October 2025 arXiv papers — page 73

Gyuyeon Na, Minjung Park, Hyeonjeong Cha, Sangmi Chai

We present HCLA, a human-centered multi-agent system for anomaly detection in digital-asset transactions. The system integrates three cognitively aligned roles: Rule Abstraction, Evidence Scoring, and Expert-Style Justification. These roles operate in a conversational workflow that enables non-experts to express analytical intent in natural language, inspect

Andy Bruce, Alexander Aghili, Razvan Marinescu, Daniel Sabo

In the field of machine learning coarse-grained potentials in molecular dynamics, many propagators require that the effective Hamiltonian is quadratic in momentum, thus limiting the family of coarse-graining functions. In this paper, we derive a general family of coarse-graining embedding functions for which Langevin dynamics samples correctly. These equatio

Katsuhiko Matsuzaki

We prove that the fiber space consisting of BMOA functions that are the logarithms of derivatives of conformal homeomorphisms of the unit disk onto bounded quasidisks forms a real-analytic disk bundle over the Bers embedding of the BMO Teichm\"uller space. For the VMO Teichm\"uller space, we show that the corresponding sub-bundle consisting of VMOA functions

Biviana Marcela Suarez Sierra

This study investigates the factors associated with failure in each of the four thematic units of a General Statistics course offered at a private university in Colombia. Unlike traditional analyses that treat performance as a single outcome, this research disaggregates results by unit: Exploratory Data Analysis, Probability and Random Variables, Statistical

Daewoo Park, Suho Park, Inseok Hong, Hanwool Lee

We present AI PB, a production-scale generative agent deployed in real retail finance. Unlike reactive chatbots that answer queries passively, AI PB proactively generates grounded, compliant, and user-specific investment insights. It integrates (i) a component-based orchestration layer that deterministically routes between internal and external LLMs based on

Yajie Li, Albert Galimov, Mitra Datta Ganapaneni, Pujitha Thejaswi

Entity Linking (EL) has traditionally relied on large annotated datasets and extensive model fine-tuning. While recent few-shot methods leverage large language models (LLMs) through prompting to reduce training requirements, they often suffer from inefficiencies due to expensive LLM-based reasoning. ARTER (Adaptive Routing and Targeted Entity Reasoning) pres

Daisuke Matsumoto, Tomohiro Kikuchi, Yusuke Takagi, Soichiro Kojima

Rationale and Objectives: Computer-aided detection systems for chest radiographs are widely used, and concurrent reader displays, such as bounding-box (BB) highlights, may influence the reading process. This pilot study used eye tracking to conduct a preliminary experiment to quantify which aspects of visual search were affected. Materials and Methods: We sa

Angus Walsh, Lorcan Conlon, Biveen Shajilal, Ozlem Erkilic

A core problem in communications is the optimal discrimination of binary-phase-shift-keyed (BPSK) signals. A longstanding goal has been to reach the fundamental quantum limit, known as the Helstrom bound, for BPSK signals encoded in coherent states. However, due to technical constraints, proposals for reaching the bound remain impractical. In this letter we

Ziheng Zhang, Xinyue Ma, Arpita Chowdhury, Elizabeth G. Campolongo

This work investigates descriptive captions as an additional source of supervision for biological multimodal foundation models. Images and captions can be viewed as complementary samples from the latent morphospace of a species, each capturing certain biological traits. Incorporating captions during training encourages alignment with this shared latent struc

Krishnakumar Balasubramanian, Sayan Banerjee, Philippe Rigollet

We study stationary solutions of McKean-Vlasov equations on the circle. Our main contributions stem from observing an exact equivalence between solutions of the stationary McKean-Vlasov equation and an infinite-dimensional quadratic system of equations over Fourier coefficients, which allows explicit characterization of the stationary states in a sequence sp

Jiho Park, Sieun Choi, Jaeyoon Seo, Jihie Kim

Although recent advancements in diffusion models have significantly enriched the quality of generated images, challenges remain in synthesizing pixel-based human-drawn sketches, a representative example of abstract expression. To combat these challenges, we propose StableSketcher, a novel framework that empowers diffusion models to generate hand-drawn sketch

Hao Yu, Haoyu Chen, Yan Jiang, Wei Peng

Self-attention (SA) has become the cornerstone of modern vision backbones for its powerful expressivity over traditional Convolutions (Conv). However, its quadratic complexity remains a critical bottleneck for practical applications. Given that Conv offers linear complexity and strong visual priors, continuing efforts have been made to promote the renaissanc

R. A. Tonacatl-Monez, R. Heid, O. De la Peña-Seaman

This first-principles study investigates the structural, electronic, lattice dynamical properties, and electron-phonon coupling in ferromagnetic cubic B20 FeGe under applied pressure. The implemented spin-scaling exchange-correlation (ssxc) approach allowed to modify the magnetic moment and ferromagnetic phase energetics using a single scaling parameter, the

Constance Crozier

Transmission system operators face a variety of discrete operational decisions, such as switching of branches and/or devices. Incorporating these decisions into optimal power flow (OPF) results in mixed-integer non-linear programming problems (MINLPs), which can't presently be solved at scale in the required time. Various linearizations of the OPF exist, mos

Tawfik Osman, Aditya S. Shekhawat, Abhradeep Roy, Georgios C. Trichopoulos

Reconfigurable Intelligent Surfaces (RISs) can redirect electromagnetic waves to desired directions to enhance signal coverage and/or improve signal-to-noise ratio (SNR) at the user equipment (UE). We present the design, implementation, and evaluation of an RIS-assisted O-RAN 5G system operating in the FR2 millimeter wave (mmWave) frequency band. We first in

Lorenzo Arboit, Dennis N. Schneider, Britty Baby, Vinkle Srivastav

Video-based assessment and surgical data science can advance surgical training, research, and quality improvement, yet adoption remains limited by heterogeneous recording formats and privacy concerns linked to video sharing. This work develops, evaluates, and publicly releases Endoshare, a surgeon-friendly application that merges, standardizes, and de-identi

J. Bayron Orjuela-Quintana, Mauricio Reyes, Elena Giusarma, Francisco Villaescusa-Navarro

Observations of the large-scale structure (LSS) provide a powerful test of gravity on cosmological scales, but high-resolution N-body simulations of modified gravity (MG) are prohibitively expensive. We present MG-NECOLA, a convolutional neural network that enhances fast MG-PICOLA simulations to near-N-body fidelity at a fraction of the cost. MG-NECOLA repro

Chang Yang, Ziyi Wang, Wangfeng Tan, Zhiting Tan

Social media platforms have become important sources for identifying suicide risk, but automated detection systems face multiple challenges including severe class imbalance, temporal complexity in posting patterns, and the dual nature of risk levels as both ordinal and categorical. This paper proposes a hierarchical dual-head neural network based on MentalRo

Bosong Huang, Ming Jin, Yuxuan Liang, Johan Barthelemy

Explaining time series classification models is crucial, particularly in high-stakes applications such as healthcare and finance, where transparency and trust play a critical role. Although numerous time series classification methods have identified key subsequences, known as shapelets, as core features for achieving state-of-the-art performance and validati

Akshay Naik, Ramavarapu S. Sreenivas, William R. Norris, Albert E. Patterson

Reliable off-road autonomy requires operational constraints so that behavior stays predictable and safe when soil strength is uncertain. This paper presents a runtime assurance safety monitor that collaborates with any planner and uses a Bekker-based cost model with bounded uncertainty. The monitor builds an upper confidence traversal cost from a lightweight

Y. Sekhmani, G. G. Luciano, S. K. Maurya, J. Rayimbaev

We study the thermodynamic topology and microscopic interaction properties of charged black holes in RegMax gravity, focusing on the role of the coupling parameter $α$. Using the Duan topological current method together with Ruppeiner geometry, we show that $α$ controls a sharp change in phase structure. Above a certain critical threshold, we find that the D

Reza Ahmari, Ahmad Mohammadi, Vahid Hemmati, Mohammed Mynuddin

This study investigates the vulnerabilities of autonomous navigation and landing systems in Urban Air Mobility (UAM) vehicles. Specifically, it focuses on Trojan attacks that target deep learning models, such as Convolutional Neural Networks (CNNs). Trojan attacks work by embedding covert triggers within a model's training data. These triggers cause spec

Itay M. Bloch, Ana M. Botti, Mariano Cababie, Gustavo Cancelo

Dark matter particles with sufficiently large interactions with ordinary matter can scatter in the Earth's atmosphere and crust before reaching an underground detector. This Earth-shielding effect can induce a directional dependence in the dark matter flux, leading to a sidereal daily modulation in the signal rate. We perform a search for such a modulati

Ritik Shah, Marco F Duarte

Hyperspectral sensors capture dense spectra per pixel but suffer from low spatial resolution, causing blurred boundaries and mixed-pixel effects. Co-registered companion sensors such as multispectral, RGB, or panchromatic cameras provide high-resolution spatial detail, motivating hyperspectral super-resolution through the fusion of hyperspectral and multispe

Murod Mirzhalilov, Nandini Trivedi, Mohit Randeria

We theoretically analyze the topological insulator (TI) surface state mediated interactions between local moments in a proximate 2D ferromagnetic insulator (FMI) motivated by recent experiments that show a significant increase in the Curie temperature Tc of FMI-TI heterostructures. Such interactions have been investigated earlier with a focus on dilute magne

Y. Q. Chai, M. Y. Wang, S. N. Wang, P. H. Ouyang

It is well known that the current-biased Josephson junction (CBJJ) can serve as a Josephson threshold detector (JTD) for the sensitive detection of weak microwave signals. Based on the recent work (PRB {\bf 111}, 024501 (2025)) on the detection sensitive limit of the usual equilibrium JTD, here we numerically demonstrate that a non-equilibrium JTD can be alt

Jan Hajduček, Veronica Leccese, Ján Rusz, Jon Ander Arregi

Electron magnetic circular dichroism (EMCD) in transmission electron microscopy (TEM) enables element-specific measurement of spin and orbital magnetic moments, analogous to X-ray magnetic circular dichroism (XMCD). While the EMCD technique offers unmatched spatial resolution, its quantitative accuracy remains under scrutiny, particularly in beam-splitter ge

Hong-Li Zeng, Yu-Han Huang, John Barton, Erik Aurell

We consider populations evolving according to natural selection, mutation, and recombination, and assume that the genomes of all or a representative selection of individuals are known. We pose the problem if it is possible to infer fitness parameters and genotype fitness order from such data. We tested this hypothesis in simulated populations. We delineate p

Nitay Hurvitz, Gleb Finkelstein, Eran Sela

The surprisingly rich physics of a single Coulomb-blockaded metallic island, when coupled to quantum Hall edge channels, is now well established -- giving rise to charge fractionalization and multi-channel quantum impurity behavior. Here, we show that qualitatively new physics emerges in arrays of such elements. We consider a 1D chain of $N$ metallic islands

Abdul Jabbar, Aakash Bansal, William Whittow

Dynamic metasurface antennas (DMAs) represent a novel approach to programmable and affordable electromagnetic wave manipulation for enhanced wireless communications, sensing, and imaging applications. Nevertheless, current DMA designs and models are usually quasi-narrowband, neglecting the versatile frequency-diverse manifestation and its utilization. This w

Hengrui Liu, Tao Feng, Xiaomiao Wang, Menglong Zhang

Let $v$ be a positive odd integer. A $(v,k,λ)$-perfect difference family (PDF) is a collection $\mathcal{F}$ of $k$-subsets of $\{0,1,\ldots,v-1\}$ such that the multiset $\bigcup_{F\in \mathcal{F}}\{x-y : x,y\in F, x>y\}$ covers each element of $\left\{1,2,\ldots,(v-1)/2\right\}$ exactly $λ$ times. Perfect difference families are a special class of perfect

Biao Dong, Bin Cao, Qinyu Zhang

This work is concerned with the coordination gain in integrated sensing and communication (ISAC) systems under a compress-and-estimate (CE) framework, wherein inference performance is leveraged as the key metric. To enable tractable transceiver design and resource optimization, we characterize inference performance via an error probability bound as a monoton

Chung-Yun Hsieh, Manuel Gessner

We introduce a thermodynamic work extraction task that describes the energy storage enhancement of quantum systems. This task induces majorisation-like conditions that provide a necessary and sufficient characterisation of state conversions in general quantum resource theories. When applied to specific resources, these conditions reduce to the majorisation c

Ryan Husband, Jessica Eastman, Ryan J. Thomas, Simon A. Haine

When generating light with orbital angular momentum by imprinting orbital phase onto a standard Gaussian beam, it is often assumed that the propagation of the generated spatial mode is a Laguerre-Gaussian. However, the true propagation of this beam in a realistic, aperture-limited optical system is non-trivial and has not been thoroughly explored in existing

Aidan Blaser, Luc Lenain, Nick Pizzo

Irrotational and monochromatic surface gravity waves possess a mean Lagrangian drift which transports mass and enhances mixing in the upper ocean. In the ocean, where many surface waves are present, it is commonly assumed that the mean Lagrangian drift can be computed independently for each wave component and summed. Here we show, using laboratory measuremen

Ameya Nambisan, Simon Günzler, Dennis Rieger, Nicolas Gosling

Abrikosov vortices, where the superconducting gap is completely suppressed in the core, are dissipative, semi-classical entities that impact applications from high-current-density wires to superconducting quantum devices. In contrast, we present evidence that vortices trapped in granular superconducting films can behave as two-level systems, exhibiting micro

Weifan Guan, Qinghao Hu, Aosheng Li, Jian Cheng

Vision-Language-Action (VLA) models extend vision-language models to embodied control by mapping natural-language instructions and visual observations to robot actions. Despite their capabilities, VLA systems face significant challenges due to their massive computational and memory demands, which conflict with the constraints of edge platforms such as on-boa

Dmitry S. Ageev, Vladimir A. Bykov

In this paper, we study excited states in Anti-de Sitter (AdS) space prepared by local operator insertions of a massive scalar field, corresponding to local operator quenches in a free bulk scalar theory. Using the AdS/CFT correspondence, we compute the time evolution of boundary observables in the dual CFT states. We then introduce a hard wall in AdS Poinca

Zhijin Li, Xiao Guo, Zhoujian Cao, Yun-Long Zhang

The fundamental nature of dark matter (DM) remains unknown, with significant uncertainties in its density profile. DM environments surrounding massive binary black holes (BBHs) modify their orbital dynamics, thereby altering gravitational wave (GW) emissions. For BBH systems at the Galactic Center, dynamical friction induced by DM spikes could produce detect

Christian F. Schmidt, Simon Brunner, Stefan Floerchinger

We consider excitations of a spin-1 Bose-Einstein-condensate (BEC) in the vicinity of different mean-field configurations and derive mappings to emergent relativistic quantum field theories minimally coupled to curved acoustic spacetimes. The quantum fields are typically identified with Nambu-Goldstone bosons, such that the structure of the analogue quantum

Alex Bols, Mahdie Hamdan, Pieter Naaijkens, Siddharth Vadnerkar

We study Kitaev's quantum double model for arbitrary finite gauge group in infinite volume, using an operator-algebraic approach. The quantum double model hosts anyonic excitations which can be identified with equivalence classes of `localized and transportable endomorphisms', which produce anyonic excitations from the ground state. Following the Dop

Kaiyuan Ji, Hemant K. Mishra, Milán Mosonyi, Mark M. Wilde

Hypothesis exclusion is an information-theoretic task in which an experimenter aims at ruling out a false hypothesis from a finite set of known candidates, and an error occurs if and only if the hypothesis being ruled out is the ground truth. For the tasks of quantum state exclusion and quantum channel exclusion -- where hypotheses are represented by quantum

Jon M. Miller, Xin Xiang, Doyee Byun, Ehud Behar

High-resolution X-ray spectroscopy with XRISM gives an unprecedented view of the ``central engine'' in active galactic nuclei, providing unique insights into black hole accretion and feedback. We present an analysis of the first XRISM/Resolve spectrum of the Seyfert-1 galaxy Mrk 279, known for its complex line profiles and variability. The data reveal veloci

Yuanyuan Tian

For nearly half a century, the core design of query optimizers in industrial database systems has remained remarkably stable, relying on foundational principles from System R and the Volcano/Cascades framework. However, the rise of cloud computing, massive data volumes, and unified data platforms has exposed the limitations of this traditional, monolithic ar

Tochukwu E. Ogri, Muzaffar Qureshi, Zachary I. Bell, Wanjiku A. Makumi

In this paper, we develop a safe control synthesis method that integrates state estimation and parameter estimation within an adaptive optimal control (AOC) and control barrier function (CBF)-based control architecture. The developed approach decouples safety objectives from the learning objectives using a CBF-based guarding controller where the CBFs are rob

M. Abdullah Canbaz, Hakan Otal, Tugce Unlu, Nour Alhussein

Cyber threats increasingly demand joint responses, yet the organizational dynamics behind multi-agency cybersecurity collaboration remain poorly understood. Understanding who leads, who bridges, and how agencies coordinate is critical for strengthening both U.S. homeland security and allied defense efforts. In this study, we construct a co-authorship network

Travis A. Roberts, Sourabh Karmakar, Cameron J. Turner

Additive manufacturing, or 3D printing, is a complex process that creates free-form geometric objects by sequentially placing material to construct an object, usually in a layer-by-layer process. One of the most widely used methods is Fused Deposition Modeling (FDM). FDM is used in many of the consumer-grade polymer 3D printers available today. While consume

Rina Friedberg, Richard Mudd, Patrick Johnstone, Melissa Pothen

Sequential treatment assignments in online experiments lead to complex dependency structures, often rendering identification, estimation and inference over treatments a challenge. Treatments in one session (e.g., a user logging on) can have an effect that persists into subsequent sessions, leading to cumulative effects on outcomes measured at a later stage.

Hui Chen, Xinjie Wang, Xianchao Xiu, Wanquan Liu

Tensor low-rank representation (TLRR) has demonstrated significant success in image clustering. However, most existing methods rely on fixed transformations and suffer from poor robustness to noise. In this paper, we propose a novel transformed bilateral tensor low-rank representation model called TBTLRR, which introduces a data-adaptive tensor nuclear norm

Antonio Norelli, Michael Bronstein

A meaningful text can be hidden inside another, completely different yet still coherent and plausible, text of the same length. For example, a tweet containing a harsh political critique could be embedded in a tweet that celebrates the same political leader, or an ordinary product review could conceal a secret manuscript. This uncanny state of affairs is now

Saeed Saviz Naeini, Reda Snaiki, Alejandro Di Luca

Atlantic Canada faces significant hurricane threats from damaging winds and coastal flooding that are projected to intensify under climate change. This study adopts a two-stage framework. First, the evolution of wind and coastal-flood hazards is quantified from a historical baseline (1979-2014) to two future periods: a near future (2024-2059) and a far futur

Swaroop Hegde

Ruzsa's inequality states that $|A+A+A| \leq |A+A|^{3/2}$ for any finite set $A$ in a commutative group. Ruzsa has constructed examples showing that this inequality is sharp asymptotically, up to a constant factor. We prove an inverse result which says that if $|A+A+A| \geq \frac{1}{M} |A+A|^{3/2}$ for some parameter $M,$ then the set $A$ resembles the sets

Ryan Zhang, Herbert Woisetschläger

Real-world AI systems are tackling increasingly complex problems, often through interactions among large language model (LLM) agents. When these agents develop inconsistent conventions, coordination can break down. Applications such as collaborative coding and distributed planning therefore require reliable, consistent communication, and scalability is a cen

Nephtalí Eliceo Martínez-Pérez, Cupatitzio Ramírez Romero

An FLRW reduction of N=1 supergravity is troublesome since spatial isotropy prohibits a non-vanishing Rarita-Schwinger field. In view of this, we consider the quadratic form $\psi_m^{\ \alpha} \psi_{n \alpha}$ arising from a particular superspace generalization of the metric tensor. Imposing the FLRW form on this object reduces $\psi_m^{\ \alpha}$ to a singl

Bernd Pfrommer

Reconstructing an intensity image from the events of a moving event camera is a challenging task that is typically approached with neural networks deployed on graphics processing units. This paper presents a much simpler, FIlter Based Asynchronous Reconstruction method (FIBAR). First, intensity changes signaled by events are integrated with a temporal digita

Sourabh Karmakar, Apurva Patel, Cameron J. Turner

Stewart platform-based Parallel Kinematic (PKM) Machines have been extensively studied by researchers due to their inherent finer control characteristics. This has opened its potential deployment opportunities in versatile critical applications like the medical field, engineering machines, space research, electronic chip manufacturing, automobile manufacturi

Hiroki Matsukiyo, Jun-ichi Fukuda

To enhance the understanding of the behavior of active nematic, it is important to understand the behavior of topological defects. In this paper, we study the configuration of topological defects of a two-dimensional active nematic around a circular obstacle. In the case of a passive nematic liquid crystal, the equilibrium configuration of defects can be eas

Sourabh Karmakar, Cameron J. Turner

Researchers have studied Stewart-Gough platforms, also known as Gough-Stewart platforms or hexapod platforms extensively for their inherent fine control characteristics. Their studies led to the potential deployment opportunities of Stewart-Gough Platforms in many critical applications such as the medical field, engineering machines, space research, electron

Ram Dyuthi Sristi, Sowmya Manojna Narasimha, Jingya Huang, Alice Despatin

Simultaneous recordings from thousands of neurons across multiple brain areas reveal rich mixtures of activity that are shared between regions and dynamics that are unique to each region. Existing alignment or multi-view methods neglect temporal structure, whereas dynamical latent variable models capture temporal dependencies but are usually restricted to a

Rodrigo Barra Novoa

The study explores the evolution of Chile's industrial policy from 1990 to 2022 through the lens of state capacity, innovation and endogenous development. In a global context where governments are reasserting their role as active agents of innovation, Chile presents a paradox. It is a stable and open economy that has expanded investment in science and techno

Yimeng Qiu, Feihuang Fang

We study whether liquidity and volatility proxies of a core set of cryptoassets generate spillovers that forecast market-wide risk. Our empirical framework integrates three statistical layers: (A) interactions between core liquidity and returns, (B) principal-component relations linking liquidity and returns, and (C) volatility-factor projections that captur

Hugo Arbelaez, Martin Chuaqui, Rodrigo Hernandez, Willy Sierra

We study the localization of the poles of the best Mobius approximations for locally univalent functions in the unit disk. Sharp geometric bounds for the pole function are established in terms of Pommerenke's linear invariant orders, refining classical criteria for convexity and concavity. The behavior of poles is further analyzed for starlike mappings, conv

Hongyi Liu, Jiaji Huang, Zhen Jia, Youngsuk Park

Speculative decoding is widely used in accelerating large language model (LLM) inference. In this work, we focus on the online draft model selection problem in speculative decoding. We design an algorithm that provably competes with the best draft model in hindsight for each query in terms of either the token acceptance probability or expected acceptance len

Alec Dektor, Runze Chi, Roel Van Beeumen, Chao Yang

We present a new subspace iteration method for computing low-lying eigenpairs (excited states) of high-dimensional quantum many-body Hamiltonians with nearest neighbor interactions on two-dimensional lattices. The method is based on a new block isometric projected entangled pair state (block-isoPEPS) ansatz that generalizes the block matrix product state (MP

Mohammed Abouzaid, Ciprian Manolescu

We set up Heegaard Floer theory over the integers, using canonical orientations coming from coupled Spin structures on the Lagrangian tori. We prove naturality of Heegaard Floer homology, sutured Floer homology, and link Floer homology over $\mathbb{Z}$. We give a new proof of the surgery exact triangle in this context, as well as a definition of involutive

Wm. Matthew Kennedy, Cigdem Patlak, Jayraj Dave, Blake Chambers

AI systems have the potential to produce both benefits and harms, but without rigorous and ongoing adversarial evaluation, AI actors will struggle to assess the breadth and magnitude of the AI risk surface. Researchers from the field of systems design have developed several effective sociotechnical AI evaluation and red teaming techniques targeting bias, hat

John L. Spiesberger, Eugene Terray

Numerical implementation of a theory yields acoustic wave packets whose peak-to-peak speeds, $c_{3d}$, are supersonic in a dispersionless medium due to temporal interference between direct and boundary-reflected paths. The effect occurs when the source and receiver are near each other and at least one is within $c\tilde{δt}/2$ of the boundary, where $c$ is t

Mehrdad Ghassabi, Sadra Hakim, Hamidreza Baradaran Kashani, Pedram Rostami

Enhancing reasoning capabilities in small language models is critical for specialized applications such as medical question answering, particularly in underrepresented languages like Persian. In this study, we employ Reinforcement Learning with AI Feedback (RLAIF) and Direct preference optimization (DPO) to improve the reasoning skills of a general-purpose P

Yuecai Han, Yuhang Li

In this paper, infinite horizon stochastic difference equations and backward stochastic difference equations with fractional noises are studied. The main difficulty comes from fractional noises on infinite horizon. Motivated by discrete-time optimal control problem driven by fractional noises and on infinite horizon, the stochastic maximum principle for disc

Hui Wang, Hans D. Schotten, Stefan M. Goetz

The rapid growth of electric vehicles (EVs) has driven the development of roadway wireless charging technology, effectively extending EV driving range. However, wireless charging introduces significant cybersecurity challenges. Any receiver within the magnetic field can potentially extract energy, and previous research demonstrated that a hacker could detect

Yuwei Cheng, Zifeng Zhao, Haifeng Xu

Online advertising platforms use automated auctions to connect advertisers with potential customers, requiring effective bidding strategies to maximize profits. Accurate ad impact estimation requires considering three key factors: delayed and long-term effects, cumulative ad impacts such as reinforcement or fatigue, and customer heterogeneity. However, these

Filip Ficek

We present an elementary proof of existence of infinite family of time-periodic solutions to the one-dimensional nonlinear cubic wave equation with Dirichlet boundary conditions. It relies on the first order perturbative expansion and uses the Banach contraction principle to show existence of nearby solutions. In contrast to the previous results, this approa

Michael Goodrich, Yan Gu, Ryuto Kitagawa, Yihan Sun

Balanced search trees are widely used in computer science to efficiently maintain dynamic ordered data. To support efficient set operations (e.g., union, intersection, difference) using trees, the join-based framework is widely studied. This framework has received particular attention in the parallel setting, and has been shown to be effective in enabling si

Hashem Omrani, Raha Imanirad, Adam Diamant, Utkarsh Verma

We propose an approach for dynamic efficiency evaluation across multiple organizational dimensions using data envelopment analysis (DEA). The method generates both dimension-specific and aggregate efficiency scores, incorporates desirable and undesirable outputs, and is suitable for large-scale problem settings. Two regularized DEA models are introduced: a s

Junyuan Fang, Tuoc Phan

This paper studies a class of linear parabolic equations with measurable coefficients in divergence form whose volumetric heat capacity coefficients are assumed to be in some Muckenhoupt class of weights. As such, the coefficients can be degenerate, singular, or both degenerate and singular. A class of weighted parabolic cylinders with a non-homogeneous quas

Floris Gisolf, Zeno J. M. H. Geradts, Marcel Worring

Analyzing large complex image collections in domains like forensics, accident investigation, or social media analysis involves interpreting intricate, overlapping relationships among images. Traditional clustering and classification methods fail to adequately represent these complex relationships, particularly when labeled data or suitable pre-trained models

Ian Berry, Daniel Huber, Yaguang Li, Daniel Hey

Many A-F type stars do not display $\delta$ Scuti pulsations, despite being located within the instability strip. Open clusters provide a unique opportunity to study $\delta$ Scuti pulsations among coeval populations with uniform chemical composition. Here we use data from the TESS Mission to discover 79 $\delta$ Scuti pulsators in the 300 Myr old open clust

Debdeep Sanyal, Aakash Sen Sharma, Dhruv Kumar, Saurabh Deshpande

Policy optimization (PO) algorithms are used to refine Large Language Models for complex, multi-step reasoning. Current state-of-the-art pipelines enforce a strict think-then-answer format to elicit chain-of-thought (CoT); however, the behavior of PO when these rigid constraints are relaxed into an open-ended CoT structure remains an under-studied question.

Valery Shchesnovich

Solvable bosonic models provide a fundamental framework for describing light propagation in nonlinear media, including optical down-conversion processes that generate squeezed states of light and their higher-order generalizations. In quantum optics a central objective is to determine the time evolution of a given initial state. Exact analytic solution to th

Babacar Seck, Anas Abdullah

Cross-commodity valuation approaches to value gas fire power plants are well studied in the literature. Hence, the value of the gas fire power plant is identical to the value of a spark spread option wherein the underlying are electricity and gas with a strike price assimilated to operating and maintenance costs. Power and fuels spot prices account for uncer

Keke Zhang

In this paper, we present an explicit construction of twisted traces for quantum Coulomb branches of conical theories. We develop an operator representation of the Coulomb branch algebra and use it to derive integral formulas for the twisted trace. Our construction provides a concrete realization of twisted traces that arise as the correlation functions of a

Anna Hellers, Mathias Reichle, Sven Klinkel

In this work, a polygonal Reissner-Mindlin plate element is presented. The formulation is based on a scaled boundary finite element method, where in contrast to the original semi-analytical approach, linear shape functions are introduced for the parametrization of the scaling and the radial direction. This yields a fully discretized formulation, which enable

Nafis Chowdhury, Moinul Haque, Anika Ahmed, Nazia Tasnim

Recent progress in NLP research has demonstrated remarkable capabilities of large language models (LLMs) across a wide range of tasks. While recent multilingual benchmarks have advanced cultural evaluation for LLMs, critical gaps remain in capturing the nuances of low-resource cultures. Our work addresses these limitations through a Bengali Language Cultural

Gareema Ranjan, Mahmoud Alfadel, Gengyi Sun, Shane McIntosh

Since developers invoke the build system frequently, its performance can impact productivity. Modern artifact-based build tools accelerate builds, yet prior work shows that teams may abandon them for alternatives that are easier to maintain. While prior work shows why downgrades are performed, the implications of downgrades remain largely unexplored. In this

Changrui Liu, Shengling Shi, Anil Alan, Ganesh Kumar Venayagamoorthy

Efficient energy management is essential for reliable and sustainable microgrid operation amid increasing renewable integration. In this paper, an imitation learning-based framework to approximate mixed-integer Economic Model Predictive Control (EMPC) is proposed for microgrid energy management, considering fuel generators, renewable energy resources, a unif

Yuyang Jiang, Longjie Guo, Yuchen Wu, Aylin Caliskan

Large language model (LLM)-powered chatbots are increasingly used for opinion exploration. Prior research examined how LLMs alter user views, yet little work extended beyond one-way influence to address how user input can affect LLM responses and how such bi-directional influence manifests throughout the multi-turn conversations. This study investigates this

Cristian Cioflan, Jose Fonseca, Xiaying Wang, Luca Benini

Time series classification (TSC) on extreme edge devices represents a stepping stone towards intelligent sensor nodes that preserve user privacy and offer real-time predictions. Resource-constrained devices require efficient TinyML algorithms that prolong the device lifetime of battery-operated devices without compromising the classification accuracy. We int

Cheng-Hsin Cheng, Giuseppe Ficarra, Helvi Witek

Scalar fields of masses between $10^{-21}\rm{eV}/c^2$ and $10^{-11} \rm{eV}/c^2$ can exhibit enhanced gravitational interactions with black holes, and form scalar clouds around them. Such a cloud modifies the dynamics of a coalescing black-hole binary, and the resulting gravitational waves may provide a new channel to detect light scalar fields, such as axio

Marianne Menglin Liu, Daniel Garcia, Fjona Parllaku, Vikas Upadhyay

Large language model (LLM) agents rely on external tools to solve complex tasks, but real-world toolsets often contain redundant tools with overlapping names and descriptions, introducing ambiguity and reducing selection accuracy. LLMs also face strict input context limits, preventing efficient consideration of large toolsets. To address these challenges, we

David Dukić

This doctoral thesis improves the transfer learning for sequence labeling tasks by adapting pre-trained neural language models. The proposed improvements in transfer learning involve introducing a multi-task model that incorporates an additional signal, a method based on architectural modifications in autoregressive large language models, and a sequence labe

Dmitry Arkhangelsky, Wisse Rutgers

We study a policy evaluation problem in centralized markets. We show that the aggregate impact of any marginal reform, the Marginal Policy Effect (MPE), is nonparametrically identified using data from a baseline equilibrium, without additional variation in the policy rule. We achieve this by constructing the equilibrium-adjusted outcome: a policy-invariant s

Marin Biloš, Anderson Schneider, Yuriy Nevmyvaka

Temporal point processes are powerful generative models for event sequences that capture complex dependencies in time-series data. They are commonly specified using autoregressive models that learn the distribution of the next event from the previous events. This makes sampling inherently sequential, limiting efficiency. In this paper, we propose a novel alg

Liron Mor Yosef, Haim Avron

Over a decade ago, it was demonstrated that quantum computing has the potential to revolutionize numerical linear algebra by enabling algorithms with complexity superior to what is classically achievable, e.g., the seminal HHL algorithm for solving linear systems. Efficient execution of such algorithms critically depends on representing inputs (matrices and

Shengyu Chen, Shihang Feng, Yi Luo, Xiaowei Jia

Ultrasound brain imaging remains challenging due to the large difference in sound speed between the skull and brain tissues and the difficulty of coupling large probes to the skull. This work aims to achieve quantitative transcranial ultrasound by reconstructing an accurate speed-of-sound (SoS) map of the brain. Traditional physics-based full-waveform invers

Vahid Jalili

Since its 2009 genesis block, the Bitcoin network has processed >1.08 billion (B) transactions representing >8.72B BTC, offering rich potential for machine learning (ML); yet, its pseudonymity and obscured flow of funds inherent in its UTxO-based design, have rendered this data largely inaccessible for ML research. Addressing this gap, we present an ML-compa

Damian Bowness, Charalambos Poullis

When viewing a 3D Gaussian Splatting (3DGS) model from camera positions significantly outside the training data distribution, substantial visual noise commonly occurs. These artifacts result from the lack of training data in these extrapolated regions, leading to uncertain density, color, and geometry predictions from the model. To address this issue, we pro

Jeffrey Bringolf, Hovhannes A. Harutyunyan, Shahin Kamali, Seyed-Mohammad Seyed-Javadi

We study the Telephone Broadcasting problem in graphs with restricted structure. Given a designated source in an undirected graph, the goal is to disseminate a message to all vertices in the minimum number of rounds, where in each round every informed vertex may inform at most one neighbor. For general graphs, the problem is NP-hard. Recent work shows that t

Akshara Vincent

We provide counterexamples to uniqueness of solutions as well as a priori Calder\'on-Zygmund estimates for solutions below $L^2$ using convex integration argument for equations of the type $$ \text{div} (A (\nabla u)) = 0 \quad \text{in } \mathbb{B}^2, $$ where $A: \mathbb{R}^{2} \to \mathbb{R}^2$ is smooth, uniformly elliptic and has essentially linear grow

Alexander G. Tartakovsky, Jay Bartroff, Cheng-Der Fuh, Haipeng Xing

Tze Leung Lai made seminal contributions to sequential analysis, particularly in sequential hypothesis testing, changepoint detection and nonlinear renewal theory. His work established fundamental optimality results for the sequential probability ratio test and its extensions, and provided a general framework for testing composite hypotheses. In changepoint

Nigel Higson, Emil Prodan

Given a triangulation of a closed orientable surface, we place single-mode resonators or single-orbital artificial atoms at its vertices, edges and facets, and we devise near-neighbor hopping terms derived from the boundary and Poincar\'e duality maps of the simplicial complex of the triangulation. Regardless of the surface or its triangulation, these terms