December 2024 arXiv papers — page 204

Pamely Zantou, Blessed Guda, Bereket Retta, Gladys Inabeza

Birth Apshyxia (BA) is a severe condition characterized by insufficient supply of oxygen to a newborn during the delivery. BA is one of the primary causes of neonatal death in the world. Although there has been a decline in neonatal deaths over the past two decades, the developing world, particularly sub-Saharan Africa, continues to experience the highest un

Christopher Fusco, Shin-Fang Ch'ng, Mosam Dabhi, Simon Lucey

We present a spatio-temporal perspective on category-agnostic 3D lifting of 2D keypoints over a temporal sequence. Our approach differs from existing state-of-the-art methods that are either: (i) object-agnostic, but can only operate on individual frames, or (ii) can model space-time dependencies, but are only designed to work with a single object category.

Hussein Hammoud, Yuning Zhang, Zihang Cheng, Seun Sangodoyin

The coordination of vehicles is a crucial element of autonomous driving, as it enhances the efficiency, convenience, and safety of road traffic. In order to fully exploit the capabilities of such coordination, communication with high data rate and low latency is required. It can be reasonably argued that millimeter-wave (mm-wave) vehicle-to-vehicle (V2V) sys

Shintaro Fukushima, Kenji Yamanishi

This study addresses the issue of graph generation with generative models. In particular, we are concerned with graph community augmentation problem, which refers to the problem of generating unseen or unfamiliar graphs with a new community out of the probability distribution estimated with a given graph dataset. The graph community augmentation means that t

Zhi Li, Ruixin Wang, Guoxin Wei

In this paper, we obtain a rigidity result of $2$-dimensional complete lagrangian self-shrinkers with constant squared norm $|\vec{H}|^{2}$ of the mean curvature vector in the Euclidean space $\mathbb{R}^{4}$. The same idea is also used to give a similar result of Lagrangian $\xi$-submanifolds in $\mathbb{R}^{4}$.

Zhifei Zhu

In this article, we prove a generalization of our previous result in [12]. In particular, we show that for an $n$-dimensional, simply connected Riemannian manifold with diameter $D$ and volume $V$. Suppose that $M$ admits a good cover consisting of $N$ elements. Then, the length of a shortest closed geodesic on $M$ is bounded by some function that only depen

Wooseok Jang, Youngjun Hong, Geonho Cha, Seungryong Kim

Manipulation of facial images to meet specific controls such as pose, expression, and lighting, also known as face rigging, is a complex task in computer vision. Existing methods are limited by their reliance on image datasets, which necessitates individual-specific fine-tuning and limits their ability to retain fine-grained identity and semantic details, re

Chunyang Cao, F. K. Liu, Xian Chen, Shuo Li

Quasiperiodic eruptions (QPEs) are a novel class of transients recently discovered in a few extragalactic nuclei. It has been suggested that a QPE can be produced by a main-sequence star undergoing repeated partial disruptions by the tidal field of a supermassive black hole (SMBH) immediately after getting captured on a tightly bound orbit through the Hills

M. Sharif, and Malick Sallah

In this study, we utilize the minimal geometric deformation technique of gravitational decoupling to extend the regular Bardeen black hole, leading to the derivation of new black hole solutions within the framework of Rastall theory. By decoupling the field equations associated with an extended matter source into two subsystems, we address the first subsyste

Sven Buder, Tobias Buck, Qian-Hui Chen, Kathryn Grasha

Radial metallicity gradients are fundamental to understanding galaxy formation and evolution. In our high-resolution simulation of a NIHAO-UHD Milky Way analogue, we analyze the linearity, scatter, spatial coherence, and age-related variations of metallicity gradients using young stars and gas. While a global linear model generally captures the gradient, it

Kento Uchida, Teppei Yamaguchi, Shinichi Shirakawa

Despite the state-of-the-art performance of the covariance matrix adaptation evolution strategy (CMA-ES), high-dimensional black-box optimization problems are challenging tasks. Such problems often involve a property called low effective dimensionality (LED), in which the objective function is formulated with redundant dimensions relative to the intrinsic ob

Bailey Sykes, Bernhard Müller

We perform five 3D magnetohydrodynamic (MHD) core-collapse supernova simulations for non-rotating progenitors between 9.5 $M_\odot$ and 24 $M_\odot$. Four of the five models produce explosions while one fails. The exploding models are extended to between 0.9 s and 1.6 s post-bounce to study a possible impact of magnetic fields on explosion and remnant proper

Trung-Hieu Hoang, Duc Minh Vo, Minh N. Do

Test-time adaptation (TTA) has emerged as a promising solution to tackle the continual domain shift in machine learning by allowing model parameters to change at test time, via self-supervised learning on unlabeled testing data. At the same time, it unfortunately opens the door to unforeseen vulnerabilities for degradation over time. Through a simple theoret

Matthew T. Miles, Ryan M. Shannon, Daniel J. Reardon, Matthew Bailes

Pulsar Timing Arrays search for nanohertz-frequency gravitational waves by regularly observing ensembles of millisecond pulsars over many years to look for correlated timing residuals. Recently the first evidence for a stochastic gravitational wave background has been presented by the major Arrays, with varying levels of significance ($\sim$2-4$\sigma$). In

Sami Jaghouar, Jack Min Ong, Manveer Basra, Fares Obeid

In this report, we introduce INTELLECT-1, the first 10 billion parameter language model collaboratively trained across the globe, demonstrating that large-scale model training is no longer confined to large corporations but can be achieved through a distributed, community-driven approach. INTELLECT-1 was trained on 1 trillion tokens using up to 14 concurrent

Jeongmin Han

In this paper, we study a certain type of noisy tug-of-war game which can be regarded as an interpretation of a certain type of boundary value problem for the normalized $p$-Laplace equation, where $1<p<2$. More precisely, we will investigate the boundary regularity of the value function to the game and its convergence to a viscosity solution of the model pr

Steven Dillmann, Juan Rafael Martínez-Galarza, Roberto Soria, Rosanne Di Stefano

We present a novel representation learning method for downstream tasks like anomaly detection, unsupervised classification, and similarity searches in high-energy data sets. This enabled the discovery of a new extragalactic fast X-ray transient (FXT) in Chandra archival data, XRT 200515, a needle-in-the-haystack event and the first Chandra FXT of its kind. R

Joseph McGovern

We apply the methods of \cite{Alexandrov:2023zjb} to compute generating series of D4D2D0 indices with a single unit of D4 charge for several compact Calabi-Yau threefolds, assuming modularity of these indices. Our examples include a $\mathbb{Z}_{7}$ quotient of R{\o}dland's pfaffian threefold, a $\mathbb{Z}_{5}$ quotient of Hosono-Takagi's double quintic sym

Matthew T. Miles, Ryan M. Shannon, Daniel J. Reardon, Matthew Bailes

Pulsar timing arrays are ensembles of regularly observed millisecond pulsars timed to high precision. Each pulsar in an array could be affected by a suite of noise processes, most of which are astrophysically motivated. Analysing them carefully can be used to understand these physical processes. However, the primary purpose of these experiments is to detect

Divya Sharma

This research paper delves into the financial behavior of urbanized households in India, specifically focusing on million-plus agglomerations. Using data from the 77th round of the All India Debt and Investment Survey, the study analyzes assets, borrowing patterns, and the usage of financial instruments like bank accounts, e-wallets, and life insurance. The

Minh Tran, Thang Pham, Winston Bounsavy, Tri Nguyen

Handling occlusion remains a significant challenge for video instance-level tasks like Multiple Object Tracking (MOT) and Video Instance Segmentation (VIS). In this paper, we propose a novel framework, Amodal-Aware Video Instance Segmentation (A2VIS), which incorporates amodal representations to achieve a reliable and comprehensive understanding of both visi

Chao Wu, Hao Hu, Ruohan Wang, Tingqing Zhou

The Chamblin-Reall gravity is a remarkable non-conformal platform for the fluid/gravity correspondence to achieve its maximum efficiency. When a probe scalar field that does not change the background metric is manually introduced into the action of the gravity side, an external scalar field will appear at the boundary, and the gradients of the external scala

Ruchao Fan, Bo Ren, Yuxuan Hu, Rui Zhao

Integrating speech into LLM (speech-LLM) has gaining increased attention recently. The mainstream solution is to connect a well-trained speech encoder and LLM with a neural adapter. However, the length mismatch between the speech and text sequences are not well handled, leading to imperfect modality matching between the speech and text. In this work, we prop

Dasheng Wei, Jie Xu, Yi Zhu

We study strong approximation for the intersection of two affine quadrics. As its application, we prove the fibration method for weak approximation over number fields of rank four with nonsplit fibers split by quadratic extensions.

Matthew Ding, Alexandro Garces, Jason Li, Honghao Lin

We consider the problem of finding a minimum cut of a weighted graph presented as a single-pass stream. While graph sparsification in streams has been intensively studied, the specific application of finding minimum cuts in streams is less well-studied. To this end, we show upper and lower bounds on minimum cut problems in insertion-only streams for a variet

Walaa I. Eshraim

Motivated by the Hamilton$-$Jacobi approach of fields with constraints, we analyse the classical structure of three different constrained field systems: (i) the scalar field coupled to two flavors of fermions through Yukawa couplings (ii) the scalar field coupled minimally to the vector potential (iii) the electromagnetic field coupled to a spinor. The equat

Guowei Wu, Weike Pan, Qiang Yang, Zhong Ming

Graph neural network (GNN) has emerged as a state-of-the-art solution for item recommendation. However, existing GNN-based recommendation methods rely on a centralized storage of fragmented user-item interaction sub-graphs and training on an aggregated global graph, which will lead to privacy concerns. As a response, some recent works develop GNN-based feder

Suhyun Shin, Seungwoo Yoon, Ryota Maeda, Seung-Hwan Baek

Hyperspectral 3D imaging captures both depth maps and hyperspectral images, enabling comprehensive geometric and material analysis. Recent methods achieve high spectral and depth accuracy; however, they require long acquisition times often over several minutes or rely on large, expensive systems, restricting their use to static scenes. We present Dense Dispe

Mikhail Drugov, Dmitry Ryvkin, Jun Zhang

We study tournaments where winning a rank-dependent prize requires passing a minimum performance standard. We show that, for any prize allocation, the optimal standard is always at a mode of performance that is weakly higher than the global mode and identify a necessary and sufficient condition for it to be at the global mode. When the prize scheme can be de

Jianguo Huang, Yuejin Xu

In this paper, for solving a class of linear parabolic equations in rectangular domains, we have proposed an efficient Parareal exponential integrator finite element method. The proposed method first uses the finite element approximation with continuous multilinear rectangular basis function for spatial discretization, and then takes the Runge-Kutta approach

Xingsong Ye, Yongkun Du, Yunbo Tao, Zhineng Chen

Scene text recognition (STR) suffers from challenges of either less realistic synthetic training data or the difficulty of collecting sufficient high-quality real-world data, limiting the effectiveness of trained models. Meanwhile, despite producing holistically appealing text images, diffusion-based visual text generation methods struggle to synthesize accu

Seongchan Kim, Woojeong Jin, Sangbeom Lim, Heeji Yoon

Referring video object segmentation (RVOS) requires tracking and segmenting an object throughout a video according to a given natural language expression, demanding both complex motion understanding and the alignment of visual representations with language descriptions. Given these challenges, the recently proposed Segment Anything Model 2 (SAM2) emerges as

Cashous Bortner, John Gilliana, Dev Patel, Zaia Tamras

Given experimental data, one of the main objectives of biological modeling is to construct a model which best represents the real world phenomena. In some cases, there could be multiple distinct models exhibiting the exact same dynamics, meaning from the modeling perspective it would be impossible to distinguish which model is ``correct.'' This is the study

Takashi Sato, Shinto Watanabe, Ryo Takahashi, Wakako Yukita

For full-body wireless power transfer (WPT), a liquid metal (LM)-based meandered textile coil has been proposed. Multiple rigid capacitors must be inserted in a long coil for efficiency; however, the conventional adhesive jointing suffers from the fragile connection between a rubber tube filled with LM and the capacitor due to the poor adhesion of the rubber

C. -Y. Liu, C. G. Feyisa, Muhammad S. Hasan, H. H. Jen

Non-Hermitian quantum systems showcase many distinct and intriguing features with no Hermitian counterparts. One of them is the exceptional point which marks the PT (parity and time) symmetry phase transition, where an enhanced spectral sensitivity arises and leads to novel quantum engineering. Here we theoretically study the multipartite entanglement proper

Joseph Raj Vishal, Divesh Basina, Aarya Choudhary, Bharatesh Chakravarthi

Recent advances in video question answering (VideoQA) offer promising applications, especially in traffic monitoring, where efficient video interpretation is critical. Within ITS, answering complex, real-time queries like "How many red cars passed in the last 10 minutes?" or "Was there an incident between 3:00 PM and 3:05 PM?" enhances situational awareness

Zhihan Cao, Hiroaki Yamada, Simone Teufel, Takenobu Tokunaga

Recently, much work has concerned itself with the enigma of what exactly pretrained language models~(PLMs) learn about different aspects of language, and how they learn it. One stream of this type of research investigates the knowledge that PLMs have about semantic relations. However, many aspects of semantic relations were left unexplored. Generally, only o

Yi-Chang Chen, Po-Chun Hsu, Chan-Jan Hsu, Da-shan Shiu

Large language models (LLMs) have significantly advanced autonomous agents, particularly in zero-shot tool usage, also known as function calling. This research delves into enhancing the function-calling capabilities of LLMs by exploring different approaches, including prompt formats for integrating function descriptions, blending function-calling and instruc

Geonho Lee, Janghwan Lee, Sukjin Hong, Minsoo Kim

Low-rank adaptation (LoRA) has become the dominant method for parameter-efficient LLM fine-tuning, with LoRA-based quantization error compensation (LQEC) emerging as a powerful tool for recovering accuracy in compressed LLMs. However, LQEC has underperformed in sub-4-bit scenarios, with no prior investigation into understanding this limitation. We propose RI

Xiaoyu Du, Yingying Chen, Yang Zhang, Jinhui Tang

Sequential recommendation approaches have demonstrated remarkable proficiency in modeling user preferences. Nevertheless, they are susceptible to profile pollution attacks (PPA), wherein items are introduced into a user's interaction history deliberately to influence the recommendation list. Since retraining the model for each polluted item is time-consuming

Leping Li, Hongqiang Song, Yijun Hou, Guiping Zhou

Failure of a filament eruption caused by magnetic reconnection between the erupting filament and the overlying magnetic field has been previously proposed in numerical simulations. It is, however, rarely observed. In this study, we report the reconnection between an erupting filament and its overlying coronal loops, that results in the failure of the filamen

Rhea Palak Bakshi, Ali Guo, Dionne Ibarra, Gabriel Montoya-Vega

Independence complexes of circle graphs are purely combinatorial objects. However, when constructed from some diagram of a link $L$, they reveal topological properties of $L$, more specifically, of its Khovanov homology. We analyze the homotopy type of independence complexes of circle graphs, with a focus on those arising when the graph is bipartite. Moreove

Qingtian Zhu, Yumin Zheng, Yuling Sang, Yifan Zhan

Spatial Transcriptomics (ST) is a method that captures gene expression profiles aligned with spatial coordinates. The discrete spatial distribution and the super-high dimensional sequencing results make ST data challenging to be modeled effectively. In this paper, we manage to model ST in a continuous and compact manner by the proposed tool, SUICA, empowered

Shu-Yue Li, Qing-Min Zhang, Bei-Li Ying, Li Feng

In this paper, we perform a follow-up investigation of the solar eruption originating from active region (AR) 13575 on 2024 February 9. The primary eruption of a hot channel (HC) generates an X3.4 class flare, a full-halo coronal mass ejection (CME), and an extreme-ultraviolet (EUV) wave. Interaction between the wave and a quiescent prominence (QP) leads to

Mengran Li, Junzhou Chen, Guanying Jiang, Fuliang Li

Accurately estimating time of arrival (ETA) for trucks is crucial for optimizing transportation efficiency in logistics. GPS trajectory data offers valuable information for ETA, but challenges arise due to temporal sparsity, variable sequence lengths, and the interdependencies among multiple trucks. To address these issues, we propose the Temporal-Attribute-

Wanting Sun, Guanghui Wang, Lan Wei

Given a system $\mathcal{G} =\{G_1,G_2,\dots,G_m\}$ of graphs/digraphs/hypergraphs on the common vertex set $V$ of size $n$, an $m$-edge graph/digraph/hypergraph $H$ on $V$ is transversal in $\mathcal{G}$ if there exists a bijection $\phi:E(H)\rightarrow [m]$ such that $e \in E(G_{\phi(e)})$ for all $e\in E(H)$. In this survey, we consider extremal problems

Zexuan Sun, Garvesh Raskutti

As opaque black-box predictive models become more prevalent, the need to develop interpretations for these models is of great interest. The concept of variable importance and Shapley values are interpretability measures that applies to any predictive model and assesses how much a variable or set of variables improves prediction performance. When the number o

Mojtaba S. Fazli, Shannon Quinn

Object tracking is a fundamental tool in modern innovation, with applications in defense systems, autonomous vehicles, and biomedical research. It enables precise identification, monitoring, and spatiotemporal analysis of objects across sequential frames, providing insights into dynamic behaviors. In cell biology, object tracking is vital for uncovering cell

Chenghao Li, Yuke Zhang, Dake Chen, Jingqi Xu

Diffusion models have demonstrated significant potential in image generation. However, their ability to replicate training data presents a privacy risk, particularly when the training data includes confidential information. Existing mitigation strategies primarily focus on augmenting the training dataset, leaving the impact of diffusion model architecture un

Min Namkung, Changhyoup Lee, Hyang-Tag Lim

In quantum multi-parameter estimation, the precision of estimating unknown parameters is bounded by the Cramer-Rao bound (CRB), defined via the inverse of the Fisher information matrix (FIM). However, in certain scenarios such as distributed quantum sensing the FIM becomes non-invertible due to parameter redundancy, which depends on the probe state and measu

Alejandro Fontan, Javier Civera, Tobias Fischer, Michael Milford

Evaluation is critical to both developing and tuning Structure from Motion (SfM) and Visual SLAM (VSLAM) systems, but is universally reliant on high-quality geometric ground truth -- a resource that is not only costly and time-intensive but, in many cases, entirely unobtainable. This dependency on ground truth restricts SfM and SLAM applications across diver

Hao Wu, Zhihang Zhong, Xiao Sun

Image captioning models often suffer from performance degradation when applied to novel datasets, as they are typically trained on domain-specific data. To enhance generalization in out-of-domain scenarios, retrieval-augmented approaches have garnered increasing attention. However, current methods face two key challenges: (1) image features used for retrieva

Cevahir Koprulu, Po-han Li, Tianyu Qiu, Ruihan Zhao

Many continuous control problems can be formulated as sparse-reward reinforcement learning (RL) tasks. In principle, online RL methods can automatically explore the state space to solve each new task. However, discovering sequences of actions that lead to a non-zero reward becomes exponentially more difficult as the task horizon increases. Manually shaping r

Keito Kudo, Yoichi Aoki, Tatsuki Kuribayashi, Shusaku Sone

This study investigates the internal information flow of large language models (LLMs) while performing chain-of-thought (CoT) style reasoning. Specifically, with a particular interest in the faithfulness of the CoT explanation to LLMs' final answer, we explore (i) when the LLMs' answer is (pre)determined, especially before the CoT begins or after, and (ii) h

C. Sampson, D. Hallman, N. B. Murphy, E. Cherkaev

Oceanic wave propagation through Earth's sea ice covers is a critical component of accurate ice and climate modeling. Continuum models of the polar ocean surface layer are characterized rheologically by the effective complex viscoelasticity of the composite of ice floes and sea water. Here we present the first rigorous theory of this parameter, and distill i

Smriti Janaswamy, Jeremy Blackburn

Social media is very popular for facilitating conversations about important topics and bringing forth insights and issues related to these topics. Reddit serves as a platform that fosters social interactions and hosts engaging discussions on a wide array of topics, thus forming narratives around these topics. One such topic is climate change. There are exten

David G. Clark, Haim Sompolinsky

Statistical-physics calculations in machine learning and theoretical neuroscience often involve lengthy derivations that obscure physical interpretation. Here, we give concise, non-replica derivations of several key results and highlight their underlying similarities. In particular, using a cavity approach, we analyze three high-dimensional learning problems

Emily Chen, Nicholas Huang, Casey Robinson, Kevin Xu

This paper explores null elements in English, Chinese, and Korean Penn treebanks. Null elements contain important syntactic and semantic information, yet they have typically been treated as entities to be removed during language processing tasks, particularly in constituency parsing. Thus, we work towards the removal and, in particular, the restoration of nu

Zuobai Zhang, Pascal Notin, Yining Huang, Aurélie Lozano

Designing novel functional proteins crucially depends on accurately modeling their fitness landscape. Given the limited availability of functional annotations from wet-lab experiments, previous methods have primarily relied on self-supervised models trained on vast, unlabeled protein sequence or structure datasets. While initial protein representation learni

Jun Xiang, Yudong Guo, Leipeng Hu, Boyang Guo

Building realistic and animatable avatars still requires minutes of multi-view or monocular self-rotating videos, and most methods lack precise control over gestures and expressions. To push this boundary, we address the challenge of constructing a whole-body talking avatar from a single image. We propose a novel pipeline that tackles two critical issues: 1)

N. Benjamin Murphy, Daniel Hallman, Elena Cherkaev, Kenneth M. Golden

Following seminal work in the early 1980s that established the existence and representations of the homogenized transport coefficients for two phase random media, we develop a mathematical framework that provides Stieltjes integral representations for the bulk transport coefficients for uniaxial polycrystalline materials, involving spectral measures of self-

Cheng Wu, Xin Ren, Yuhang Yang, Yu-Min Hu

$f(Q)$ and $f(T)$ gravity are based on fundamentally different geometric frameworks, yet they exhibit many similar properties. This article provides a comprehensive summary and comparative analysis of the various theoretical branches of torsional gravity and non-metric gravity, which arise from different choices of affine connection. We identify two types of

Takahito Fujimori

Linear Quadratic Regulator (LQR) is often combined with feedback linearization (FBL) for nonlinear systems that have the nonlinearity additive to the input. Conventional approaches estimate and cancel the nonlinearity based on the first principle or data-driven methods such as Gaussian Processes (GPs). However, the former needs an elaborate modeling process,

Ricardo Augusto Borsoi, Konstantin Usevich, David Brie, Tülay Adali

Coupled tensor decompositions (CTDs) perform data fusion by linking factors from different datasets. Although many CTDs have been already proposed, current works do not address important challenges of data fusion, where: 1) the datasets are often heterogeneous, constituting different "views" of a given phenomena (multimodality); and 2) each dataset can conta

Shuoyi Zhou, Yixuan Zhou, Weiqin Li, Jun Chen

This paper describes the zero-shot spontaneous style TTS system for the ISCSLP 2024 Conversational Voice Clone Challenge (CoVoC). We propose a LLaMA-based codec language model with a delay pattern to achieve spontaneous style voice cloning. To improve speech intelligibility, we introduce the Classifier-Free Guidance (CFG) strategy in the language model to st

Mohammad Sadeghi, Wayne Crump, Scott Parkins, Maarten Hoogerland

We demonstrate the first experimental realization of cascaded resonance fluorescence over a 64-meter propagation delay time between two spatially and temporally independent ensembles of laser-cooled Cesium atoms coupled to an optical nanofiber. Spontaneously emitted photons from a strongly driven first ensemble are guided through a standard fiber, reflected

Hanyang Jiang, Yao Xie

Reliable uncertainty quantification at unobserved spatial locations, especially in the presence of complex and heterogeneous datasets, remains a core challenge in spatial statistics. Traditional approaches like Kriging rely heavily on assumptions such as normality, which often break down in large-scale, diverse datasets, leading to unreliable prediction inte

Boris A. Malomed

This item from the News & Views category, to be published in Light: Science & Applications, aims to provide a summary of theoretical and experimental results recently published in Ref. [24], which demonstrate the creation of corner modes in nonlinear optical waveguides of the higher-order topological-insulator (HOTI) type. Actually, these are second-order HO

Katarzyna Musial, Jiaqi Wen, Andreas Gwyther-Gouriotis

Complex network systems' models are designed to perfectly emulate real-world networks through the use of simulation and link prediction. Complex network systems are defined by nodes and their connections where both have real-world features that result in a heterogeneous network in which each of the nodes has distinct characteristics. Thus, incorporating real

Muchao Ye, Weiyang Liu, Pan He

The rapid advancement of vision-language models (VLMs) has established a new paradigm in video anomaly detection (VAD): leveraging VLMs to simultaneously detect anomalies and provide comprehendible explanations for the decisions. Existing work in this direction often assumes the complex reasoning required for VAD exceeds the capabilities of pretrained VLMs.

Victor Parque

Euclidean Steiner trees are relevant to model minimal networks in real-world applications ubiquitously. In this paper, we study the feasibility of a hierarchical approach embedded with bundling operations to compute multiple and mutually disjoint Euclidean Steiner trees that avoid clutter and overlapping with obstacles in the plane, which is significant to m

Izhar Ali, Million Haileyesus, Serhiy Hnatyshyn, Jan-Lucas Ott

This project addresses challenges posed by the widespread use of abbreviations and acronyms in digital texts. We propose a novel method that combines document preprocessing, regular expressions, and a large language model to identify abbreviations and map them to their corresponding expansions. The regular expressions alone are often insufficient to extract

Mengtong Li, Tao Zhuang, Kai Chen, Jia-Xin Zhong

Compared to traditional electrodynamic loudspeakers, the parametric array loudspeaker (PAL) offers exceptional directivity for audio applications but suffers from significant nonlinear distortions due to its inherent intricate demodulation process. The Volterra filter-based approaches have been widely used to reduce these distortions, but the effectiveness i

Penghui Wen, Mengwei He, Patrick Filippi, Na Zhao

Accurate short-term precipitation forecasting is critical for weather-sensitive decision-making in agriculture, transportation, and disaster response. Existing deep learning approaches often struggle to balance global structural consistency with local detail preservation, especially under complex meteorological conditions. We propose DuoCast, a dual-diffusio

Sunghun Yang, Minhyeok Lee, Suhwan Cho, Jungho Lee

Video monocular depth estimation is essential for applications such as autonomous driving, AR/VR, and robotics. Recent transformer-based single-image monocular depth estimation models perform well on single images but struggle with depth consistency across video frames. Traditional methods aim to improve temporal consistency using multi-frame temporal module

Madeline Howell, Simon W. Campbell, Csilla Kalup, Dennis Stello

Asteroseismic masses of globular cluster (GC) stars are invaluable to investigate stellar evolution. Previously, only two GCs have been seismically studied. We present new detections of solar-like oscillations in the clusters M9 and M19, focusing on two key areas: stellar mass loss and GC multiple populations. Using K2 photometry, we detect solar-like oscill

N. A. Rather, Ishfaq Dar, Suhail Gulzar

If all the zeros of $n$th degree polynomials $f(z)$ and $g(z) = \sum_{k=0}^{n}\lambda_k\binom{n}{k}z^k$ respectively lie in the cricular regions $|z|\leq r$ and $|z| \leq s|z-\sigma|$, $s>0$, then it was proved by Marden \cite[p. 86]{mm} that all the zeros of the polynomial $h(z)= \sum_{k=0}^{n}\lambda_k f^{(k)}(z) \frac{(\sigma z)^k}{k!}$ lie in the circle

Haoran Wang, Herui Zhang, Siyang Li, Dongrui Wu

Spiking neural networks (SNNs) aim to simulate real neural networks in the human brain with biologically plausible neurons. The leaky integrate-and-fire (LIF) neuron is one of the most widely studied SNN architectures. However, it has the vanishing gradient problem when trained with backpropagation. Additionally, its neuronal parameters are often manually sp

Hyungwon Han

We provide estimates for the spectral radii of an $n\times n$ sparse non-Hermitian random matrix $Z$ with general entries in the regime $p=d/n$ where $0<d<1$ is fixed. Utilizing the structural results of ({\L}uczak, '90), we show that the spectral radius $\rho (Z)$ is $0$ with probability converging to some nonzero value, and satisfies the inequality $(\phi

Zhexuan Zeng, Ruikun Zhou, Yiming Meng, Jun Liu

Nonlinear optimal control is vital for numerous applications but remains challenging for unknown systems due to the difficulties in accurately modelling dynamics and handling computational demands, particularly in high-dimensional settings. This work develops a theoretically certifiable framework that integrates a modified Koopman operator approach with mode

Feng Ding, Ian Laga

Variable selection remains a difficult problem, especially for generalized linear mixed models (GLMMs). While some frequentist approaches to simultaneously select joint fixed and random effects exist, primarily through the use of penalization, existing approaches for Bayesian GLMMs exist only for special cases, like that of logistic regression. In this work,

Yuxing Chen, Songlin Wei, Bowen Xiao, Jiangran Lyu

For the task of hanging clothes, learning how to insert a hanger into a garment is a crucial step, but has rarely been explored in robotics. In this work, we address the problem of inserting a hanger into various unseen garments that are initially laid flat on a table. This task is challenging due to its long-horizon nature, the high degrees of freedom of th

Victor Parque

Coordinated multi-robot motion planning at intersections is key for safe mobility in roads, factories and warehouses. The rapidly exploring random tree (RRT) algorithms are popular in multi-robot motion planning. However, generating the graph configuration space and searching in the composite tensor configuration space is computationally expensive for large

Akash Kumar, MV Sunil Krishna, Alok K Ranjan

Carbon dioxide (CO2), an important trace species that is gradually increasing in the atmosphere due to anthropogenic activities, causes enhanced warming in the lower atmosphere. The increased concentration of CO2 in the upper atmosphere results in enhanced radiative cooling rates leading to the contraction of the upper atmosphere. Due to its long lifetime an

Linna Xu, Jian Huang, Shan Yang, Yongli Zhu

In this paper, an edge computing-based machine-learning study is conducted for solar inverter power forecasting and droop control in a remote microgrid. The machine learning models and control algorithms are directly deployed on an edge-computing device (a smart meter-concentrator) in the microgrid rather than on a cloud server at the far-end control center,

Tianwang Jia, Lubin Meng, Siyang Li, Jiajing Liu

Training an accurate classifier for EEG-based brain-computer interface (BCI) requires EEG data from a large number of users, whereas protecting their data privacy is a critical consideration. Federated learning (FL) is a promising solution to this challenge. This paper proposes Federated classification with local Batch-specific batch normalization and Sharpn

Shuaijiang Zhao, Tingwei Guo, Bajian Xiang, Tongtang Wan

The GPT-4o represents a significant milestone in enabling real-time interaction with large language models (LLMs) through speech, its remarkable low latency and high fluency not only capture attention but also stimulate research interest in the field. This real-time speech interaction is particularly valuable in scenarios requiring rapid feedback and immedia

Homa Nikbakht, Michèle Wigger, Shlomo Shamai, H. Vincent Poor

In this paper, we consider a point-to-point integrated sensing and communication (ISAC) system, where a transmitter conveys a message to a receiver over a channel with memory and simultaneously estimates the state of the channel through the backscattered signals from the emitted waveform. Using Massey's concept of directed information for channels with memor

Akash Mitra, Sanku Paul, Shashi C. L. Srivastava

We investigate the signature of quantum criticality in the long-time stationary state of the long-range Kitaev chain by performing various quench protocols. In this model, the pairing interaction decays with distance according to a power law with exponent $\alpha$. Using quantum information-theoretic measures, such as mutual information and logarithmic negat

Dixiao Wei, Peng Yi, Jinlong Lei, Xingyi Zhu

Truck platooning technology enables a group of trucks to travel closely together, with which the platoon can save fuel, improve traffic flow efficiency, and improve safety. In this paper, we consider the platoon coordination problem in a large-scale transportation network, to promote cooperation among trucks and optimize the overall efficiency. Involving the

Wenchao Ge, Kurt Jacobs

Distributed quantum metrology (DQM) enables the estimation of global functions of d distributed parameters beyond the capability of separable sensors. Continuous-variable DQM involves using a linear network with at least one nonclassical input. Here we fully elucidate the structure of linear networks with two non-vacuum inputs which allows us to prove a numb

Bowen Zhao, Jiuhui Li, Peiming Xu, Xiaoguo Li

Secure outsourced computation (SOC) provides secure computing services by taking advantage of the computation power of cloud computing and the technology of privacy computing (e.g., homomorphic encryption). Expanding computational operations on encrypted data (e.g., enabling complex calculations directly over ciphertexts) and broadening the applicability of

Wenqiang Luo, Jacky Wai Keung, Boyang Yang, He Ye

Software systems have been evolving rapidly and inevitably introducing bugs at an increasing rate, leading to significant losses in resources consumed by software maintenance. Recently, large language models (LLMs) have demonstrated remarkable potential in enhancing software development and maintenance practices, particularly in automated program repair (APR

Jad Damaj, Matthew Harrison-Trainor

We examine the degree spectra of relations on ${(\omega, <)}$. Given an additional relation $R$ on ${(\omega,<)}$, such as the successor relation, the degree spectrum of $R$ is the set of Turing degrees of $R$ in computable copies of ${(\omega,<)}$. It is known that all degree spectra of relations on ${(\omega,<)}$ fall into one of four categories: the compu

Jianhai Bao, Yao Liu, Jian Wang

In this note, under a weak monotonicity and a weak coercivity, we address strong well-posedness of McKean-Vlasov stochastic differential equations (SDEs) driven by L\'{e}vy jump processes, where the coefficients are Lipschitz continuous (with respect to the measure variable) under the $L^\beta$-Wasserstein distance for $\beta\in[1,2].$ Moreover, the issue on

Edward Li, Min Shen, Zhiyuan Tu, Dexin Zhou

Large language models (LLMs) promise to democratize financial analysis by reducing information-processing costs. Yet equal access does not ensure equal outcomes, as the locus of friction may shift from processing information to evaluating model outputs. We study GPT's earnings forecasts following corporate earnings releases and document two patterns. First,

Alejandro Argáez-García, Luis Elí Pech-Moreno

We provide the necessary conditions for the existence of solutions $(x,y,z)$ to $Ax^p+By^p+Cz^p=0$ over any quadratic number field $K$ with $A,B,C$ pth powerfree integer numbers. We determine when $x$, $y$ and $z$ are rational numbers for pairwise coprime integers $A$, $B$ and $C$. Moreover, we prove that $x$, $y$ and $z$ are in $K\setminus\mathbb{Q}$ when $

The Anh Bui

Let $L$ be the Dunkl Laplacian on the Euclidean space $\mathbb R^N$ associated with a normalized root $R$ and a multiplicity function $k(\nu)\ge 0, \nu\in R$. In this paper, we first prove that the Besov and Triebel-Lizorkin spaces associated with the Dunkl Laplacian $L$ are identical to the Besov and Triebel-Lizorkin spaces defined in the space of homogeneo

K. Mahesh Krishna

Let $\mathcal{X}$ be a 3-product space. Let $A: \mathcal{D}(A)\subseteq \mathcal{X}\to \mathcal{X}$, $B: \mathcal{D}(B)\subseteq \mathcal{X}\to \mathcal{X}$ and $C: \mathcal{D}(C)\subseteq \mathcal{X}\to \mathcal{X}$ be possibly unbounded 3-self-adjoint operators. Then for all \begin{align*} x \in \mathcal{D}(ABC)\cap\mathcal{D}(ACB) \cap \mathcal{D}(BAC)\ca

Xiaoxue Ma, Yishu Li, Jacky Keung, Xiao Yu

Log anomaly detection has become a common practice for software engineers to analyze software system behavior. Despite significant research efforts in log anomaly detection over the past decade, it remains unclear what are practitioners' expectations on log anomaly detection and whether current research meets their needs. To fill this gap, we conduct an empi