October 2025 arXiv papers — page 52

Chenjian Wang

For integers $k\geq 3,d\geq 2,$ we consider the abundance property of pinned $k$-point patterns occurring in $E\subseteq \mathbb R^d$ with positive upper density $\delta(E)$. We show that for any fixed $k$-point pattern $V$, there is a set $E$ with positive upper density such that $E$ avoids all sufficiently large affine copies of $V$, with one vertex fixed

Yijia Fan, Jusheng Zhang, Jing Yang, Keze Wang

To combat the prohibitive communication costs of ``free-for-all" multi-agent systems (MAS), we introduce \textbf{Agent-GSPO}, a framework that directly optimizes for token economy using sequence-level reinforcement learning. Agent-GSPO leverages the stable and memory-efficient Group Sequence Policy Optimization (GSPO) algorithm to train agents on a communica

Denis Auroux

We survey various aspects of Floer theory and its place in modern symplectic geometry, from its introduction to address classical conjectures of Arnold about Hamiltonian diffeomorphisms and Lagrangian submanifolds, to the rich algebraic structures captured by the Fukaya category, and finally to the idea, motivated by mirror symmetry, of a "geometry of Floer

Saklain Niam, Tashfiqur Rahman, Md. Amjad Patwary, Mukarram Hossain

Cold plasma (CP) is an eco-friendly method to enhance seed germination, yet outcomes remain difficult to predict due to complex seed--plasma--environment interactions. This study introduces the first machine learning framework to forecast germination uplift in soybean, barley, sunflower, radish, and tomato under dielectric barrier discharge (DBD) plasma. Amo

Xiangjue Dong, Cong Wang, Maria Teleki, Millennium Bismay

Persona-assigned Large Language Models (LLMs) can adopt diverse roles, enabling personalized and context-aware reasoning. However, even minor demographic perturbations in personas, such as simple pronoun changes, can alter reasoning trajectories, leading to divergent sets of correct answers. Instead of treating these variations as biases to be mitigated, we

Samarth Das, Yong Yang

Suppose that $G$ is a finite solvable group and let $H$ be a Hall $\pi$-subgroup, let $b(H)$ be the largest character degree of $H$, we show that $|G:O_{\pi' \pi}(G)|_{\pi} \leq b(H)^2$.

Jing Yang, Yufeng Yang

Recent advancements in 2D and 3D generative models have expanded the capabilities of computer vision. However, generating high-quality 4D dynamic content from a single static image remains a significant challenge. Traditional methods have limitations in modeling temporal dependencies and accurately capturing dynamic geometry changes, especially when consider

Yohei Kono, Yoshiyuki Tajima

Extracting pulsive temporal patterns from a small dataset without their repetition or singularity shows significant importance in manufacturing applications but does not sufficiently attract scientific attention. We propose to quantify how long temporal patterns appear without relying on their repetition or singularity, enabling to extract such temporal patt

Nivasini Ananthakrishnan, Yuval Dagan, Kunhe Yang

Motivated by the question of how a principal can maximize its utility in repeated interactions with a learning agent, we study repeated games between an principal and an agent employing a mean-based learning algorithm. Prior work has shown that computing or even approximating the global Stackelberg value in similar settings can require an exponential number

Haotian Hang, Yueyang Shen, Vicky Zhu, Jose Cruz

In the context of global sustainability mandates, corporate carbon disclosure has emerged as a critical mechanism for aligning business strategy with environmental responsibility. The Carbon Disclosure Project (CDP) hosts the world's largest longitudinal dataset of climate-related survey responses, combining structured indicators with open-ended narratives,

Jiawei Chen, Maochao Xiao, Ziyu Zhou, Yufei Zhang

This study investigates the aerodynamic performance and flow structures of infinite swept wings with artificially simulated discontinuous ice using an enhanced delayed detached-eddy simulation. Comparisons are made among clean, continuous-ice, and discontinuous-ice configurations. Results show that discontinuous ice causes a more severe reduction in lift tha

Hamza Patwa, Philip Kurian

Collective emission of light from distributions of two-level systems (TLSs) was first predicted in 1954 by Robert Dicke, who showed that when $N$ quantum emitters absorb photons, their collective radiative decay rate can be enhanced (superradiance) or suppressed (subradiance) relative to a single emitter. In this work, we derive novel analytical expressions

Jing Yang, Kaitong Cai, Yijia Fan, Yufeng Yang

Full fine-tuning of Large Language Models (LLMs) is notoriously memory-intensive, primarily because conventional optimizers such as SGD or Adam assume access to exact gradients derived from cached activations. Existing solutions either alter the model architecture (e.g., reversible networks) or trade memory for computation (e.g., activation checkpointing), b

Ebtsam H. Taha

Generalized $m$-Kropina metrics appear naturally as a spacetime geometry compatible with Lorentz symmetry breaking, leading to useful applications in modified gravity and cosmology. We prove that a generalized $m$-Kropina metric $F$ is an almost rational Finsler metric. Thereby, we study the rationality of its Finslerian geometric objects in the directional

Sourabh Karmakar, Cameron J. Turner

This paper presents a method to generate feasible, unique forward-kinematic solutions for a general Stewart platform. This is done by using inverse kinematics to obtain valid workspace data and corresponding actuator lengths for the moving platform. For parallel kinematic machines, such as the Stewart Platform, inverse kinematics are straight forward, but th

Anik Burman, Elizabeth L. Ogburn, Abhirup Datta

Estimating effects of spatially structured exposures is complicated by unmeasured spatial confounders, which undermine identifiability in spatial linear regression models unless structural assumptions are imposed. We develop a general framework for effect estimation in spatial regression models that relaxes the commonly assumed requirement that exposures con

Abhijnan Nath, Nikhil Krishnaswamy

Large Language Models (LLMs) are increasingly being deployed in agentic settings where they act as collaborators with humans. Therefore, it is increasingly important to be able to evaluate their abilities to collaborate effectively in multi-turn, multi-party tasks. In this paper, we build on the AI alignment and safe interruptibility literature to offer nove

Yudai Matsumura, Hiroki Kishikawa, Naoya Kuse, Yasuhiro Okamura Eiji Hase

We demonstrate an all-photonic terahertz receiver for a data-modulated signal, targeting a 106-GHz, 2.97-Gb/s OOK link. The scheme employs dual-wavelength optical carriers referenced to a soliton microcomb and performs THz-to-optical carrier conversion via nonpolarimetric electro-optic downconversion using an electro-optic polymer modulator. RF spectra and e

A. Soleiman, Ebtsam H. Taha

We explore a generalization of Matsumoto metric intrinsically. Given a Finsler manifold $(M,F)$ which admits a concurrent $π$-vector field $\overlineφ$, we consider the change $\widehat{F}(x,y)=\frac {F^2 (x,y)} {F(x,y)-Φ(x,y)}$, where $Φ$ is the associated concurrent $π$-form with $F(x,y) > Φ(x,y)$ for all $(x,y) \in \T M$. We find the condition under which

Josue Abreu, Paul Bergeron, Sandhya Aneja

In this research, we investigate the feasibility of adopting the Bottleneck Bandwidth and Round-trip propagation time (BBR) protocol as the default congestion control mechanism for TCP. Our central question is whether BBR, particularly its latest iterations, BBRv2 and BBRv3, can outperform traditional TCP variants such as Reno and Cubic across diverse networ

Shuichiro Takeda, Justin Trias

The MVW involution -- named after Colette Moeglin, Marie-France Vign\'eras, and Jean-Loup Waldspurger -- is a fundamental dualizing involution in the representation theory of $p$-adic classical groups. It extends the well-known transpose-inverse automorphism for general linear groups. In this work, we establish the existence of the MVW involution for the met

Eugene V. Sukhorukov, Adrien Tomà

We develop a unified perturbative framework for energy transport along a chiral quantum Hall edge coupled to a disordered, compressible strip. Treating the strip as a generic linear response environment characterized by its retarded susceptibility, we obtain leading corrections to both the heat flux carried by the edge plasmon and to its spectrum. Two generi

Sen Na

We consider solving nonlinear optimization problems with a stochastic objective and deterministic equality constraints, assuming that only zero-order information is available for both the objective and constraints, and that the objective is also subject to random sampling noise. Under this setting, we propose a Derivative-Free Stochastic Sequential Quadratic

Fuqiang Liu, Weiping Ding, Luis Miranda-Moreno, Lijun Sun

Deep neural networks (DNNs) play a significant role in an increasing body of research on traffic forecasting due to their effectively capturing spatiotemporal patterns embedded in traffic data. A general assumption of training the said forecasting models via mean squared error estimation is that the errors across time steps and spatial positions are uncorrel

Shalini Chakraborty, Sebastian Baltes

Conversations around diversity and inclusion in software engineering often focus on gender and racial disparities. However, the State of Devs 2025 survey with 8,717 participants revealed that other forms of discrimination are similarly prevalent but receive considerably less attention. This includes discrimination based on age, political perspective, disabil

Adrita Anika, Md Messal Monem Miah

Reasoning over procedural sequences, where the order of steps directly impacts outcomes, is a critical capability for large language models (LLMs). In this work, we study the task of reconstructing globally ordered sequences from shuffled procedural steps, using a curated dataset of food recipes, a domain where correct sequencing is essential for task succes

Oleh Savchuk

Collisions of protons with lead nuclei (pPb), such as those measured by the LHCb experiment, provide a unique environment to study the surprising emergence of collective, fluid-like phenomena in small systems. A key signature of this hydrodynamic behavior is the predicted formation of a toroidal vorticity structure. In this work, I use two-particle femtoscop

Anahita Eslami-Rad, Jean-Pierre Magnot, Enrique G. Reyes

We consider the class of profinite diffeological spaces, that is, diffeological spaces which diffeologies are deduced by pull-back of diffeologies on finite-dimensional manifolds through a system of projection mappings. This class includes inductive limits of finite-dimensional manifolds, as well as solution spaces of differential relations and spaces that a

Brandon James Carone, Iran R. Roman, Pablo Ripollés

Multimodal Large Language Models (LLMs) claim "musical understanding" via evaluations that conflate listening with score reading. We benchmark three SOTA LLMs (Gemini 2.5 Pro, Gemini 2.5 Flash, and Qwen2.5-Omni) across three core music skills: Syncopation Scoring, Transposition Detection, and Chord Quality Identification. Moreover, we separate three sources

Linhan Wang, Jianwen Dou, Wang Li, Shengkun Wang

Cryogenic Electron Tomography (CryoET) combined with sub-volume averaging (SVA) is the only imaging modality capable of resolving protein structures inside cells at molecular resolution. Particle picking, the task of localizing and classifying target proteins in 3D CryoET volumes, remains the main bottleneck. Due to the reliance on time-consuming manual labe

D. Ł. Król, G. Fabbiano, M. Elvis, A. Trindade Falcão

We present a detailed analysis of the X-ray emission of the Compton-thick (CT) AGN ESO\,137-G034 based on deep ($\sim230$\,ks) Chandra observations. As in other CT AGNs, the morphology of the emission is elongated, approximately following the [O III] ionization bicone. With spatially resolved spectral modeling, we show that the extended emission within the b

Siddharth Vishwanath, Ery Arias-Castro

We develop a formal statistical framework for classical multidimensional scaling (CMDS) applied to noisy dissimilarity data. We establish distributional convergence results for the embeddings produced by CMDS for various noise models, which enable the construction of \emph{bona~fide} uniform confidence sets for the latent configuration, up to rigid transform

Eugen J. Ionascu

We derive integral inequalities governing drainage time in convex solids, inspired by Torricelli's Law, and introduce the Torricelli number as a shape invariant. We use these considerations to construct a class of solids that can be used in building asymmetrical clepsydrae.

Xingbo Fu, Zhenyu Lei, Zihan Chen, Binchi Zhang

Graph Neural Networks (GNNs) have revolutionized the field of graph learning by learning expressive graph representations from massive graph data. As a common pattern to train powerful GNNs, the "pre-training, adaptation" scheme first pre-trains GNNs over unlabeled graph data and subsequently adapts them to specific downstream tasks. In the adaptation phase,

Francesco Giovanni Celiberto, Francesca Lonigro

We present recent progress on the Heavy-Flavor Non-Relativistic Evolution (HF-NRevo) framework, designed to describe leading-power fragmentation of heavy-flavored hadrons at moderate to large transverse momentum. Starting from NLO NRQCD calculations for all partonic channels into pseudoscalar quarkonia, we construct the NRFF1.0 collinear fragmentation functi

Pranup Chhetri, Alejandro Torrejon, Sergio Eslava, Luis J. Manso

Social Robot Navigation is the skill that allows robots to move efficiently in human-populated environments while ensuring safety, comfort, and trust. Unlike other areas of research, the scientific community has not yet achieved an agreement on how Social Robot Navigation should be benchmarked. This is notably important, as the lack of a de facto standard to

D. Ł. Król, G. Fabbiano, M. Elvis, A. Trindade Falcão

We present a detailed, spatially resolved { Veilleux \& Osterbrock (VO) diagram} analysis of ESO\,137-G034, a Compton-thick Active Galactic Nucleus (AGN), based on narrowband {\it HST} imaging in [O~III], [S~II], H$\alpha$, and H$\beta$ emission lines. The narrowband optical emission exhibits a bi-conical morphology and traces the diffuse X-ray emission obse

Toshihiro Shirakawa

This paper reports the results of numerical computations for determining the number of polyominoes of size n (n-ominoes). We verify the existing counts for n <= 50 and newly compute the total number of polyominoes up to n <= 59, extending the counting limit. This work shows that, in addition to optimizing the search algorithm for the polyomino counting probl

Francesco Giovanni Celiberto, Luigi Delle Rose, Alessandro Papa

We present updated predictions for rapidity and transverse-momentum spectra in Higgs-plus-jet production at proton colliders, combining NLO fixed-order QCD with next-to-leading energy-logarithmic resummation. Preliminary results for the $Z$-boson case are also discussed. Our study underscores the importance of improving fixed-order predictions for Higgs- and

Sinan Bugu

Quantumgametheoryextendsclassical strategic decision-making by incorporating quantum superposition, entanglement, and measurement-induced randomness into competitive interactions. This paper introduces a team-based Quantum Sabotage Game (QSG), in which classical and quantum-enhanced teams engage in adversarial decision-making under identical information cons

Vijay Veerabadran, Fanyi Xiao, Nitin Kamra, Pedro Matias

There has been a surge of interest in assistive wearable agents: agents embodied in wearable form factors (e.g., smart glasses) who take assistive actions toward a user's goal/query (e.g. "Where did I leave my keys?"). In this work, we consider the important complementary problem of inferring that goal from multi-modal contextual observations. Solving this "

J. R. Rojano-Cáceres, A. Rivera-Hernández

The present work reports the development of an application called Signa App, which was designed following the philosophy of User-Centered De-sign. Signa App aims to provide a mobile platform for editing and creating texts in SignWriting notation. The proposal was based on the lack of a mo-bile application that is usable for Deaf individuals who use sign lang

Thomas Allard

We study how large an $\ell^2$ ellipsoid is by introducing type-$\tau$ integrals that capture the average decay of its semi-axes. These integrals turn out to be closely related to standard complexity measures: we show that the metric entropy of the ellipsoid is asymptotically equivalent to the type-1 integral, and that the minimax risk in non-parametric esti

Sanjoy Dasgupta, Syamantak Kumar, Shourya Pandey, Purnamrita Sarkar

Low-precision streaming PCA estimates the top principal component in a streaming setting under limited precision. We establish an information-theoretic lower bound on the quantization resolution required to achieve a target accuracy for the leading eigenvector. We study Oja's algorithm for streaming PCA under linear and nonlinear stochastic quantization. The

Ali Vosoughi, Yongyi Zang, Qihui Yang, Nathan Paek

Room impulse response (RIR) generation remains a critical challenge for creating immersive virtual acoustic environments. Current methods suffer from two fundamental limitations: the scarcity of full-band RIR datasets and the inability of existing models to generate acoustically accurate responses from diverse input modalities. We present PromptReverb, a two

Farhad Sotoudeh, Jafar Ghazanfarian

Non-equilibrium molecular dynamics (NEMD) simulations were used to study pool boiling of water films on an ultra-thin planar aluminum substrate as well as the effect of surface wettability. The simulation geometry is a 10 nm-thick water film on an FCC aluminum substrate heated from 300 K to 900 K. The first peak acceleration onset time of the film, as the me

Ghazal Farhani, Taufiq Rahman, Syed Mostaquim Ali, Andrew Liu

Because 3D structure of a roadway environment can be characterized directly by a Light Detection and Ranging (LiDAR) sensors, they can be used to obtain exceptional situational awareness for assitive and autonomous driving systems. Although LiDARs demonstrate good performance in clean and clear weather conditions, their performance significantly deteriorates

Zhenyu Wang, Mira Todorova, Christoph Freysoldt, Jörg Neugebauer

Marcus theory is fundamental to describing electron transfer reactions and quantifying their rates, effectively representing the energy surface associated with an electron transfer from the reactant to the product ionic state via parabolas within a reaction coordinate diagram. Here, we present an intuitive and computationally efficient generalised reaction c

Prajyot Pyati, Navjot Kaur, Saswata Jana, Adri Bhattacharya

We study a recently introduced \textit{unconscious} mobile robot model, where each robot is associated with a \textit{color}, which is visible to other robots but not to itself. The robots are autonomous, anonymous, oblivious and silent, operating in the Euclidean plane under the conventional \textit{Look-Compute-Move} cycle. A primary task in this model is

I. Emizh, A. Guterman

It is proved that the roots of the derivative of a polynomial with quaternionic coefficients belong to the union of the intersections of sets defined in terms of certain projections of a polynomial. The result strengthens the quaternion version of Gauss-Lucas theorem, proved by Ghiloni and Perotti in 2018.

Yurang, Kuang

We develop a fundamental framework for the quantum mechanics of stochastic systems (QMSS), showing that classical discrete stochastic processes emerge naturally as perturbations of the quantum harmonic oscillator (QHO). By constructing exact perturbation potentials that transform QHO eigenstates into stochastic representations, we demonstrate that canonical

Yiran Cheng

We construct Bridgeland stability conditions on the the following hyper-K\"ahler or strict Calabi--Yau manifolds: - Generalized Kummer varieties associated to an abelian surface that is isogenous to a product of elliptic curves. - Universal covers of Hilbert schemes of some Enriques surfaces; this provides examples of stability conditions on strict Calabi--Y

Zheng Wei, Mingchen Li, Zeqian Zhang, Ruibin Yuan

Recent advancements in multi-agent systems have demonstrated significant potential for enhancing creative task performance, such as long video generation. This study introduces three innovations to improve multi-agent collaboration. First, we propose OmniAgent, a hierarchical, graph-based multi-agent framework for long video generation that leverages a film-

Marcin Briański, Alexandra Lassota, Kristýna Pekárková, Michał Pilipczuk

Solving integer programs of the form $\min \{\mathbf{x} \mid A\mathbf{x} = \mathbf{b}, \mathbf{l} \leq \mathbf{x} \leq \mathbf{u}, \mathbf{x} \in \mathbb{Z}^n \}$ is, in general, $\mathsf{NP}$-hard. Hence, great effort has been put into identifying subclasses of integer programs that are solvable in polynomial or $\mathsf{FPT}$ time. A common scheme for many

Md Saiful Islam, Rahul Bhadani

When electric vehicles (EVs) are integrated into standalone DC microgrids (DCMGs), stability issues arise due to their constant power load (CPL) behavior, which provides negative incremental impedance (NII). In addition, the microgrids suffer from an inherent low-inertia problem. Therefore, this study presents a composite controller incorporating a global in

Vincent E. Coll, Jr. abd Lee B. Whitt

We revisit a classical calculus computation: the centroid of the subgraph of a function on the interval from 0 to a, and show that it hides a rigidity theorem. Let f be twice continuously differentiable on (0, infinity), take values in (0, infinity), and satisfy f(0+) = 0. Define xbar(a) as (integral from 0 to a of x f(x) dx) divided by (integral from 0 to a

Marta Dell'Atti

We consider some algebraic and geometric aspects of the theory of integrable systems in finite dimensions, associated with the existence of a classical $r$-matrix, first introduced by Sklyanin as the classical analogue of the quantum version. The importance of the notion of the $r$-matrix in this context relies on the fact that it connects the Hamiltonian st

Volker Burkert, Eberhard Klempt

The properties of the Roper resonance N(1440) are reviewed. Quark models have long struggled to reproduce its mass relative to its negative-parity partner N(1535). This discrepancy motivated interpretations of the Roper as a dynamically generated meson-baryon state. Including its isospin partners Delta(1600) and Delta(1700) further accentuates the tension be

Mouyang Cheng, Qiwei Wan, Bowen Yu, Eunbi Rha

High-temperature superconductors are essential for next-generation energy and quantum technologies, yet their performance is often limited by the critical current density ($J_c$), which is strongly influenced by microstructural defects. Optimizing $J_c$ through defect engineering is challenging due to the complex interplay of defect type, density, and spatia

Princessa Cintaqia, Arshia Arya, Elissa M Redmiles, Deepak Kumar

In order to train, test, and evaluate nudity detection models, machine learning researchers typically rely on nude images scraped from the Internet. Our research finds that this content is collected and, in some cases, subsequently distributed by researchers without consent, leading to potential misuse and exacerbating harm against the subjects depicted. Thi

Ariel Flint, Luca Maria Aiello, Romualdo Pastor-Satorras, Andrea Baronchelli

Multi-agent systems of large language models (LLMs) are rapidly expanding across domains, introducing dynamics not captured by single-agent evaluations. Yet, existing work has mostly contrasted the behavior of a single agent with that of a collective of fixed size, leaving open a central question: how does group size shape dynamics? Here, we move beyond this

Sayantan Choudhury, Nicolas Loizou

Introduced by Korpelevich in 1976, the extragradient method (EG) has become a cornerstone technique for solving min-max optimization, root-finding problems, and variational inequalities (VIs). Despite its longstanding presence and significant attention within the optimization community, most works focusing on understanding its convergence guarantees assume t

Mohammad Ali Labbaf Khaniki, Fateme Taroodi, Benyamin Safizadeh

Controlling high-dimensional stochastic systems, critical in robotics, autonomous vehicles, and hyperchaotic systems, faces the curse of dimensionality, lacks temporal abstraction, and often fails to ensure stochastic stability. To overcome these limitations, this study introduces the Multi-Timescale Lyapunov-Constrained Hierarchical Reinforcement Learning (

Kaihua Chang

Quantile regression is fundamental to distributional modeling, yet independent estimation of multiple quantiles frequently produces crossing -- where estimated quantile functions violate monotonicity, implying impossible negative probability densities. While Constrained Joint Quantile Regression (CJQR) elegantly enforces non-crossing by construction, existin

Andriy Miranskyy

As quantum computing advances toward early fault-tolerant machines, testing and verification of quantum programs become urgent but costly, since each execution consumes scarce hardware resources. Unlike in classical software testing, every measurement must be carefully budgeted. This paper develops a unified framework for reasoning about how many measurement

Laura Train, Rodrigo Castellanos, Miguel Gómez-López

Commercial off-the-shelf (COTS) Global Navigation Satellite System (GNSS) receivers face significant limitations under high-dynamic conditions, particularly in high-acceleration environments such as those experienced by launch vehicles. These performance degradations, often observed as discontinuities in the navigation solution, arise from the inability of t

Zheng Wei, Mingchen Li, Junxiang Liao, Zeyu Yang

We examine discussions surrounding China-U.S. relations on the Chinese and American social media platforms \textit{Douyin} and \textit{TikTok}. Both platforms, owned by \textit{ByteDance}, operate under different regulatory and cultural environments, providing a unique perspective for analyzing China-U.S. public discourse. This study analyzed 4,040 videos an

Mertcan Sevgi, Fares Antaki, Abdullah Zafar Khan, Ariel Yuhan Ong

Vision impairment and blindness are a major global health challenge where gaps in the ophthalmology workforce limit access to specialist care. We evaluate AMIE, a medically fine-tuned conversational system based on Gemini with integrated web search and self-critique reasoning, using real-world clinical vignettes that reflect scenarios a general ophthalmologi

Sourav Das, Anish Ghosh

We survey recent work done on the values at integer points of irrational inhomogeneous quadratic forms, namely, inhomogeneous analogues of the famous Oppenheim conjecture. We also prove that the set of such forms in two variables whose set of values at integer points avoids a given countable set not containing zero, has full Hausdorff dimension. Moreover, we

Arpan Aryam John, Krushna Govind Shete, Shabnam Iyyani, Saptarshi Bej

Fermi Gamma-ray Space Telescope has detected a diverse range of gamma-ray transients since its launch in 2008. Over the years, Fermi has accumulated an extensive public archive of transient events. Traditional classification methods for these events typically rely on fixed thresholds, localisation accuracy, and characteristic light curve features. However, i

Adam Wiechman, John M. Anderies, Margaret Garcia

Our infrastructure systems enable our well-being by allowing us to move, store, and transform materials and information given considerable social and environmental variation. Critically, this ability is shaped by the degree to which society invests in infrastructure, a fundamentally political question in large public systems. There, infrastructure providers

Yiyao Yang, Yasemin Gulbahar

The research introduces a reproducible framework for transforming raw, heterogeneous sensor streams into aligned, semantically meaningful representations for multimodal human activity recognition. Grounded in the Carnegie Mellon University Multi-Modal Activity Database (CMU-MMAC) database and focused on the naturalistic Subject 07 Brownie session, the study

Shahidul Islam, Md Nahidul Islam Opu, Shaowei Wang, Shaiful Chowdhury

Self-admitted technical debt (SATD) refers to comments in which developers explicitly acknowledge code issues, workarounds, or suboptimal solutions. SATD is known to significantly increase software maintenance effort. While extensive research has examined SATD in source code, its presence and impact in test code have received no focused attention, leaving a

Lei Shi, Sizhu Lu, Qiuran Lyu, Peng Ding

Accurately estimating heterogeneous treatment effects (HTE) in longitudinal settings is essential for personalized decision-making across healthcare, public policy, education, and digital marketing. However, time-varying interventions introduce many unique challenges, such as carryover effects, time-varying heterogeneity, and post-treatment bias, which are n

Anargyros Michaloliakos, Benjamin J. Chang, Lawrence A. Bergman, Alexander F. Vakakis

This work presents a purely data-driven, wavelet-based framework for modal identification and reduced-order modeling of mechanical systems with assumed linear dynamics characterized by closely spaced modes with classical or non-classical damping distribution. Traditional Fourier-based methods often fail to reliably identify closely spaced modes or accurately

Yasas Senarath, Hemant Purohit

User behavior on online platforms is evolving, reflecting real-world changes in how people post, whether it's helpful messages or hate speech. Models that learn to capture this content can experience a decrease in performance over time due to data drift, which can lead to ineffective behavioral analytics systems. However, fine-tuning such a model over time w

H. Z. Q. Chen, S. Kitaev, X. Lang, A. Pyatkin

Transforming an input sequence into its constituent k-mers is a fundamental operation in computational genomics. To reduce storage costs associated with k-mer datasets, we introduce and formally analyze MCTR, a novel two-stage algorithm for lossless compression of the k-mer multiset. Our core method achieves a minimal text representation (W) by computing an

Camryn L. Phillips, Michael A. Strauss, Masafusa Onoue, Xuheng Ding

We present an analysis of the rest frame optical JWST NIRSpec Fixed Slit spectra of extended host galaxy emission in 12 quasars from the Subaru High-z Exploration of Low-Luminosity Quasars (SHELLQs) sample at redshifts 6.0 < z < 6.4. The spatial point spread function is modeled primarily by a sum of two Gaussians as a function of wavelength and is used to fi

Rohan Palanikumar, Ahmed A. Elgohary, Simone Martini, Sameh A. Eisa

In this paper, we introduce a model-free, real-time, dynamic optimization and control method for a class of rigid body dynamics. Our method is based on a recent extremum seeking control for vibrational stabilization (ESC-VS) approach that is applicable to a class of second-order mechanical systems. The new ESC-VS method is able to stabilize a rigid body dyna

Chengyuan Deng, Jie Gao, Kevin Lu, Feng Luo

The Johnson-Lindenstrauss (JL) lemma is a cornerstone of dimensionality reduction in Euclidean space, but its applicability to non-Euclidean data has remained limited. This paper extends the JL lemma beyond Euclidean geometry to handle general dissimilarity matrices that are prevalent in real-world applications. We present two complementary approaches: First

Fei Shao, Jia Zou, Zhichao Cao, Xusheng Xiao

Provenance analysis (PA) has recently emerged as an important solution for cyber attack investigation. PA leverages system monitoring to monitor system activities as a series of system audit events and organizes these events as a provenance graph to show the dependencies among system activities, which can reveal steps of cyber attacks. Despite their potentia

Deborah Gefang, Stephen G Hall, George S. Tavlas

We develop a new Bayesian approach to estimating panel spatial autoregressive models with a known number of latent common factors, where N, the number of cross-sectional units, is much larger than T, the number of time periods. Without imposing any a priori structures on the spatial linkages between variables, we let the data speak for themselves. Extensive

Gunindra Krishna Mahanta

Thermodynamic geometry allow us to study the microscopic behavior of black hole system by defining a metric structure in thermodynamic phase space. Among the various thermodynamic metric structures, metrics defined by geometrothermodynamics (GTD) are extensively used to study the various thermodynamic system due to its Legendre invariant nature. In this work

Zhaoyang Li, Zheng Yu, Jingyi Song, Meng Xu

Patch backporting, the process of migrating mainline security patches to older branches, is an essential task in maintaining popular open-source projects (e.g., Linux kernel). However, manual backporting can be labor-intensive, while existing automated methods, which heavily rely on predefined syntax or semantic rules, often lack agility for complex patches.

Federica Gamba, Aman Sinha, Timothee Mickus, Raul Vazquez

We introduce the CAP (Confabulations from ACL Publications) dataset, a multilingual resource for studying hallucinations in large language models (LLMs) within scientific text generation. CAP focuses on the scientific domain, where hallucinations can distort factual knowledge, as they frequently do. In this domain, however, the presence of specialized termin

Rafael Sánchez, Alok Nath Singh, Andrew N. Jordan, Bibek Bhandari

Quantum tunneling allows electrons to be transferred between two regions separated by an energetically forbidden barrier. Performing a position measurement that finds a particle in the barrier forces the tunneling electrons to transition from having a classically forbidden energy to an energy above the barrier height. We exploit this effect to define quantum

Phuc Tran, Van Vu

The classical Davis-Kahan theorem provides an efficient bound on the perturbation of eigenspaces of a matrix under a large (eigenvalue) gap condition. In this paper, we consider the case when the gap is moderate. Using a bootstrapping argument, we obtain a new bound which is efficient when the perturbation matrix is uncorrelated to the ground matrix. We beli

Mohd Ruhul Ameen, Akif Islam, Abu Saleh Musa Miah, M. Saifuzzaman Rafat

Teaching complex machine learning concepts such as reinforcement learning and Markov Decision Processes remains challenging in engineering education. Students often struggle to connect abstract mathematics to real-world applications. We present LearnML@Cricket, a 12-week curriculum that uses cricket analytics to teach these concepts through practical, hands-

Jusheng Zhang, Kaitong Cai, Jing Yang, Jian Wang

Large Vision-Language Models (VLMs) face an inherent contradiction in image captioning: their powerful single-step generation capabilities often lead to a myopic decision-making process. This makes it difficult to maintain global narrative coherence while capturing rich details, a limitation that is particularly pronounced in tasks that require multi-step an

Aitor Iglesias, Nerea Aranjuelo, Patricia Javierre, Ainhoa Menendez

We present a fully interpretable and flexible statistical method for background subtraction in roadside LiDAR data, aimed at enhancing infrastructure-based perception in automated driving. Our approach introduces both a Gaussian distribution grid (GDG), which models the spatial statistics of the background using background-only scans, and a filtering algorit

Mike Thelwall, Ehsan Mohammadi

Previous research has shown that journal article quality ratings from the cloud based Large Language Model (LLM) families ChatGPT and Gemini and the medium sized open weights LLM Gemma3 27b correlate moderately with expert research quality scores. This article assesses whether other medium sized LLMs, smaller LLMs, and reasoning models have similar abilities

Pawel Wojcik, Haowen Zhou, Taras Khvorost, Guo-Zhu Zhu

We report detailed characterization of the vibronic interactions between the first two electronically excited states, A and B, in SrOPh (Ph = phenyl, -C6H5) and its deuterated counterpart, SrOPh-d5 (-C6D5). The vibronic interactions, which arise due to non-adiabatic coupling between the two electronic states, mix the B,v0 state with the energetically close v

Nader Nemati

Deep neural networks can convert ECG page images into analyzable waveforms, yet centralized training often conflicts with cross-institutional privacy and deployment constraints. A cross-silo federated digitization framework is presented that trains a full-model nnU-Net segmentation backbone without sharing images and aggregates updates across sites under rea

Gabriel Nivasch

Consider a convex polyhedral robot $B$ that can translate (without rotating) amidst a finite set of non-moving polyhedral obstacles in $\mathbb R^3$. The "free space" $\mathcal F$ of $B$ is the set of all positions in which $B$ is disjoint from the interior of every obstacle. Aronov and Sharir (1997) derived an upper bound of $O(n^2\log n)$ for the combinato

Carlos A. M. dos Santos, Marc J. J. Fleury

We present a toroidal electromagnetic ansatz that provides a realistic microscopic model of the QED electron. The proposed toroidal electromagnetic wave satisfies Maxwell's equations and reproduces fundamental properties of the electron as described in quantum electrodynamics (QED). Within this framework, the electron is modeled as a rotating electromagnetic

David Freire-Obregón, José Salas-Cáceres, Modesto Castrillón-Santana

Regularization techniques play a crucial role in preventing overfitting and improving the generalization performance of neural networks. Dropout, a widely used regularization technique, randomly deactivates units during training to introduce redundancy and prevent co-adaptation among neurons. Despite its effectiveness, dropout has limitations, such as its st

Sigtryggur Hauksson, Ilaria Casalbore, Daniele Tomatis, Nunzio Burgio

Quantifying inherent neutron sources in matter, particularly $(\alpha, n)$ reactions and spontaneous fission, is important in nuclear engineering and other fields. The SOURCES code is a common tool for calculating the yield and spectrum of such neutrons. This paper critically examines all modelling assumptions and nuclear data in SOURCES and proposes alterna

Janosz W. Dewberry, Henrik N. Latter, Gordon I. Ogilvie, Sebastien Fromang

Many dynamical interactions can induce eccentricities in astrophysical accretion disks. Disk eccentricities in turn seed a variety of instabilities, even in ideal hydrodynamics. We use 3D nonlinear simulations and 2+1D linear calculations to characterize local and global instabilities in strongly distorted disks. On local scales, our simulations show the gro

Tianran Li, Marius Staring, Yuchuan Qiao

Deformable image registration estimates voxel-wise correspondences between images through spatial transformations, and plays a key role in medical imaging. While deep learning methods have significantly reduced runtime, efficiently handling large deformations remains a challenging task. Convolutional networks aggregate local features but lack direct modeling

Xiyu Luo, Haodong Li, Xinxing Cheng, He Zhao

Image-to-image translation models have achieved notable success in converting images across visual domains and are increasingly used for medical tasks such as predicting post-operative outcomes and modeling disease progression. However, most existing methods primarily aim to match the target distribution and often neglect spatial correspondences between the