar gratings with an arbitrary line profile shape. In this approach, the gratings line profile is approximat

Bahae-Eddine Madir, Francky Luddens, Corentin Lothodé, Ionut Danaila

We study numerical algorithms to solve a specific Partial Differential Equation (PDE), namely the Stefan problem, using Physics Informed Neural Networks (PINNs). This problem describes the heat propagation in a liquid-solid phase change system. It implies a heat equation and a discontinuity at the interface where the phase change occurs. In the context of PI

Pengguang Du, Cheng Zhang, Yindi Jing, Chao Fang

In this paper, we investigate the problem of jamming detection and channel estimation during multi-user uplink beam training under random pilot jamming attacks in beamspace massive multi-input-multi-output (MIMO) systems. For jamming detection, we distinguish the signals from the jammer and the user by projecting the observation signals onto the pilot space.

Zhenghao Pan, Haijin Zeng, Jiezhang Cao, Yongyong Chen

Color video snapshot compressive imaging (SCI) employs computational imaging techniques to capture multiple sequential video frames in a single Bayer-patterned measurement. With the increasing popularity of quad-Bayer pattern in mainstream smartphone cameras for capturing high-resolution videos, mobile photography has become more accessible to a wider audien

Michael Ben Ali, Omar El-Rifai, Imen Megdiche, André Peninou

Over recent years, Federated Learning (FL) has proven to be one of the most promising methods of distributed learning which preserves data privacy. As the method evolved and was confronted to various real-world scenarios, new challenges have emerged. One such challenge is the presence of highly heterogeneous (often referred as non-IID) data distributions amo

Emanuele Natale, Davide Ferre', Giordano Giambartolomei, Frédéric Giroire

Considerable research efforts have recently been made to show that a random neural network $N$ contains subnetworks capable of accurately approximating any given neural network that is sufficiently smaller than $N$, without any training. This line of research, known as the Strong Lottery Ticket Hypothesis (SLTH), was originally motivated by the weaker Lotter

Xingyu Tan, Xiaoyang Wang, Qing Liu, Xiwei Xu

Large Language Models (LLMs) have achieved impressive results in various tasks but struggle with hallucination problems and lack of relevant knowledge, especially in deep complex reasoning and knowledge-intensive tasks. Knowledge Graphs (KGs), which capture vast amounts of facts in a structured format, offer a reliable source of knowledge for reasoning. Howe