March 2025 arXiv papers — page 199

Jie Zhou, Youshu Ji, Ning Wang, Yuchen Hu

SystemVerilog Assertions (SVAs) are essential for verifying Register Transfer Level (RTL) designs, as they can be embedded into key functional paths to detect unintended behaviours. During simulation, assertion failures occur when the design's behaviour deviates from expectations. Solving these failures, i.e., identifying and fixing the issues causing the de

Hui-Juan Zhou, Yong Chen

Physics-informed neural network (PINN) is a powerful emerging method for studying forward-inverse problems of partial differential equations (PDEs), even from limited sample data. Variable coefficient PDEs, which model real-world phenomena, are of considerable physical significance and research value. This study proposes a gradient-enhanced PINN with residua

Nikolaos Angelinos

We introduce a code construction for Wess-Zumino-Witten (WZW) models associated with simply-laced affine Lie algebras at level 1. The chiral primary fields of these rational CFTs can be parametrized by the elements of the outer automorphism group of the affine algebra, which is isomorphic to the discriminant group $G$ of the root lattice. We show that the cl

Shahrzad Kiani, Franziska Boenisch, Stark C. Draper

Federated Learning (FL) is the standard protocol for collaborative learning. In FL, multiple workers jointly train a shared model. They exchange model updates calculated on their data, while keeping the raw data itself local. Since workers naturally form groups based on common interests and privacy policies, we are motivated to extend standard FL to reflect

Tiankuo Zhang, Benoit Montreuil, Ali V Barenji, Praveen Muthukrishnan

Resource allocations in an election system, often with hundreds of polling locations over a territory such as a county, with the aim that voters receive fair and efficient services, is a challenging problem, as election resources are limited and the number of expected voters can be highly volatile through the voting period. This paper develops two propositio

Ziruo Hao, Zhenhua Cui, Tao Yang, Bo Hu

Federated learning (FL) has provided a new methodology for coordinating a group of clients to train a machine learning model collaboratively, bringing an efficient paradigm in edge intelligence. Despite its promise, FL faces several critical challenges in practical applications involving edge devices, such as data heterogeneity and delays stemming from commu

Xi Ye, Rui Heng Yang, Jun Jin, Yinchuan Li

Diffusion models exhibit impressive scalability in robotic task learning, yet they struggle to adapt to novel, highly dynamic environments. This limitation primarily stems from their constrained replanning ability: they either operate at a low frequency due to a time-consuming iterative sampling process, or are unable to adapt to unforeseen feedback in case

Zhong Ji, Weilong Cao, Yan Zhang, Yanwei Pang

Diffusion models has emerged as a powerful framework for tasks like image controllable generation and dense prediction. However, existing models often struggle to capture underlying semantics (e.g., edges, textures, shapes) and effectively utilize in-context learning, limiting their contextual understanding and image generation quality. Additionally, high co

Chengxin Zhang, Yujie Liu, Quan Chen

As the demand for computational power increases, high-bandwidth memory (HBM) has become a critical technology for next-generation computing systems. However, the widespread adoption of HBM presents significant thermal management challenges, particularly in multilayer through-silicon-via (TSV) stacked structures under varying thermal conditions, where accurat

Xiaoding Yang

The gravity-capillary problem with inclined walls is a problem that describes an open fluid flowing over an angled wall. It has broad applications in science and engineering. In this paper, we study the steady states of the two-dimensional inclined-wall problem. The steady-state configurations are characterized as solutions of the Euler-Lagrange equation ass

Muheng Li, Ruqi Zhang

Recently, gradient-based discrete sampling has emerged as a highly efficient, general-purpose solver for various combinatorial optimization (CO) problems, achieving performance comparable to or surpassing the popular data-driven approaches. However, we identify a critical issue in these methods, which we term ''wandering in contours''. This behavior refers t

Zhipeng Zhou, Ziqiao Meng, Pengcheng Wu, Peilin Zhao

Multi-task learning (MTL) is a widely explored paradigm that enables the simultaneous learning of multiple tasks using a single model. Despite numerous solutions, the key issues of optimization conflict and task imbalance remain under-addressed, limiting performance. Unlike existing optimization-based approaches that typically reweight task losses or gradien

Daniel R. Johnston, Simon N. Thomas

For any fixed $k\geq 2$, we prove that every sufficiently large integer can be expressed as the sum of a $k$th power of a prime and a number with at most $M(k)=6k$ prime factors. For sufficiently large $k$ we also show that one can take $M(k)=(2+\varepsilon)k$ for any $\varepsilon>0$, or $M(k)=(1+\varepsilon)k$ under the assumption of the Elliott--Halberstam

Jing-Qiang Peng, Shu Zhang, Qing-Cang Shui, Shuang-Nan Zhang

Swift J1727.8--1613 is a black hole X-ray binary that differs from other black hole X-ray binaries in that it has an extra hard component in addition to a reflection component. We perform spectral analysis with simultaneous Insight-HXMT, NICER and NuSTAR observations when the source was in the hard and hard intermediate states. For the presentation of the ex

Xiaofeng Lin, Enduo Zhao, Saúl Alexis Heredia Pérez, Kanako Harada

Estimating the state of biological specimens is challenging due to limited observation through microscopic vision. For instance, during mouse skull drilling, the appearance alters little when thinning bone tissue because of its semi-transparent property and the high-magnification microscopic vision. To obtain the object's state, we introduce an object state

Ya-Ping Li, Huan Yang, Zhen Pan

In this work, we numerically explore the dynamics of a point mass (e.g., a stellar-mass black hole) moving within a thin accretion disk of a massive object (i.e., a supermassive black hole) with three dimensional hydrodynamical simulations using \texttt{Athena++}. We are particularly interested in the regime that the Hill radius of the point mass is greater

Tianyi Liao, Wei Guo, Hengtao He, Shenghui Song

The fluid antenna system (FAS) is a disruptive tech-nology for future wireless communication networks. This paper considers the joint optimization of beamforming matrices and antenna positions for weighted sum rate (WSR) maximization in fluid antenna (FA)-assisted multiuser multiple-input multiple-output (MU-MIMO) networks, which presents significant chal-le

Maurice S. Fabien

This paper designs a high-order positivity-preserving discontinuous Galerkin (DG) scheme for a linear hyperbolic equation. The scheme relies on augmenting the standard polynomial DG spaces with additional basis functions. The purpose of these augmented basis functions is to ensure the preservation of a positive cell average for the unmodulated DG solution. A

Enduo Zhao, Xiaofeng Lin, Yifan Wang, Kanako Harada

Automating bone micro-milling using a robotic system presents challenges due to the uncertainties in both the external and internal features of bone tissue. For example, during mouse cranial window creation, a circular path with a radius of 2 to 4 mm needs to be milled on the mouse skull using a microdrill. The uneven surface and non-uniform thickness of the

Yifei Gao, Jun Huang, Lei Wang, Ruiting Dai

The emergence of 3D Gaussian Splatting (3D-GS) has significantly advanced 3D reconstruction by providing high fidelity and fast training speeds across various scenarios. While recent efforts have mainly focused on improving model structures to compress data volume or reduce artifacts during zoom-in and zoom-out operations, they often overlook an underlying i

Xinyue Cui, Johnny Tian-Zheng Wei, Swabha Swayamdipta, Robin Jia

Data watermarking in language models injects traceable signals, such as specific token sequences or stylistic patterns, into copyrighted text, allowing copyright holders to track and verify training data ownership. Previous data watermarking techniques primarily focus on effective memorization during pretraining, while overlooking challenges that arise in ot

Chenyi Zhou, Rubin Huo, Boyi Situ, Zihan Yan

Octa-penta graphene (OPG), a novel carbon allotrope characterized by its distinctive arrangement of pentagonal and octagonal rings, has garnered considerable attention due to its exceptional structure and functional properties. This study systematically investigates the oxidation mechanisms of OPG and elucidates the oxygen migration patterns on the OPG monol

Xihan Wang, Dianyi Yang, Yu Gao, Yufeng Yue

Recent advancements in 3D Gaussian Splatting(3DGS) have significantly improved semantic scene understanding, enabling natural language queries to localize objects within a scene. However, existing methods primarily focus on embedding compressed CLIP features to 3D Gaussians, suffering from low object segmentation accuracy and lack spatial reasoning capabilit

Joseph Kump, Anna Yesypenko, Per-Gunnar Martinsson

We introduce a two-level direct solver for the Hierarchical Poincar\'e-Steklov (HPS) method for solving linear elliptic PDEs. HPS combines multidomain spectral collocation with a direct solver, enabling high-order discretizations for highly oscillatory solutions while preserving computational efficiency. Our method employs batched linear algebra routines wit

Weida Hu, Casey Papovich, Lu Shen, Zixuan Peng

Recent JWST observations have uncovered high-redshift galaxies characterized by multiple star-forming clumps, many of which appear to be undergoing mergers. Such mergers, especially those of two galaxies with equivalent masses, play a critical role in driving galaxy evolution and regulating the chemical composition of their environments. Here, we report a ma

I-Jung Hsu, Chih-Hsun Lin, Chia-Mu Yu, Sy-Yen Kuo

Trajectory data, which tracks movements through geographic locations, is crucial for improving real-world applications. However, collecting such sensitive data raises considerable privacy concerns. Local differential privacy (LDP) offers a solution by allowing individuals to locally perturb their trajectory data before sharing it. Despite its privacy benefit

Pulak Ranjan Giri

Quantum walk followed by some amplitude amplification technique has been successfully used to search for marked vertices on various graphs. Lackadaisical quantum walk can search for target vertices on graphs without the help of any additional amplitude amplification technique. These studies either exploit AKR or SKW coin to distinguish the marked vertices fr

Aocheng Li, James R. Zimmer-Dauphinee, Rajesh Kalyanam, Ian Lindsay

Point cloud completion helps restore partial incomplete point clouds suffering occlusions. Current self-supervised methods fail to give high fidelity completion for large objects with missing surfaces and unbalanced distribution of available points. In this paper, we present a novel method for restoring large-scale point clouds with limited and imbalanced gr

Zhe Zhang, Jiajie Qiao, Xiaoliang Wu, Shaowen Yu

For the special single-layer fractional quantum Hall system with a filling factor of 5/2, which has an even denominator, this paper uses principal component analysis (PCA) to study its behavior under the breaking of particle-hole symmetry. By introducing a model three-body potential to represent the mechanism of particle-hole symmetry breaking, the paper fin

Jimin Bai, Long-Zhou Huang, Jin Shang, Yun-Jiang Wang

Stress-stress correlations in crystalline solids with long-range order can be straightforwardly derived using elasticity theory. In contrast, the `emergent elasticity' of amorphous solids, rigid materials characterized by an underlying disordered structure, defies direct explanation within traditional theoretical frameworks. To address this challenge, tensor

Tanumoy Banerjee, Kevin Ji, Weiyi Xia, Gaoyuan Ouyang

The transition to a low-carbon economy demands efficient and sustainable energy-storage solutions, with hydrogen emerging as a promising clean-energy carrier and with metal hydrides recognized for their hydrogen-storage capacity. Here, we leverage machine learning (ML) to predict hydrogen-to-metal (H/M) ratios and solution energy by incorporating thermodynam

Minh Trung Tran, Nasrin Sohrabi, Zahir Tari, Qin Wang

We identify the slow liquidity drain (SLID) scam, an insidious and highly profitable threat to decentralized finance (DeFi), posing a large-scale, persistent, and growing risk to the ecosystem. Unlike traditional scams such as rug pulls or honeypots (USENIX Sec'19, USENIX Sec'23), SLID gradually siphons funds from liquidity pools over extended periods, makin

Areej A. Almoneef, Rashad A. Abdel-baky

This work investigates slant timelike-ruled surfaces and their evolute offsets in Minkowski 3-space $\mathbb{E}_{1}^{3}$. Using the symmetry of evolute curves, we derive a parametric formulation for skew timelike-ruled surfaces and establish conditions ensuring the coaxial alignment of the central normal with the ruling direction of the corresponding offset

Xiaoxiang Chai, Gaoming Wang

A warped product with a spherical factor and a logarithmically concave warping function satisfies a scalar curvature rigidity of the Llarull type. We develop a scalar curvature rigidity of the Llarull type for a general class of domains in a three dimensional spherical warped product. In the presence of rotational symmetry, we identify this class of domains

Philip Charles, Deep Ray, Yue Yu, Joost Prins

The optimal Petrov-Galerkin formulation to solve partial differential equations (PDEs) recovers the best approximation in a specified finite-dimensional (trial) space with respect to a suitable norm. However, the recovery of this optimal solution is contingent on being able to construct the optimal weighting functions associated with the trial basis. While e

Zhaoxia Heng, Zehan Li, Haijing Zhou

The search for light scalar and pseudoscalar particles provides a promising avenue for probing physics beyond the Standard Model (SM). In this study, we investigated the exotic decay channels of the 125 GeV SM-like Higgs boson into pairs of light CP-odd ($a_s$) or CP-even ($h_s$) Higgs bosons within the framework of the General Next-to-Minimal Supersymmetric

Mary Shaw

Producing a good software design involves not only writing a definition that satisfies the syntax of the chosen language or structural constraints of a design paradigm. It also involves upholding a variety of expectations about the behavior of the system: the semantic expectations. These expectations may apply not only at the code level, but also to more abs

Wanglong Lu, Lingming Su, Jingjing Zheng, Vinícius Veloso de Melo

Digital versions of real-world text documents often suffer from issues like environmental corrosion of the original document, low-quality scanning, or human interference. Existing document restoration and inpainting methods typically struggle with generalizing to unseen document styles and handling high-resolution images. To address these challenges, we intr

Yin Li, Hua Chen, Fugee Tsung

Motion stages are critical in semiconductor manufacturing equipment for processes like die bonding, wafer loading, and chip packaging, as their performance must meet the industry's stringent precision requirements. Vibration, a significant yet often overlooked adversary to precision motion stages, is challenging to identify and mitigate due to its subtle nat

Kequan Chen, Pan Liu, Yuxuan Wang, David Z. W. Wang

Accurate prediction of traffic crash risks for individual vehicles is essential for enhancing vehicle safety. While significant attention has been given to traffic crash risk prediction, existing studies face two main challenges: First, due to the scarcity of individual vehicle data before crashes, most models rely on hypothetical scenarios deemed dangerous

Dmitrii L. Maslov, Vladimir I. Yudson, Cristian D. Batista

We investigate resistive anomalies in metals near ferromagnetic phase transitions, focusing on the role of long-range critical fluctuations. Our analysis reveals that diffusive motion of electrons near the critical temperature ($T_c$) enhances a singular behavior of the resistivity near $T_c$ through a classical memory effect, surpassing the prediction by Fi

Pulak Ranjan Giri

Quantum walk has been successfully used to search for targets on graphs with vertices identified as the elements of a database. This spacial search on a two-dimensional periodic grid takes $\mathcal{O}\left(\sqrt{N\log N}\right)$ oracle consultations to find a target vertex from $N$ number of vertices with $\mathcal{O}(1)$ success probability, while reaching

Aidan Gao, Junhong Lin

Spatial clustering is a crucial field, finding universal use across criminology, pathology, and urban planning. However, most spatial clustering algorithms cannot pull information from nearby nodes and suffer performance drops when dealing with higher dimensionality and large datasets, making them suboptimal for large-scale and high-dimensional clustering. D

Jiarui Xia, Song Shu, Xiaogang Li

Based on chiral soliton models, the quantum fluctuation energies of quarks over a spatially inhomogeneous meson field background have been thoroughly studied. We have used a systematic calculation scheme initiated by Schwinger, in which the loop quantum fluctuation energies are evaluated by a nontrivial level summation over the eigenvalue spectrum of the eff

Dongchi Huang, Tianle Zhang, Yihang Li, Ling Zhao

Dexterous grasping in the real world presents a fundamental and significant challenge for robot learning. The ability to employ affordance-aware poses to grasp objects with diverse geometries and properties in arbitrary scenarios is essential for general-purpose robots. However, existing research predominantly addresses dexterous grasping problems within sim

Jiyue Jiang, Pengan Chen, Jiuming Wang, Dongchen He

Large language models (LLMs) have become important tools in solving biological problems, offering improvements in accuracy and adaptability over conventional methods. Several benchmarks have been proposed to evaluate the performance of these LLMs. However, current benchmarks can hardly evaluate the performance of these models across diverse tasks effectively

Hyeon-Woo Jeong, Sang-Sung Lee, Sincheol Kang, Minchul Kam

This study investigates polarimetric characteristics of the blazar 3C~454.3 at 22-129~GHz using decadal~(2011-2022) data sets. In addition, we also delve into the origin of the polarization flare observed in 2019. The data sets were obtained from the single-dish mode observations of the Korean VLBI Network~(KVN) and the 43-GHz Very Long Baseline Array~(VLBA)

Wei Wang, Jiashi Chen, Pengfu Tian, Luis C. Ho

Relativistic jets from accreting black holes (BHs) radiate non-thermal emission which is highly variable in different time scales. Magnetic fields anchored to a rotating BH or accretion disc accelerate and collimate jets of the BH systems. Previous studies on black holes of different mass scales, including supermassive and stellar-mass black holes, only repo

Aleksandrs Slivkins, Yunzong Xu, Shiliang Zuo

We study the greedy (exploitation-only) algorithm in bandit problems with a known reward structure. We allow arbitrary finite reward structures, while prior work focused on a few specific ones. We fully characterize when the greedy algorithm asymptotically succeeds or fails, in the sense of sublinear vs. linear regret as a function of time. Our characterizat

M. Marelli, L. Sidoli, M. Polletta, A. De Luca

Supergiant Fast X-ray Transients (SFXT) are a sub-class of High Mass X-ray Binaries (HMXB) in which a compact object accretes part of the clumpy wind of the blue supergiant companion, triggering a series of brief, X-ray flares lasting a few kiloseconds. Currently, only about fifteen SFXTs are known. The EXTraS catalog provides the timing signatures of every

Mary Shaw, Daniel V. Klein, Theodore L. Ross

The mid-1990s saw the design of programming languages for software architectures, which define the high-level aspects of software systems including how code components were composed to form full systems. Our paper "Abstractions for Software Architecture and Tools to Support Them" presented a conceptual view of software architecture based on abstractions used

Burak Aksoy, John Wen

Manipulating a deformable linear object (DLO) such as wire, cable, and rope is a common yet challenging task due to their high degrees of freedom and complex deformation behaviors, especially in an environment with obstacles. Existing local control methods are efficient but prone to failure in complex scenarios, while precise global planners are computationa

Amin Karimi, Charalambos Poullis

Few-shot semantic segmentation (FSS) aims to enable models to segment novel/unseen object classes using only a limited number of labeled examples. However, current FSS methods frequently struggle with generalization due to incomplete and biased feature representations, especially when support images do not capture the full appearance variability of the targe

Farid Rajkotia-Zaheer, David Goluskin

Bounds on turbulent averages in shear flows can be derived from the Navier--Stokes equations by a mathematical approach called the background method. Bounds that are optimal within this method can be computed at each Reynolds number Re by numerically optimizing subject to a spectral constraint, which requires a quadratic integral to be nonnegative for all po

Brian A. Freno, Neil R. Matula, Robert A. Pfeiffer, Vinh Q. Dang

Electromagnetic slot models are employed to efficiently simulate electromagnetic penetration through openings in an otherwise closed electromagnetic scatterer. Such models, which incorporate varying assumptions about the geometry of the openings, are typically coupled with electromagnetic surface integral equations that model electromagnetic scattering. In t

Luan M. T. de Moraes, Antônio M. S. Macedo, Raydonal Ospina, Giovani L. Vasconcelos

We introduce matrix H theory, a framework for analyzing collective behavior arising from multivariate stochastic processes with hierarchical structure. The theory models the joint distribution of the multiple variables (the measured signal) as a compound of a large-scale multivariate distribution with the distribution of a slowly fluctuating background. The

Moshood Fakorede, Umar Farooq

Despite over 3.5 million Android apps and 200+ million Android Auto-compatible vehicles, only a few hundred apps support Android Auto due to platform-specific compliance requirements. Android Auto mandates service-based architectures in which the vehicle system invokes app callbacks to render the UI and handle interactions, which is fundamentally different f

Md Nizam Uddin, Yihe Zhang, Xiali Hei

The pervasive nature of software vulnerabilities has emerged as a primary factor for the surge in cyberattacks. Traditional vulnerability detection methods, including rule-based, signature-based, manual review, static, and dynamic analysis, often exhibit limitations when encountering increasingly complex systems and a fast-evolving attack landscape. Deep lea

Hsiang-Shang Ko, Shin-Cheng Mu, Jeremy Gibbons

We reconstruct some of the development in Richard Bird's [2008] paper Zippy Tabulations of Recursive Functions, using dependent types and string diagrams rather than mere simple types. This paper serves as an intuitive introduction to and demonstration of these concepts for the curious functional programmer, who ideally already has some exposure to dependent

Munehito Shoda, Riouhei Nakatani, Shinsuke Takasao

Photoevaporation caused by X-rays and ultraviolet radiation from the central star has attracted attention as a key process driving the dispersal of protoplanetary discs. Although numerous models have been used to investigate the photoevaporation process, their conclusions vary, partly due to differences in the adopted radiation spectra of the host star in pa

Houria Triki, Vladimir I. Kruglov

We discover three novel classes of pulse-train waveforms in an optical Kerr nonlinear medium possessing all orders of dispersion up to the fourth order. We show that both single- and double humped pulse-trains can be formed in the nonlinear medium. A distinguishing property is that these structures have different amplitudes, widths and wavenumbers but equal

Jeon Ho Kang, Sagar Joshi, Ruopeng Huang, Satyandra K. Gupta

The growing adoption of batteries in the electric vehicle industry and various consumer products has created an urgent need for effective recycling solutions. These products often contain a mix of compliant and rigid components, making robotic disassembly a critical step toward achieving scalable recycling processes. Diffusion policy has emerged as a promisi

Chenhui Kou, Yuhui Yin, Min Zhu, Shengkun Jia

The design of fluid channel structures of reactors or separators of chemical processes is key to enhancing the mass transfer processes inside the devices. However, the systematic design of channel topological structures is difficult for complex turbulent flows. Here, we address this challenge by developing a machine learning framework to efficiently perform

Sungwon Kim, Yoonho Lee, Yunhak Oh, Namkyeong Lee

Federated Learning (FL) on graphs enables collaborative model training to enhance performance without compromising the privacy of each client. However, existing methods often overlook the mutable nature of graph data, which frequently introduces new nodes and leads to shifts in label distribution. Since they focus solely on performing well on each client's l

Seongjae Han, Chol Park

Let $p$ be an odd prime, and $\mathbf{Q}_{p^f}$ the unramified extension of $\mathbf{Q}_p$ of degree $f$. In this paper, we reduce the problem of constructing strongly divisible modules for $2$-dimensional semi-stable non-crystalline representations of $\mathrm{Gal}(\overline{\mathbf{Q}}_p/\mathbf{Q}_{p^f})$ with Hodge--Tate weights in the Fontaine--Laffaill

Thomas Kroll, Margaret Doyle, Aliaksei Halavanau, Thomas M. Linker

We report the successful resolution of the multiplet structure of the K{\alpha}1 x-ray emission in manganese (Mn) complexes through seeded stimulated X-ray emission spectroscopy (seeded S-XES). By employing a femtosecond pump pulse above the Mn K edge to generate simultaneous 1s core-holes, and a second-color tunable seed pulse to initiate the stimulated emi

Pablo C. Lopez-Custodio, Yuhe Gong, Luis F. C. Figueredo

Modern robotics applications require an inverse kinematics (IK) solver that is fast, robust and consistent, and that provides all possible solutions. Currently, the Franka robot arm is the most widely used manipulator in robotics research. With 7 DOFs, the IK of this robot is not only complex due to its 1-DOF redundancy, but also due to the link offsets at t

Ulisse Iotti

This paper investigates the extendability of local solutions for incompressible 3D Navier-Stokes and 3D Euler problems, with initial data $\mathbf{u}_0$ in the Sobolev space $H^s (\mathbb{R}^3)$, where $s$ ensures the existence and uniqueness of classical solutions. A geometric decomposition of the configuration space, identified by the orthogonality between

Jiarong Wu, Pavel Perezhogin, David John Gagne, Brandon Reichl

Accurately quantifying air-sea fluxes is important for understanding air-sea interactions and improving coupled weather and climate systems. This study introduces a probabilistic framework to represent the highly variable nature of air-sea fluxes, which is missing in deterministic bulk algorithms. Assuming Gaussian distributions conditioned on the input vari

Xiangxin Zhou, Yi Xiao, Haowei Lin, Xinheng He

The dynamic nature of proteins, influenced by ligand interactions, is essential for comprehending protein function and progressing drug discovery. Traditional structure-based drug design (SBDD) approaches typically target binding sites with rigid structures, limiting their practical application in drug development. While molecular dynamics simulation can the

Kashumi Madampe, John Grundy, Nalin Arachchilage

With generative AI becoming widespread, the existence of AI-based programming assistants for developers is no surprise. Developers increasingly use them for their work, including generating code to fulfil the data protection requirements (privacy) of the apps they build. We wanted to know if the reality is the same as expectations of AI-based programming ass

Mike Van Ness, Madeleine Udell

Additive models offer accurate and interpretable predictions for tabular data, a critical tool for statistical modeling. Recent advances in Neural Additive Models (NAMs) allow these models to handle complex machine learning tasks, including feature selection and survival analysis, on large-scale data. This paper introduces dnamite, a Python package that impl

Wenhui Zhu, Xin Li, Xiwen Chen, Peijie Qiu

Recently, Multimodal Large Language Models (MLLMs) have gained significant attention for their remarkable ability to process and analyze non-textual data, such as images, videos, and audio. Notably, several adaptations of general-domain MLLMs to the medical field have been explored, including LLaVA-Med. However, these medical adaptations remain insufficientl

Sourabh Medapati, Priya Kasimbeg, Shankar Krishnan, Naman Agarwal

If we want to train a neural network using any of the most popular optimization algorithms, we are immediately faced with a dilemma: how to set the various optimization and regularization hyperparameters? When computational resources are abundant, there are a variety of methods for finding good hyperparameter settings, but when resources are limited the only

Alina Ostafe, Carl Pomerance, Igor E. Shparlinski

We show that only a rather small proportion of linear equations are solvable in elements of a fixed finitely generated subgroup of a multiplicative group of a number field. The argument is based on modular techniques combined with a classical idea of P. Erd\H{o}s (1935). We then use similar ideas to get a tight upper bound on the number of linear recurrence

Qianzhong Chen, Jiankai Sun, Naixiang Gao, JunEn Low

Autonomous visual navigation is an essential element in robot autonomy. Reinforcement learning (RL) offers a promising policy training paradigm. However existing RL methods suffer from high sample complexity, poor sim-to-real transfer, and limited runtime adaptability to navigation scenarios not seen during training. These problems are particularly challengi

Sreyan Ghosh, Zhifeng Kong, Sonal Kumar, S Sakshi

Understanding and reasoning over non-speech sounds and music are crucial for both humans and AI agents to interact effectively with their environments. In this paper, we introduce Audio Flamingo 2 (AF2), an Audio-Language Model (ALM) with advanced audio understanding and reasoning capabilities. AF2 leverages (i) a custom CLAP model, (ii) synthetic Audio QA d

Yu. Yu. Dubenskaya, A. P. Kryukov, E. O. Gres, S. P. Polyakov

Modern Imaging Atmospheric Cherenkov Telescopes (IACTs) generate a huge amount of data that must be classified automatically, ideally in real time. Currently, machine learning-based solutions are increasingly being used to solve classification problems. However, these classifiers require proper training data sets to work correctly. The problem with training

Zehan Wu, Dehua Wen

In view of the great uncertainty of the equation of state (EOS) of high-density nuclear matter, establishing EOS-independent universal relations between global properties of neutron stars provides a practical way to constrain the unobservable or difficult-to-observe properties through astronomical observations. It is common to construct universal relations b

Manon Revel, Théophile Pénigaud

This article unpacks the design choices behind longstanding and newly proposed computational frameworks aimed at finding common grounds across collective preferences and examines their potential future impacts, both technically and normatively. It begins by situating AI-assisted preference elicitation within the historical role of opinion polls, emphasizing

Zongqian Li, Ehsan Shareghi, Nigel Collier

Large Language Models (LLMs) reasoning processes are challenging to analyze due to their complexity and the lack of organized visualization tools. We present ReasonGraph, a web-based platform for visualizing and analyzing LLM reasoning processes. It supports both sequential and tree-based reasoning methods while integrating with major LLM providers and over

Lisa Pilgram, Fida K. Dankar, Jorg Drechsler, Mark Elliot

Synthetic data generation is one approach for sharing individual-level data. However, to meet legislative requirements, it is necessary to demonstrate that the individuals' privacy is adequately protected. There is no consolidated standard for measuring privacy in synthetic data. Through an expert panel and consensus process, we developed a framework for

Mohamed A. Shalby, Renyu Wang, Denis Sedov, Leonid P. Pryadko

Connecting two surface-code patches may require significantly higher noise at the interface. We show, via circuit-level simulations under a depolarizing noise model with idle errors, that surface codes remain fault tolerant despite substantially elevated interface error rates. Specifically, we compare three strategies -- direct noisy links, gate teleportatio

Marco Bianchetti, Gabriele D'Acunto, Gianmarco De Francisci Morales, Yuko Kuroki

We investigate portfolio optimization in financial markets from a trading and risk management perspective. We term this task Risk-Aware Trading Portfolio Optimization (RATPO), formulate the corresponding optimization problem, and propose an efficient Risk-Aware Trading Swarm (RATS) algorithm to solve it. The key elements of RATPO are a generic initial portfo

Navid Keshtiarast, Pradyumna Kumar Bishoyi, Ido Manuel Lumbantobing, Marina Petrova

Sensing is emerging as a vital future service in next-generation wireless networks, enabling applications such as object localization and activity recognition. The IEEE 802.11bf standard extends Wi-Fi capabilities to incorporate these sensing functionalities. However, coexistence with legacy Wi-Fi in densely populated networks poses challenges, as contention

Erik Kalz, Shashank Ravichandir, Johannes Birkenmeier, Ralf Metzler

Chiral fluids are defined by broken mirror or time-reversal symmetry, giving rise to tensorial transport coefficients with antisymmetric components. A key example is the odd mobility tensor, which governs the response of a chiral tracer to an applied force and induces a characteristic transverse drift. While this response is well understood in the infinite d

Shinichi Nishihaya, Hiroaki Ishizuka, Yuki Deguchi, Ayano Nakamura

Intrinsic anomalous Hall effect (AHE) formulated by geometric properties of Bloch wavefunctions is a ubiquitous transport phenomenon not limited to magnetic systems but also allowed in non-magnetic ones under an external field breaking time-reversal symmetry. On the other hand, detection of field-induced AHE is practically challenging because the band modula

Fengchen Gu, Zhengyong Jiang, Ángel F. García-Fernández, Angelos Stefanidis

Portfolio management remains a crucial challenge in finance, with traditional methods often falling short in complex and volatile market environments. While deep reinforcement approaches have shown promise, they still face limitations in dynamic risk management, exploitation of temporal markets, and incorporation of complex trading strategies such as short-s

Kaixiao Fang, Zhongxiao Jia

The joint bidiagonalization (JBD) process of a regular matrix pair $\{A,L\}$ is mathematically equivalent to two simultaneous Lanczos bidiagonalization processes of the upper and lower parts of the Q-factor of QR factorization of the stacked matrix $(A^{\mathrm T},\,L^{\mathrm T})^{\mathrm T}$ when their starting vectors are closely related in a specific way

Ehsan Ahmadi, Ray Mercurius, Soheil Alizadeh, Kasra Rezaee

Trajectory prediction models in autonomous driving are vulnerable to perturbations from non-causal agents whose actions should not affect the ego-agent's behavior. Such perturbations can lead to incorrect predictions of other agents' trajectories, potentially compromising the safety and efficiency of the ego-vehicle's decision-making process. Mot

Samuel A. Lopes, Héctor Suárez, Yésica Suárez

In this paper we study the properties Koszul, Artin-Schelter regular and (skew) Calabi-Yau of some special types of quantum and generalized Heisenberg algebras and also analyze relations between these algebras, (graded) iterated Ore extensions and (graded) skew PBW extensions. The first-named author and Razavinia introduced the quantum generalized Heisenberg

Abdolvahhab Rostamijavanani, Shanwu Li, Yongchao Yang

While linear systems have been useful in solving problems across different fields, the need for improved performance and efficiency has prompted them to operate in nonlinear modes. As a result, nonlinear models are now essential for the design and control of these systems. However, identifying a nonlinear system is more complicated than identifying a linear

Leonidas Daskalakis

For every $c\in(1,23/22)$ and every probability dynamical system $(X,\mathcal{B},\mu,T)$ we prove that for any $f,g\in L^{\infty}_{\mu}(X)$ the bilinear ergodic averages \[ \frac{1}{N}\sum_{n=1}^Nf(T^{\lfloor n^c\rfloor}x)g(T^{-\lfloor n^c\rfloor}x)\quad\text{converge for $\mu$-a.e. $x\in X$.} \] In fact, we consider more general sparse orbits $(\lfloor h(n)

Harikumar K. Chandrasekharan, Ross Donaldson

Monitoring polarization dynamics in multimode fibers is critical for a range of applications, spanning from optical communication to sensing. Although the modal behavior of multimode fibers is well understood through interferometry and advanced detection techniques, most studies focus on a single polarization state of specific modes, leaving the spatial mode

Andrés Fábrega, Jack Cable, Michael A. Specter, Sunoo Park

Voter registration systems are a critical - and surprisingly understudied - element of most high-stakes elections. Despite a history of targeting by adversaries, relatively little academic work has been done to increase visibility into how voter registration systems keep voters' data secure, accurate, and up to date. Enhancing transparency and verifiability

Yixiao Ge, Arthur Pearce, Pieter van Goor, Robert Mahony

Range-only Simultaneous Localisation and Mapping (RO-SLAM) is of interest due to its practical applications in ultra-wideband (UWB) and Bluetooth Low Energy (BLE) localisation in terrestrial and aerial applications and acoustic beacon localisation in submarine applications. In this work, we consider a mobile robot equipped with an inertial measurement unit (

Mahmoud AlaaEldin, Mohammad Al-Jarrah, Xidong Mu, Emad Alsusa

Non-orthogonal multiple access (NOMA) is widely recognized for enhancing the energy and spectral efficiency through effective radio resource sharing. However, uplink NOMA systems face greater challenges than their downlink counterparts, as their bit error rate (BER) performance is hindered by an inherent error floor due to error propagation caused by imperfe

Fanwen Wang, Zi Wang, Yan Li, Jun Lyu

Cardiovascular health is vital to human well-being, and cardiac magnetic resonance (CMR) imaging is considered the {clinical reference standard} for diagnosing cardiovascular disease. However, its adoption is hindered by long scan times, complex contrasts, and inconsistent quality. While deep learning methods perform well on specific CMR imaging {sequences},

Eran Ben Arosh, Eldar Ragonis, Lev Merensky, Avner Fleischer

Chiral (highly helical) extreme ultraviolet (XUV) sources are pivotal for investigating chiroptical phenomena on the ultrafast electronic timescale. Table-top, coherent High Harmonic Generation (HHG)-based sources are particularly well-suited for these studies. However, chiral materials, such as organic chiral molecules and solid-state magnetic materials, ex

Likith Kadiyala, Ramteja Sajja, Yusuf Sermet, Ibrahim Demir

This research investigates the integration of emotional diversity into Large Language Models (LLMs) to enhance collective intelligence. Inspired by the human wisdom of crowds phenomenon, where group decisions often outperform individual judgments, we fine-tuned the DarkIdol-Llama-3.1-8B model using Google's GoEmotions dataset and Low-Rank Adaptation (LoRA) t