December 2024 arXiv papers — page 12

Haitian Chen, Qingyao Ai, Xiao Wang, Yiqun Liu

Efficiently retrieving a concise set of candidates from a large document corpus remains a pivotal challenge in Information Retrieval (IR). Neural retrieval models, particularly dense retrieval models built with transformers and pretrained language models, have been popular due to their superior performance. However, criticisms have also been raised on their

Naveed A. Abbasi, Kelvin Arana, Siddhant Singh, Atulya Bist

The upper midband, designated as Frequency Range 3 (FR3), is increasingly critical for the next-generation of wireless networks. Channel propagation measurements and their statistical analysis are essential first steps towards this direction. This paper presents a comprehensive ultra-wideband (UWB) double-directional channel measurement campaign in a large p

Jialun Li, Carlos Matheus, Wenyu Pan, Zhongkai Tao

We use the Selberg zeta function to study the limit behavior of resonances in a degenerating family of Kleinian Schottky groups. We prove that, after a suitable rescaling, the Selberg zeta functions converge to the Ihara zeta function of a limiting finite graph associated to the relevant non-Archimedean Schottky group acting on the Berkovich projective line.

Hanmeng Zhan

We consider pretty good state transfer in coined quantum walks between antipodal vertices on the hypercube $Q_d$. When $d$ is a prime, this was proven to occur in the arc-reversal walk with Grover coins. We extend this result by constructing weighted Grover coins that enable pretty good state transfer on every $Q_d$. Our coins are real, and require modificat

Chang Liu, Dejun Luo

We consider the globally modified stochastic (hyperviscous) Navier-Stokes equations with transport noise on 3D torus. We first establish the existence and pathwise uniqueness of the weak solutions, and then show their convergence to the solutions of the deterministic 3D globally modified (hyperviscous) Navier-Stokes equations in an appropriate scaling limit.

Sumit Bhattacharjee, Elena Litvinova

A consistent finite-temperature microscopic theory for the response of strongly coupled superfluid fermionic systems is formulated. We start from the general many-body Hamiltonian with the vacuum (bare) two-fermion interaction and derive the equation of motion (EOM) for the thermally averaged two-time two-fermion correlation function, which determines the sp

Sanmoy Bandyopadhyay, Vaibhav Pant

In this article, an active contours without edges (ACWE)-based algorithm has been proposed for the detection of solar filaments in H-alpha full-disk solar images. The overall algorithm consists of three main steps of image processing. These are image pre-processing, image segmentation, and image post-processing. Here in the work, contours are initialized on

Yufeng Zhu

The head-mounted display is a vital component of augmented reality, incorporating optics with complex display and see-through optical behavior. Computationally modeling these optical behaviors requires meeting three key criteria: accuracy, efficiency, and accessibility. In recent years, various approaches have been proposed to model display and see-through o

Wuzhang Fang, Edward Schwartz, Alexey A. Kovalev, K. D. Belashchenko

Field-free switching of perpendicular magnetization has been observed in an epitaxial L1$_1$-ordered CoPt/CuPt bilayer and attributed to spin-orbit torque (SOT) arising from the crystallographic $3m$ point group of the interface. Using a first-principles nonequilibrium Green's function formalism combined with the Anderson disorder model, we calculate the ang

Shafia Maryam, Mubasher Jamil, Mustapha Azreg-Aïnou, Zoe C S Chan

We investigate gravitational lensing by \textit{special} Buchdahl inspired metric with the Buchdahl parameter $\tilde{k}$. In strong deflection limit, we derive the deflection angle analytically for the light rays that diverge as photons approach the photon sphere. These are then used in order to compute the angular image positions modeling supermassive blac

Abhinav Roy, Bhavesh Gyanchandani, Aditya Oza, Abhishek Sharma

Parkinson's Disease (PD) is a degenerative neurological disorder that impairs motor and non-motor functions, significantly reducing quality of life and increasing mortality risk. Early and accurate detection of PD progression is vital for effective management and improved patient outcomes. Current diagnostic methods, however, are often costly, time-consuming

Chris J. Lygouras, Hung-Yu Yang, Xiaohan Yao, Jonathan Gaudet

Weyl fermions can arise from time-reversal symmetry-breaking magnetism, but their impact on magnetic order is a source of ongoing research. Using high-precision neutron diffraction and spectroscopy, we present a comprehensive exploration of the magnetic structure and excitation spectrum of Weyl semimetal and helical magnet NdAlSi. We use Luttinger-Tisza, cla

Yujie Li, Wenjia Xu, Guangzuo Li, Zijian Yu

The domain gap between remote sensing imagery and natural images has recently received widespread attention and Vision-Language Models (VLMs) have demonstrated excellent generalization performance in remote sensing multimodal tasks. However, current research is still limited in exploring how remote sensing VLMs handle different types of visual inputs. To bri

Tomasz Rutowski, Elizabeth Shriberg, Amir Harati, Yang Lu

Digital screening and monitoring applications can aid providers in the management of behavioral health conditions. We explore deep language models for detecting depression, anxiety, and their co-occurrence from conversational speech collected during 16k user interactions with an application. Labels come from PHQ-8 and GAD-7 results also collected by the appl

Zixuan Tan, Jiayuan Zhou, Xing Hu, Shengyi Pan

Identifying recurring vulnerabilities is crucial for ensuring software security. Clone-based techniques, while widely used, often generate many false alarms due to the existence of similar but patched (SBP) code, which is similar to vulnerable code but is not vulnerable due to having been patched. Although the SBP code poses a great challenge to the effectiv

X. H. Wu, Z. X. Ren, P. W. Zhao

Accurate description of deformed atomic nuclei by the orbital-free density functional theory has been a longstanding textbook challenge, due to the difficulty in accounting for the intricate quantum shell effects that are present in such systems. Orbital-free density functional theory is, in principle, capable of describing all effects of nuclear systems, as

Verónica Vázquez-Aceves, Yiren Lin, Alejandro Torres-Orjuela

We analyze the parameter estimation accuracy that can be achieved for the mass and spin of SgrA$^\ast$, the SMBH in our Galactic Center, by detecting multiple extremely large mass-ratio inspirals (XMRIs). XMRIs are formed by brown dwarfs (BD) inspiraling into a supermassive black hole (SMBH), thus emitting gravitational waves (GWs) inside the detection band

Yamato Suda, Daisuke Jido

Based on simulations of the interacting instanton liquid model (IILM) with three-flavor quarks, we compute the free energy density of the QCD vacuum as a function of the quark condensate. We then evaluate the second derivative of the free energy density with respect to the quark condensate at the origin. This evaluation allows us to investigate whether chira

Paula Belzig

In this thesis, we are interested in the limits of quantum communication with and without entanglement, and with and without noise assumptions on the communication setup. When a sender and a receiver are connected by a communication line that is governed by noise which is modelled by a quantum channel, they hope to design a coding scheme, i.e. messages and m

Yang Li, Dong Du, Linfeng Song, Chen Li

We introduce HunyuanProver, an language model finetuned from the Hunyuan 7B for interactive automatic theorem proving with LEAN4. To alleviate the data sparsity issue, we design a scalable framework to iterative synthesize data with low cost. Besides, guided tree search algorithms are designed to enable effective ``system 2 thinking`` of the prover. HunyuanP

Ruijuan Liu, Jinggu Wu, Yuan Jiang, Yanting Zhao

A soft ferromagnetic plate uniformizes Tesla-level fields generated by attached permanent magnets, producing a smooth and electronically tunable surface field on the opposite side. By arranging $n$ precisely fabricated rectangular plates, a nearly ideal magnetic quadrupole field with a substantial gradient can be created at center. This robust and rapidly tu

Boris Bačić, Claudiu Vasile, Chengwei Feng, Marian G. Ciucă

The purpose of this paper is to contribute towards the near-future privacy-preserving big data analytical healthcare platforms, capable of processing streamed or uploaded timeseries data or videos from patients. The experimental work includes a real-life knee rehabilitation video dataset capturing a set of exercises from simple and personalised to more gener

Steve Mann, Martin Cooper, Bran Ferren, Thomas M. Coughlin

As technology advances, the integration of physical, virtual, and social worlds has led to a complex landscape of ``Realities'' such as Virtual Reality (VR), Augmented Reality (AR), metaverse, spatial computing, and other emerging paradigms. This paper builds upon and refines the concept of eXtended Reality (XR) as the unifying framework that not only interp

Rubi Hudson

In a decision-making scenario, a principal could use conditional predictions from an expert agent to inform their choice. However, this approach would introduce a fundamental conflict of interest. An agent optimizing for predictive accuracy is incentivized to manipulate their principal towards more predictable actions, which prevents that principal from bein

Yong-Geun Oh

The present paper is a continuation of the study of the interplay between the contact Hamiltonian dynamics and the moduli theory of (perturbed) contact instantons and its applications initiated in [Oh21b, Oh22a]. In this paper we prove Weinstein's conjecture and Arnold's chord conjecture in their full generalities. The two key ingredients lying in the backgr

Yanying Cheng

With the rapid development of information and communication technology (ICT), smart classroom has become an important trend in education modernization. This article reviews the development of smart classrooms from the hardware and software levels. The hardware describes the transformation from the construction of basic ICT facilities in single mode to a mult

James A. Long, Kevin G. Milans, Michael C. Wigal

We show that if $G$ is a $n$-vertex connected chordal graph, then it admits a longest path transversal of size $O(\log^2 n)$. Under the stronger assumption of 2-connectivity, we show $G$ admits a longest cycle transversal of size $O(\log n)$. We also provide longest path and longest cycle transversals which are bounded by the leafage of the chordal graph.

A. Hayrapetyan

The title of the article is identical to the title of Chapter 21 in Gardner (2001): because we are going to analyze the probability calculations and the ambiguity of the problem statements. We will analyze 3 out of 4 problems from Gardner (2001): broken stick, two boys, three prisoners; and the obtuse random triangle in Hamming (1991) problems. Keywords: Bro

Gaoxiang Zhao, Chunmao Huang, Li Zhou, Xiaoqiang Wang

Multivariate long-term time series forecasting aims to predict future sequences by utilizing historical observations, with a core focus on modeling intra-sequence and cross-channel dependencies. Numerous studies have developed diverse architectures to capture these patterns, achieving significant improvements in forecasting accuracy. Among them, iTransformer

Bora Bozkurt, Ahmet Muaz Aktas, Hasan Atalay Gunel, Mohaned Chraiti

There is a growing interest in codebook-based beam-steering for millimeter-wave (mmWave) systems due to its potential for low complexity and rapid beam search. A key focus of recent research has been the design of codebooks that strike a trade-off between achievable gain and codebook size, which directly impacts beam search time. Statistical approaches have

Min Zhang, Zilin Wang, Liyan Chen, Kunhong Liu

Recent advances in AI-driven storytelling have enhanced video generation and story visualization. However, translating dialogue-centric scripts into coherent storyboards remains a significant challenge due to limited script detail, inadequate physical context understanding, and the complexity of integrating cinematic principles. To address these challenges,

Olaoluwa Adigun, Bart Kosko

This chapter presents the new family of soft diamond synaptic regularizers based on thick-tailed symmetric alpha stable $S{\alpha}S$ probability bell curves. These new parametrized weight priors improved deep-learning performance on image and language-translation test sets and increased the sparsity of the trained weights. They outperformed the state-of-the-

Avinash Amballa, Gayathri Akkinapalli, Vinitra Muralikrishnan

Human motion synthesis conditioned on textual input has gained significant attention in recent years due to its potential applications in various domains such as gaming, film production, and virtual reality. Conditioned Motion synthesis takes a text input and outputs a 3D motion corresponding to the text. While previous works have explored motion synthesis u

Sin Kyu Kang, Oleg Popov

In the present work, the connection between the smallness of the neutrino masses and the stability of the proton is studied. We analyze this connection from different perspectives: the smallness of neutrino mass and the proton stability originate from the same source, small neutrino masses lead to a long lived proton, and the smallness of the proton decay wi

Zhi Chen, Yun-Fei Shao, Yong Ma, Mingsheng Wei

Acoustic Scene Classification (ASC) identifies an environment based on an audio signal. This paper explores ASC in low-resource conditions and proposes a novel model, DS-FlexiNet, which combines depthwise separable convolutions from MobileNetV2 with ResNet-inspired residual connections for a balance of efficiency and accuracy. To address hardware limitations

Nikhil Srivastava

This survey accompanies a lecture on the paper ``Interlacing Families I: Bipartite Ramanujan Graphs of All Degrees'' by A. Marcus, D. Spielman, and N. Srivastava at the 2024 International Congress of Basic Science (ICBS) in July, 2024. Its purpose is to explain the developments surrounding this work over the past ten or so years, with an emphasis on connecti

Zeyu Yang, Zijie Pan, Xiatian Zhu, Li Zhang

Dynamic 3D scene representation and novel view synthesis are crucial for enabling immersive experiences required by AR/VR and metaverse applications. It is a challenging task due to the complexity of unconstrained real-world scenes and their temporal dynamics. In this paper, we reformulate the reconstruction of a time-varying 3D scene as approximating its un

Wanlin Li, Jonathan Love, Eric Stubley

We study the $\ell$-torsion subgroup in Jacobians of curves of the form $y^{\ell} = f(x)$ for irreducible $f(x)$ over a finite field $\mathbf{F}_{q}$ of characteristic $p \neq \ell$. This is a function field analogue of the study of $\ell$-torsion subgroups of ideal class groups of number fields $\mathbf{Q}(\sqrt[\ell]{N})$. We establish an upper bound, lowe

Bei Yan, Jie Zhang, Zhiyuan Chen, Shiguang Shan

The rapid integration of Large Vision-Language Models (LVLMs) into critical domains necessitates comprehensive moral evaluation to ensure their alignment with human values. While extensive research has addressed moral evaluation in LLMs, text-centric assessments cannot adequately capture the complex contextual nuances and ambiguities introduced by visual mod

Gautam Kumar, Ashwini Ratnoo

This letter presents a conflict resolution strategy for an autonomous vehicle mounted with a stereo camera approaching an unsignalized T-intersection. A mathematical model for uncertainty in stereo camera depth measurements is considered and an analysis establishes the proposed adaptive depth sampling logic which guarantees an upper bound on the computed clo

Linda M. Carpenter, Katherine Schwind, Taylor Murphy

We explore models where single new exotic states interact with the Standard Model through an asymmetric Standard Model portal with couplings to at least one quark and one lepton. All effective operators up to dimension six where such interactions couple the SM to spin 0 and spin 1/2 particles are written down, and the exotic states accessible through the por

Peixin Xu, Yujuan Ding, Wenqi Fan

Chart summarization, which focuses on extracting key information from charts and interpreting it in natural language, is crucial for generating and delivering insights through effective and accessible data analysis. Traditional methods for chart understanding and summarization often rely on multi-stage pipelines, which may produce suboptimal semantic alignme

Haotian Fu, Peng Zhang, Song Yang, Herui Zhang

A brain-computer interface (BCI) facilitates direct interaction between the brain and external devices. To concurrently achieve high decoding accuracy and low energy consumption in invasive BCIs, we propose a novel spiking neural network (SNN) framework incorporating local synaptic stabilization (LSS) and channel-wise attention (CA), termed LSS-CA-SNN. LSS o

Kazufumi Ito

In this paper we discuss inverse medium problems. We develop the direct sampling method based on probing indices using the saddle point formulation. The medium is constructed by solutions of saddle point problems. The method improves the probing functions for the direct sampling method and directly images the medium. The method is very efficient and can be a

Andrew Comech, Hatice Pekmez

We consider the resolvent estimates and properties of virtual states of the higher order derivatives in one dimension, focusing on Schroedinger-type operators of degree $N=3$ (the approach applies to higher orders). The derivation is based on the construction of the Jost solution for higher order differential operators and on restricting the resolvent onto s

Yi-Jen Lee

Motivated by a variant of Atiyah-Floer conjecture proposed in \cite{L2} and its potential generalizations, we study in this article and its sequel as a first step properties of moduli spaces of Seiberg-Witten equations on a 3-dimensional cobordism with cylindrical ends (CCE) \(Y\), perturbed by closed 2-forms of the form \(r*d\ff+w\), where \(r\geq 1\), wher

Peixin Dai, Jingsi Zhang, Zhitao Shu

Accurate identification and localisation of brain tumours from medical images remain challenging due to tumour variability and structural complexity. Convolutional Neural Networks (CNNs), particularly ResNet and Unet, have made significant progress in medical image processing, offering robust capabilities for image segmentation. However, limited research has

Zhengsong Lu, Bo Zeng

In this paper, we study the two-stage distributionally robust optimization (DRO) problem from the primal perspective. Unlike existing approaches, this perspective allows us to build a deeper and more intuitive understanding on DRO, to leverage classical and well-established solution methods and to develop a general and fast decomposition algorithm (and its v

Venkat Ram Reddy Ganuthula

This paper introduces Agency-Driven Labor Theory as a new theoretical framework for understanding human work in AI-augmented environments. While traditional labor theories have focused primarily on task execution and labor time, ADLT proposes that human labor value is increasingly derived from agency - the capacity to make informed judgments, provide strateg

Zixiang Wan, Ziyue Qiu, Yiyang Liu, Wei-Qiang Zhang

Speech Emotion Recognition (SER) involves analyzing vocal expressions to determine the emotional state of speakers, where the comprehensive and thorough utilization of audio information is paramount. Therefore, we propose a novel approach on self-supervised learning (SSL) models that employs all available auxiliary information -- specifically metadata -- to

Anisha G. Singh, Matthew Krogstad, Maja D. Bachmann, Paul Thompson

We explore, through a combination of x-ray diffraction and elastoresistivity measurements, the effect of disorder on the strain-tuned charge density wave and associated multicriticality in Pd$_x$ErTe$_3$ (x = 0, 0.01, 0.02 and 0.026). We focus particularly on the behavior near the strain-tuned bicritical point that occurs in pristine ErTe$_3$ (x=0). Our stud

Young-Pil Choi, Jinwook Jung, Yoonjung Lee

This paper investigates the global dynamics of the Euler--Riesz system in three dimensions, focusing on the well-posedness and large-time behavior of solutions near equilibrium. The system generalizes classical interactions by incorporating the Riesz interactions $\nabla (-\Delta)^{-\sigma/2}(\rho - 1)$. We show that the system admits a global smooth solutio

Sungik Choi, Hankook Lee, Jaehoon Lee, Seunghyun Kim

Dramatic advances in the quality of the latent diffusion models (LDMs) also led to the malicious use of AI-generated images. While current AI-generated image detection methods assume the availability of real/AI-generated images for training, this is practically limited given the vast expressibility of LDMs. This motivates the training-free detection setup wh

Qiao Zhang, Xiao Li, Xiucui Guan

We consider the Restricted Inverse Optimal Value Problem (RIOVSP) on trees under weighted bottleneck Hamming distance, denoted as (RIOVSPT$_{BH}$). The problem aims to minimize the total cost under weighted bottle-neck Hamming distance such that the length of the shortest root-leaf path of the tree is lower-bounded by a given value by adjusting the length of

Pablo Romero

Let $G$ be a connected simple graph on $n$ vertices and $m$ edges. Denote $N_{i}^{(j)}(G)$ the number of spanning subgraphs of $G$ having precisely $i$ edges and not more than $j$ connected components. The graph $G$ is \emph{strong} if $N_{i}^{j}(G)\geq N_{i}^{j}(H)$ for each pair of integers $i\in \{0,1,\ldots,m\}$ and $j\in \{1,2,\ldots,n\}$ and each conne

Hiran Sarkar, Vishal Chudasama, Naoyuki Onoe, Pankaj Wasnik

Open-Set Object Detection (OSOD) has emerged as a contemporary research direction to address the detection of unknown objects. Recently, few works have achieved remarkable performance in the OSOD task by employing contrastive clustering to separate unknown classes. In contrast, we propose a new semantic clustering-based approach to facilitate a meaningful al

Mark Huber, Danny Vargas

In 1976, Knuth and Yao presented an algorithm for sampling from a finite distribution using flips of a fair coin that on average used the optimal number of flips. Here we show how to easily run their algorithm for the special case of rolling a fair die that uses memory linear in the input. Analysis of this algorithm yields a bound on the average number of co

Ying Zhang, Haibao Yan, Danni Zhu, Jiankun Wang

Air-ground collaborative robots have shown great potential in the field of fire and rescue, which can quickly respond to rescue needs and improve the efficiency of task execution. Mapping and navigation, as the key foundation for air-ground collaborative robots to achieve efficient task execution, have attracted a great deal of attention. This growing intere

Yi-Hao Chen

This tutorial is designed to clarify a few misconceptions in the field of ultrafast optics. (1) Analytic signal that underlies the complex-conjugate decomposition of the field is discussed, as well as the misunderstanding between propagation-constant-offset and offset-frequency analytic signal and slowly-varying envelope assumption. (2) It contains complete

Xiaoli Liu, Shixu Meng, Jialu Tian, Bo Zhang

This work considers a time domain inverse acoustic obstacle scattering problem due to passive data. Motivated by the Helmholtz-Kirchhoff identity in the frequency domain, we propose to relate the time domain measurement data in passive imaging to an approximate data set given by the subtraction of two scattered wave fields. We propose a time domain linear sa

Dehao Zhao

Symmetric teleparallel gravity (STG) can be regarded as a modified gravity theory that lacks diffeomorphism symmetries, which complicates the calculation of its degrees of freedom. In this study, we analyze the linear perturbations of general STG models on a Minkowski background, considering both scenarios with and without scalar couplings. Furthermore, we p

Aditya Rauniyar, Micah Corah, Sebastian Scherer

Motion capture has become increasingly important, not only in computer animation but also in emerging fields like the virtual reality, bioinformatics, and humanoid training. Capturing outdoor environments offers extended horizon scenes but introduces challenges with occlusions and obstacles. Recent approaches using multi-drone systems to capture multiple act

Zijie Chen, Zhanchao Zhou, Yu Lu, Renjun Xu

Solving NP-hard problems traditionally relies on heuristics, yet manually designing effective heuristics for complex problems remains a significant challenge. While recent advancements like FunSearch have shown that large language models (LLMs) can be integrated into evolutionary algorithms (EAs) for heuristic design, their potential is hindered by limitatio

Peijie Feng, Fubei Liu, Yuanfeng Liu, Mingzhe Chong

Free-space wavefront manipulation devices have emerged as powerful platforms for advanced optical information systems. In response to the challenges posed by the exponential growth of optical information, optical multiplexing and dynamic reconfigurable devices are being actively explored to the enhance system capacity. Among them, coarse-grained mechanically

An Fu, Chang-ai Sun, Jiaming Zhang, Huai Liu

Metamorphic testing (MT) is a simple yet effective technique to alleviate the oracle problem in software testing. The underlying idea of MT is to test a software system by checking whether metamorphic relations (MRs) hold among multiple test inputs (including source and follow-up inputs) and the actual output of their executions. Since MRs and source inputs

Bruce Deng, Mayank Kejriwal

Agent-based modeling (ABM) has become a cornerstone of complexity science, enabling the study of heterogeneous agents interacting within dynamic environments. Among ABM frameworks, John Conway's Game of Life (GoL) stands out for its simplicity and ability to generate emergent macroscopic patterns from basic microscopic rules. In this paper, we propose and im

Ryuna Nagayama, Kohei Yoshimura, Sosuke Ito

Activity, which represents the kinetic property of dynamics, plays a central role in obtaining thermodynamic speed limits (TSLs). In this paper, we discuss a unified framework that provides the existing TSLs based on different activities such as dynamical activity and dynamical state mobility. This unification is based on generalized means that include stand

Cory Hargus, Federico Ghimenti, Julien Tailleur, Frédéric van Wijland

When submerged in a chiral active bath, a passive object becomes a spinning ratchet imbued with odd transport properties. We present the most general Langevin dynamics for a rigid body in a chiral active bath, in the adiabatic limit of large object mass. For rotationally symmetric objects, odd diffusion and odd mobility are connected by an Einstein relation,

Venkata Sai Chandra Prasanth Narisetty, Tejaswi Maddineni

Autonomous vehicle (AV) technology is transforming the landscape of transportation bypromising safer, more efficient, and sustainable mobilitysolutions. In recent years, significant advancements in AI, machine learning, sensor fusion, and vehicle-to-everything(V2X)communicationhavepropelledthedevelopmentoffullyautonomous vehicles. This paper explores the cut

Venkata Sai Chandra Prasanth Narisetty, Tejaswi Maddineni

The global shift towards electric vehicles (EVs) as a sustainable alternative to traditional gasoline-powered cars has triggered a significant rise in the demand for lithium-ion batteries. However, as the adoption of EVs grows, the issue of battery disposal and recycling has emerged as a critical challenge. The recycling of EV batteries is essential not only

Jay A. Berres, S. Ali Hassani Gangaraj, George W. Hanson

We establish the theoretical framework for a material system that supports surface plasmon polaritions (SPPs) excited by a dipole excitation, where the media configuration suddenly changes at a temporal boundary. We employ three-dimensional Green's function analysis in the Laplace transform domain. We use this framework to demonstrate dynamic SPP formation a

Mai Xu, Yinglin Zhu, Qunliang Xing, Jing Yang

Stereo images captured by Mars rovers are transmitted after lossy compression due to the limited bandwidth between Mars and Earth. Unfortunately, this process results in undesirable compression artifacts. In this paper, we present a novel stereo quality enhancement approach for Martian images, named MarsSQE. First, we establish the first dataset of stereo Ma

Chunsheng Zuo, Pavel Guerzhoy, Michael Guerzhoy

Transformers with causal attention can solve tasks that require positional information without using positional encodings. In this work, we propose and investigate a new hypothesis about how positional information can be stored without using explicit positional encoding. We observe that nearby embeddings are more similar to each other than faraway embeddings

Pablo Romero

If $G$ is a simple graph and $\rho\in[0,1]$, the reliability $R_G(\rho)$ is the probability of $G$ being connected after each of its edges is removed independently with probability $\rho$. A simple graph $G$ is a \emph{uniformly most reliable graph} (UMRG) if $R_G(\rho)\geq R_H(\rho)$ for every $\rho\in[0,1]$ and every simple graph $H$ on the same number of

Wen-Bin Pan, Zhangping Yu, Yi Ling

We investigate second-order gravitational perturbations in asymptotically AdS black branes, developing a gauge-invariant framework to compute the amplitude ratio between quadratic and linear quasi-normal modes. Our analysis reveals resonant divergences of this ratio when the summed frequencies of two source modes coincide with the frequency of a third mode.

Yuhe Ding, Bo Jiang, Aihua Zheng, Qin Xu

Vision language models (VLMs) like CLIP show stellar zero-shot capability on classification benchmarks. However, selecting the VLM with the highest performance on the unlabeled downstream task is non-trivial. Existing VLM selection methods focus on the class-name-only setting, relying on a supervised large-scale dataset and large language models, which may n

Alessandro Danelon, Andrew Snowden

A tensor space is a vector space equipped with a finite collection of multilinear forms. The length of a tensor space is its length as a representation of its symmetry group. Infinite dimension tensor spaces of finite length are special, highly symmetrical objects. We classify the (universal) biquadratic spaces of length two; there are seven families of them

Peng Zhang, Heye Huang, Hang Zhou, Haotian Shi

This paper introduces a physics enhanced residual learning (PERL) framework for connected and automated vehicle (CAV) platoon control, addressing the dynamics and unpredictability inherent to platoon systems. The framework first develops a physics-based controller to model vehicle dynamics, using driving speed as input to optimize safety and efficiency. Then

Calder Katyal

The integration of optimization problems within neural network architectures represents a fundamental shift from traditional approaches to handling constraints in deep learning. While it is long known that neural networks can incorporate soft constraints with techniques such as regularization, strict adherence to hard constraints is generally more difficult.

Calder Katyal

One of the emerging techniques in node classification in heterogeneous graphs is to restrict message aggregation to pre-defined, semantically meaningful structures called metapaths. This work is the first attempt to incorporate attention into the process of encoding entire metapaths without dropping intermediate nodes. In particular, we construct two encoder

Qingyun Jin, Xiaohui Song, Feng Zhou, Zengchang Qin

Large language models (LLMs) have demonstrated exceptional performance across diverse natural language processing tasks. However, as the model size and the input sequence's length increase, the linearly increasing key-value (KV) cache significantly degrades inference throughput. Therefore, grouped-query attention (GQA), as an alternative to multi-head attent

Julian Chaidez

This article clarifies the status of linearized contact homology given the foundations of the contact dg-algebra established by Pardon. In particular, we prove that the set of isomorphism classes of linearized contact homologies of a closed contact manifold is a contact invariant.

Zhen Ma, He Xu, Jielong Dou, Yi Qin

Magnetic adhesion tracked climbing robots are widely utilized in high-altitude inspection, welding, and cleaning tasks due to their ability to perform various operations against gravity on vertical or inclined walls. However, during operation, the robot may experience overturning torque caused by its own weight and load, which can lead to the detachment of m

Ervin Moore, Ahmed Imteaj, Md Zarif Hossain, Shabnam Rezapour

Federated Learning (FL) is a privacy-preserving distributed machine learning scheme, where each participant data remains on the participating devices and only the local model generated utilizing the local computational power is transmitted throughout the database. However, the distributed computational nature of FL creates the necessity to develop a mechanis

Yongjie Fu, Mehmet K. Turkcan, Mahshid Ghasemi, Zhaobin Mo

We present methods and applications for the development of digital twins (DT) for urban traffic management. While the majority of studies on the DT focus on its ``eyes," which is the emerging sensing and perception like object detection and tracking, what really distinguishes the DT from a traditional simulator lies in its ``brain," the prediction and decisi

Frank Wang, Eric Yee

We compute the Hilbert series of the space of $n=3$ variable quasi-invariant polynomials in characteristic $2$ and $3$, capturing the dimension of the homogeneous components of the space, and explicitly describe the generators in the characteristic $2$ case. In doing so we extend the work of the first author in 2023 on quasi-invariant polynomials in characte

Kazuto Oshima

We construct superposition states of energy eigenstates of the hydrogen molecule using classically emulated digital quantum simulation. We generate the ground state and excited states of the system via the twirling operation method, and construct superposition states of the ground state and an excited state of the system by applying a controlled excitation u

Junyi Chen, Mengjia Wu, Qian Liu, Ying Ding

The degraded performance and group unfairness caused by confounding sensitive attributes in rumor detection remains relatively unexplored. To address this, we propose a two-step framework. Initially, it identifies confounding sensitive attributes that limit rumor detection performance and cause unfairness across groups. Subsequently, we aim to learn equally

Sharika J. Hegde, Max T. M. Ng, Marcos Rios, Hani S. Mahmassani

The COVID-19 vaccine development, manufacturing, transportation, and administration proved an extreme logistics operation of global magnitude. Global vaccination levels, however, remain a key concern in preventing the emergence of new strains and minimizing the impact of the pandemic's disruption of daily life. In this paper, country-level vaccination rates

Jian Liang, Lijun Sheng, Hongmin Liu, Ran He

Unsupervised domain adaptation aims to transfer knowledge from a related, label-rich source domain to an unlabeled target domain, thereby circumventing the high costs associated with manual annotation. Recently, there has been growing interest in source-free domain adaptation, a paradigm in which only a pre-trained model, rather than the labeled source data,

Max T. M. Ng, Hani S. Mahmassani, Joseph L. Schofer

To measure the impacts on U.S. rail and intermodal freight by economic disruptions of the 2007-09 Great Recession and the COVID-19 pandemic, this paper uses time series analysis with the AutoRegressive Integrated Moving Average (ARIMA) family of models and covariates to model intermodal and commodity-specific rail freight volumes based on pre-disruption data

Genji Fujii

Measurement-based quantum computation (MBQC) is a protocol for quantum computation that represents a model distinct from the circuit-based approach. MBQC has been proposed not only for qubits but also for qudits, continuous-variable (CV) qubits, and Bose-Einstein condensates (BECs) qubits. In qubit-based MBQC, arbitrary rotations on the Bloch sphere can be p

Max T. M. Ng, Hani S. Mahmassani

This paper investigates managed lane (ML) toll setting and its effect under mixed traffic of connected automated vehicles (CAVs), high-occupancy vehicles (HOVs), and human-driven vehicles (HDVs), with a goal to avoid flow breakdown and minimize total social cost. A mesoscopic finite-difference traffic simulation model considers the flow-density relationship

Skanda Bharadwaj, Robert Collins, Yanxi Liu

Classical approaches to Vanishing Point Detection (VPD) rely solely on the presence of explicit straight lines in images, while recent supervised deep learning approaches need labeled datasets for training. We propose an alternative unsupervised approach: Recurrence-based Vanishing Point Detection (R-VPD) that uses implicit lines discovered from recurring co

Yuxuan Li, Xiang Li, Yunheng Li, Yicheng Zhang

With the rapid advancement of remote sensing technology, high-resolution multi-modal imagery is now more widely accessible. Conventional Object detection models are trained on a single dataset, often restricted to a specific imaging modality and annotation format. However, such an approach overlooks the valuable shared knowledge across multi-modalities and l

Tao Yang, Rong-Gen Cai, Zhoujian Cao, Hyung Mok Lee

Early detection and localization of gravitational waves (GWs) are essential for identifying electromagnetic (EM) counterparts, playing a key role in multi-messenger astronomy. However, second-generation (2G) ground-based detectors are most sensitive to frequencies of tens to hundreds of hertz, limiting the in-band duration of GW signals to $\mathcal{O}(0.1)$

Bobo Hua, Jin Sun

We study the hot spots conjecture for domains in the Gaussian space $(\mathbb{R}^n, (2\pi)^{-n/2} e^{-|x|^2/2} dx)$ for $n \ge 2$. Given a bounded domain $\Omega$ with a piecewise smooth boundary, we consider the first nontrivial eigenfunction of the Ornstein--Uhlenbeck operator $L_\gamma = \Delta - \langle x, \nabla \rangle$ subject to Neumann or mixed Diri

Yitong Zhou, Mingyue Cheng, Qingyang Mao, Feiyang Xu

Pre-trained foundation models have recently made significant progress in table-related tasks such as table understanding and reasoning. However, recognizing the structure and content of unstructured tables using Vision Large Language Models (VLLMs) remains under-explored. To bridge this gap, we propose a benchmark based on a hierarchical design philosophy to

Sawyer Jack Robertson

There are several interrelated notions of discrete curvature on graphs. Many approaches utilize the optimal transportation metric on its probability simplex or the distance matrix of the graph. In this survey article, we compute formulas for three different types of curvature on graphs. Along the way, we obtain a comparison result for the curvatures under co

Muskan Shergill, Zach Thompson, Guanqun Song, Ting Zhu

LPWAN service's inexpensive cost and long range capabilities make it a promising addition and countless satellite companies have started taking advantage of this technology to connect IoT users across the globe. However, LEO satellites have the unique challenge of using rechargeable batteries and green solar energy to power their components. LPWAN technology