March 2026 arXiv papers — page 11

Guan-Lun Huang, Yuh-Jzer Joung

Modern web scraping struggles with dynamic, interactive websites that require more than static HTML parsing. Current methods are often brittle and require manual customization for each site. To address this, we introduce Webscraper, a framework designed to handle the challenges of modern, dynamic web applications. It leverages a Multimodal Large Language Mod

Xuzhen Cao, Xiaolin Li, Liang Bai, Zhaoxin Liang

Nonlinear interaction enables topological phenomena impossible in linear systems. A paradigm is nonlinear Thouless pump, where the transport of solitons can be topologically quantized even when band occupation is nonuniform. Such nonlinear quantization traditionally requires a time-periodic Hamiltonian with static nonlinearity and, much as in the linear case

George Boateng, Samuel Boateng, Victor Kumbol

Providing timely and accurate learning support in large-scale online coding courses is challenging, particularly in resource-constrained contexts. We present Kwame 2.0, a bilingual (English-French) generative AI teaching assistant built using retrieval-augmented generation and deployed in a human-in-the-loop forum within SuaCode, an introductory mobile-based

Benjamin E. Diamond

To each ternary sextic $f(X_0, X_1, X_2)$ whose associated plane curve is smooth, the Shioda construction attaches a smooth sextic fourfold $X \subset \mathbb{P}^5$ whose defining equation $f(X_0, X_1, X_2) - f(Y_0, Y_1, Y_2)$ is fixed under the involution $ι: (X_0, X_1, X_2, Y_0, Y_1, Y_2) \mapsto i \cdot (Y_0, Y_1, Y_2, -X_0, -X_1, -X_2)$. The induced acti

James Marshall Reber, Sebastián Pavez-Molina

Given a $C^0$ conjugacy between two Anosov diffeomorphisms, the matching periodic data problem asks whether this conjugacy is smooth provided spectral data of the diffeomorphisms match at periodic points. We show that if the two $C^0$ conjugate diffeomorphisms on $\mathbb{T}^3$ are sufficiently close to a hyperbolic linear automorphism with a pair of complex

Rui Sun

The standard wage Phillips curve aggregates away from which workers reset wages when. I show this aggregation omits a first-order term: the covariance between workers' cost-push exposure and their reset frequency. I introduce two sufficient statistics and embed them in a multi-country HANK model calibrated to six euro-area economies. The omitted term generat

Bastian B. Brandt, Gergely Endrődi, José Javier Hernández Hernández, Gergely Markó

Quantum Chromodynamics (QCD) is the theory of the strong interactions within the Standard Model of particle physics, which explains more than 99% of the mass of the visible Universe. However, there is evidence that a substantial portion of our Universe is made up of particles beyond the Standard Model, i.e. dark matter. A popular dark matter candidate is the

Brian Doherty

Transient sources on astronomical photographic plates are objects that appear on a single exposure but have no counterpart in modern sky surveys or on temporally adjacent plates. I present an independent replication of two findings reported by Bruehl and Villarroel (2025) and Villarroel et al. (2025): (1) a temporal correlation between transient detections o

Silong Yong, Stephen Sheng, Carl Qi, Xiaojie Wang

Existing robotic foundation policies are trained primarily via large-scale imitation learning. While such models demonstrate strong capabilities, they often struggle with long-horizon tasks due to distribution shift and error accumulation. While reinforcement learning (RL) can finetune these models, it cannot work well across diverse tasks without manual rew

Xiongkun Zheng, Dabin Zheng, Xiaoqiang Wang, Mu Yuan

Affine-invariant codes have attracted considerable attention due to their rich algebraic structure and strong theoretical properties. In this paper, we study a family of affine-invariant codes whose defining set consists of all descendants of elements in the cyclotomic coset of a single specified element. Our main contributions are as follows. First, we esta

Hung N. Do, Jessica Z. Kubicek-Sutherland, S. Gnanakaran

Access to the most up-to-date information on medical countermeasures is important for the research and development of effective treatments for viruses and marine toxins. However, there is a lack of comprehensive databases that curate data on viruses and marine toxins, making decisions on medical countermeasures slow and difficult. In this work, we employ two

Guan Wang, Shuyin Xia, Lei Qian, Tao Wu

Graph Convolutional Network (GCN) is a model that can effectively handle graph data tasks and has been successfully applied. However, for large-scale graph datasets, GCN still faces the challenge of high computational overhead, especially when the number of convolutional layers in the graph is large. Currently, there are many advanced methods that use variou

Jinshi Sai, Shigehisa Takakuwa, Hsi-Wei Yen, Yusuke Tsukamoto

Turbulence in protoplanetary disks plays a crucial role in the evolution of disk structures and the planet formation process therein. However, the strength of the turbulence remains unclear in young, embedded disks surrounded by infalling envelopes. In this paper, we present the first direct measurement of the nonthermal velocity dispersion within the embedd

Michele Polese, Rajeev Gangula, Tommaso Melodia

The convergence of communication, sensing, and Artificial Intelligence (AI) in the Radio Access Network (RAN) offers compelling economic advantages through shared spectrum and infrastructure. How can inference and sensing be integrated in the RAN infrastructure at a system level? Current abstractions in O-RAN and 3GPP lack the interfaces and capabilities to

William O'Regan

We give a simple and self-contained proof of an extension of a projection theorem of Bourgain over the reals to division algebras over local fields of zero characteristic.

Yuto Hama, Daisuke Kitayama, Kensuke Inaba, Toshimori Honjo

This paper proposes a novel optimization framework for discrete phase shifts of a reconfigurable intelligent surface (RIS) using a coherent Ising machine (CIM). Unlike conventional methods based on iterative convex approximation or combinatorial search with exponentially increasing complexity, the CIM physically explores the solution space of Ising Hamiltoni

YaoKun Lei, Yi Isaac Yang

Chemical reaction sampling critically depends on collective variables (CVs) that capture the slow degrees of freedom governing reactive transformations. However, existing reaction CVs are often defined in geometric space or learned in a system-specific manner, which limits their transferability and leaves open the more fundamental question of how reaction pr

Fares Fawzi, Seyed Parsa Neshaei, Marta Knezevic, Tanya Nazaretsky

Formative feedback is central to effective learning, yet providing timely, individualised feedback at scale remains a persistent challenge. While recent work has explored the use of large language models (LLMs) to automate feedback, most existing systems still conceptualise feedback as a static, one-way artifact, offering limited support for interpretation,

Danielle R. Thomas, Conrad Borchers, Kirk P. Vanacore, Kenneth R. Koedinger

Generative Artificial Intelligence (GenAI) is now widespread in education, yet the efficacy of GenAI systems remains constrained by the quality and interpretation of the labeled data used to train and evaluate them. Studies commonly report inter-rater reliability (IRR), often summarized by a single coefficient such as Cohen's kappa (k), as a gatekeeper to ``

Omer Nguena Timo, Paul-Alexis Rodriguez, Florent Avellaneda

Finite state machines (FSM) are executable formal specifications of reactive systems. These machines are designed based on systems' requirements. The requirements are often recorded in textual documents written in natural languages. FSMs play a crucial role in different phases of the model-driven system engineering (MDE). For example, they serve to automate

Ruoqi Wang, Xinyang Li, Bo Zhao, Haofu Wen

Topologically non-trivial nodes emerging from flat-band crossings not only enhance unconventional topological responses but also play a fundamental role in exploring correlation-driven topological physics. Here, we report the exceptionally robust chiral-anomaly-dominated transport in D0_3-Fe_3Ga. First, we observe a combination of positive and negative magne

Mahesh Ramani, Shlok Kumar

We present an optimally minimal two-axiom basis for BCH-algebras. The standard presentation of a BCH-algebra relies on three axioms: two equations and one quasi-identity. Using automated theorem proving, we prove that the two standard equations can be entirely replaced by a 14-symbol equation, ((xy)z)((x(z0))y) = 0, while retaining the standard quasi-identit

Xizhi Fu, Lei Han, Xi Liu, Cheng Song

The deterministic switching of magnetic order parameters is critically important, as it forms the fundamental basis for manipulating information states in magnetic memory devices. This work presents a general theoretical framework that unifies the mechanisms of magnetic switching by introducing the concept of switching symmetry and establishing that the nece

Alexander S. Petty

For a prime base $b$ and primitive odd Dirichlet character $\chi$ modulo $b^2$, the collision transform coefficient $\hat{S}^{\circ}(\chi)$ admits an exact factorization: \[ \hat{S}^{\circ}(\chi) = -\frac{B_{1,\overline{\chi}} \cdot \overline{S_G(\chi)}}{\phi(b^2)}, \] where $B_{1,\overline{\chi}}$ is the generalized first Bernoulli number and $S_G(\chi)$ is

Swen Kuh, Lauren Kennedy, Qixuan Chen, Andrew Gelman

When estimating population prevalence from a non-random sample, it is important to adjust for differences between sample and population. However, adjustment for multiple factors requires analysis that can be difficult to understand and validate. In this manuscript, we explore an unexpected downward trend of estimates when covariates are added sequentially to

Xiaoyan Zhang, Jiangpeng He

Visual food recognition in real-world dietary logging scenarios naturally exhibits severe data imbalance, where a small number of food categories appear frequently while many others occur rarely, resulting in long-tailed class distributions. In practice, food recognition systems often operate in a continual learning setting, where new categories are introduc

Mingjin Chen, Junhao Chen, Zhaoxin Fan, Yujian Lee

Recent methods have made notable progress in the visual quality of hand-object interaction video synthesis. However, most approaches rely on 2D control signals that lack spatial expressiveness and limit the utilization of synthetic 3D conditional data. To address these limitations, we propose HVG-3D, a unified framework for 3D-aware hand-object interaction (

Alexander Chen, Yuntian Wang, Md Sadman Sakib Rahman, Yuhang Li

Nonlinear computation is essential for various information processing tasks. Optical implementations are attractive because passive light propagation can manipulate high-dimensional signals with extreme throughput and parallelism; yet realizing nonlinear mappings in optical hardware remains challenging due to the weak nonlinearity of optical materials and th

Bartłomiej Zawalski

In his classical work, W. Blaschke proved that a convex body whose shadow boundaries are flat for every direction of parallel illumination must be an ellipsoid. An extension recently proposed by I. Gonzalez-Garc\'ia, J. Jer\'onimo-Castro, E. Morales-Amaya, and D.J. Verdusco-Hern\'andez predicts that the same conclusion holds for illumination by point light s

Shota Kawakami, Daisuke Takahashi

Modern processors deliver higher throughput for lower-precision arithmetic than for higher-precision arithmetic. For matrix multiplication, the Ozaki scheme exploits this performance gap by splitting the inputs into lower-precision components and delegating the computation to optimized lower-precision routines. However, no similar approach exists for the fas

Yi Wei, Xufeng Cai, Jelena Diakonikolas

Cyclic block coordinate methods are a fundamental class of first-order algorithms, widely used in practice for their simplicity and strong empirical performance. Yet, their theoretical behavior remains challenging to explain, and setting their step sizes -- beyond classical coordinate descent for minimization -- typically requires careful tuning or line-sear

Yuwen Zhu, Feiyang Qi, Zhengzhe Xiang

To address the challenges of simultaneously satisfying detection accuracy, edge real-time performance, low-power operation, and end-to-end business linkage in parking scenarios, this paper proposes an intelligent parking barrier system based on deep learning and multi-sensor fusion. The system adopts a three-layer collaborative architecture comprising an edg

Xiangkai Sun, Feng Guo, Liang He, Xiaole Guo

This paper deals with a new Tikhonov regularized primal-dual dynamical system with variable mass and Hessian-driven damping for solving a convex optimization problem with linear equality constraints. The system features several time-dependent parameters: variable mass, slow viscous damping, extrapolation, and temporal scaling. By employing the Lyapunov analy

Yi Bing, Liu Jia, Fu Jinyang, Peng Xiang

Diffusion models have recently emerged as powerful stochastic frameworks for high-dimensional inference and generation. However, existing applications to partial differential equations (PDEs) predominantly rely on physics-informed training strategies, which tightly couple learning with specific governing equations and limit generalization across problem sett

Wensu Li, Atin Aboutorabi, Harry Lyu, Kaizhi Qian

This paper develops a unified framework for evaluating the optimal degree of task automation. Moving beyond binary automate-or-not assessments, we model automation intensity as a continuous choice in which firms minimize costs by selecting an AI accuracy level, from no automation through partial human-AI collaboration to full automation. On the supply side,

Tetsuya Sato, Tomoyuki Nakagawa

In this paper, we consider the sphericity test for a one-sample problem under high-dimensional two-step monotone incomplete data. Existing asymptotic expansions for the null distributions of the likelihood ratio test (LRT) statistic and modified LRT statistic are inaccurate in high-dimensional settings. Therefore, we derive Edgeworth expansions for the null

Luke Bhan, Peter Quawas, Miroslav Krstic, Yuanyuan Shi

Modern control systems frequently operate under input delays and sampled state measurements. A common delay-compensation strategy is predictor feedback; however, practical implementations require solving an implicit ODE online, resulting in intractable computational cost. Moreover, predictor formulations typically assume continuously available state measurem

Kanak Gautam, Poorvi Bhatia, Parmit K. Chilana

Learning to use feature-rich software is a persistent challenge, but generative AI tools promise to lower this barrier by replacing complex navigation with natural language prompts. We investigated how people approach prompt-based tools for 3D modeling in an observational study with 26 participants (14 casuals, 12 professionals). Consistent with earlier work

Luke Bhan, Miroslav Krstic, Yuanyuan Shi

Due to simplicity and strong stability guarantees, predictor feedback methods have stood as a popular approach for time delay systems since the 1950s. For time-varying delays, however, implementation requires computing a prediction horizon defined by the inverse of the delay function, which is rarely available in closed form and must be approximated. In this

Isaac Planas-Sitjà, Ryosuke Iritani, Adam L. Cronin

Anthropogenic activity threatens biodiversity through climate change, habitat fragmentation, and increasing frequency and scale of disturbance. Various theoretical studies have sought to shed light on how these factors could promote or hinder the coexistence of species. However, our understanding of the relative importance of, and interactions between, these

Mi chen, Renhao Ye

Context. Random seed selection in deep learning is often arbitrary -- conventionally fixed to values such as 42, a number with no known feline endorsement. Aims. We propose that cats, as liminal beings with a historically ambiguous relationship to quantum mechanics, are better suited to this task than random integers. Methods. We construct a cat-driven seed

Yuqing Xiao, John Grundy, Anuradha Madugalla, Elizabeth Manias

Requirements engineering for aged-care digital health must account for human aspects, because requirement priorities are shaped not only by technical functionality but also by stakeholders' health conditions, socioeconomics, and lived experience. Knowing which human aspects matter most, and for whom, is critical for inclusive and evidence-based requirements

Muhamed Ramees Cheriya Mukkolakkal

This paper presents two independent contributions for Apache Pulsar practitioners. First, we validate 1,499,947 msg/s at 3.88 ms median publish latency on just three bare-metal Kubernetes nodes running Pulsar 4.0.8 with Java 21 and ZGC Generational garbage collection, and project a hardware-driven path to 15 million msg/s on 15 machines using five independen

Iordanis Fostiropoulos, Muhammad Rafay Azhar, Abdalaziz Sawwan, Boyu Fang

We introduce GISTBench, a benchmark for evaluating Large Language Models' (LLMs) ability to understand users from their interaction histories in recommendation systems. Unlike traditional RecSys benchmarks that focus on item prediction accuracy, our benchmark evaluates how well LLMs can extract and verify user interests from engagement data. We propose two n

Jadon Y. Lin, C. Martijn de Sterke, Boris T. Kuhlmey

We show that optical forces perpendicular to the direction of the incident light, generated on structures with asymmetric optical scattering, can manipulate longitudinal elastic waves traveling in that same perpendicular direction. When the radiation pressure acts unidirectionally, reciprocity and hence Newton's Third Law are effectively broken. As a result,

Yen-Chun Liu, Alexander Volfovsky, German Schnaidt, Cristobal Garib

This study addresses the challenge of estimating average treatment effects (ATEs) for advertising campaigns in online marketplaces where complete randomized experimentation is infeasible. We propose two key innovations: (1) a shrinkage estimator that optimally combines observational and experimental data without assuming smooth treatment effects across campa

Zhaorui Yang, Haichao Zhu, Qian Zhang, Rajiv Gupta

Fault localization identifies program locations responsible for observed failures. Existing techniques rank suspicious code using syntactic spectra--signals derived from execution structure such as statement coverage, control-flow divergence, or dependency reachability. These signals collapse for semantic bugs, where failing and passing executions follow ide

Disen Liao, Felix Dangel, Yaoliang Yu

Bilevel optimization (BO) is widely applicable to many machine learning problems. Scaling BO, however, requires repeatedly computing hypergradients, which involves solving inverse Hessian-vector products (IHVPs). In practice, these operations are often approximated using crude surrogates such as one-step gradient unrolling or identity/short Neumann expansion

Gabriele Marini, Alessandro Colombo, Andrea Lanubile, William A. Paxton

While battery aging is commonly studied at the cell-level, evaluating aging and performance within battery modules remains a critical challenge. Testing cells within fully assembled modules requires hardware solutions to access cell-level information without compromising module integrity. In this paper, we design and develop a hardware testing platform to mo

Andrii Iurov, Liubov Zhemchuzhna, Tiyhearah Danner-Jackson

The subject of the present paper is a detailed theoretical investigation of the energy spectrum and bandgaps, as well as topological and collective properties and linear response, in $d$-wave altermagnets in the presence of an off-resonance optical dressing field. We consider the altermagnets with both $d_{x^2-y^2}$ and $d_{xy}$ pairing symmetries and focus

Shiji Lyu

Bertin (1972) defined regularity for coherent local rings, and Knaf (2004) studied the property for a local ring $A$ essentially finitely presented over a valuation ring $V$. We discuss several properties of this notion of regularity for such $A$, obtaining results parallel to results for regularity of Noetherian local rings. We include classical and modern

Konstantin M. Dyakonov

In the Hardy spaces $H^1$ and $H^\infty$, there are neat and well-known characterizations of the extreme points of the unit ball. We obtain counterparts of these classical theorems when $H^1$ (resp., $H^\infty$) gets replaced by the quotient space $H^1/E$ (resp., $H^\infty/E$), under certain assumptions on the subspace $E$. In the $H^1$ setting, we also trea

Xiaoqi Zhang, J. Andrew Zhang, Chang Liu, Weijie Yuan

Sensing and communication are fundamental enablers of next-generation networks. While communication technologies have advanced significantly, sensing remains limited to conventional parameter estimation and is far from fully explored. Motivated by these limitations, we propose semantic sensing (SemS), a novel framework that shifts the design objective from r

David Robinson, Animesh Gupta, Elizabeth Clark, Olga Melnik

Standard clinical assessments of upper-extremity motor function after stroke either rely on ordinal scoring, which lacks sensitivity, or time-based task metrics, which do not capture movement quality. In this work, we present a computer vision-based framework for analysis of upper-extremity movement during the Box and Block Test (BBT) through world-aligned j

Maomi Ueno, Enbo Zhang, Kazuma Fuchimoto, Satoshi Chiba

The fission product yield (FPY) is crucially important information for numerous nuclear applications. However, the peak-shaped characteristics of FPY data present important challenges for predicting unobservable FPY data. To address these challenges, after applying Multi-task learning models to fission product yield data and their experimental error estimate

Jinyue Jiang, Jiancheng An, Lu Gan, Naofal Al-Dhahir

Flexible intelligent metasurface (FIM) has recently received considerable interest due to its advantage in realizing a better channel condition by dynamically morphing its surface shape. An FIM consists of multiple elements deposited on a flexible substrate. These elements can not only transmit signals, but also adapt their displacements in a direction perpe

Prithwish Ghosh, Sujit K Ghosh

An Automated Sliced Gibbs framework is proposed for fully automated Markov chain Monte Carlo sampling from arbitrary finite dimensional probability kernels. The method targets unnormalized, non-smooth, heavy tailed, and highly multimodal densities. A Cauchy transformation based effective support estimator is combined with slice driven Gibbs updates. This con

Maruchi Kim, Rasya Fawwaz, Zhi Yang Lim, Brinda Moudgalya

Despite their ubiquity, wireless earbuds remain audio-centric due to size and power constraints. We present VueBuds, the first camera-integrated wireless earbuds for egocentric vision, capable of operating within stringent power and form-factor limits. Each VueBud embeds a camera into a Sony WF-1000XM3 to stream visual data over Bluetooth to a host device fo

Qianru Lyu, Conrad Borchers, Meng Xia, Karen Xiao

Past research has defined a general process for the data-driven redesign of educational technologies and has shown that in carefully-selected instances, this process can help make systems more effective. In the current work, we test the generality of the approach by applying it to four units of a middle-school mathematics intelligent tutoring system that wer

Pratyay Banerjee, Masud Moshtaghi, Ankit Chadha

LLM-based autonomous agents lack persistent procedural memory: they re-derive solutions from scratch even when structurally identical tasks have been solved before. We present APEX-EM, a non-parametric online learning framework that accumulates, retrieves, and reuses structured procedural plans without modifying model weights. APEX-EM introduces: (1) a struc

Alicia Bao, Jiamian He, Angel Hsu, Diego Manya

As large language models (LLMs) are increasingly used in domain-specific applications, including climate change and environmental research, understanding their energy footprint has become an important concern. The growing adoption of retrieval-augmented (RAG) systems for climate-domain specific analysis raises a key question: how does the energy consumption

Henry Lamm

The orbifold lattice has been proposed as a route to practical quantum simulation of Yang--Mills theory, with claims of exponential speedup over all known approaches. Through analytical derivations, Monte Carlo simulation, and explicit circuit construction, we identify compounding costs entirely absent in Kogut--Susskind formulations: a mass-dependent Trotte

Jaber Jaber, Osama Jaber

World models that predict future states from video remain limited by flat latent representations that entangle objects, ignore causal structure, and collapse temporal dynamics into a single scale. We present HCLSM, a world model architecture that operates on three interconnected principles: object-centric decomposition via slot attention with spatial broadca

Amogh Joshi, Julian Ost, Felix Heide

Unbounded 3D world generation is emerging as a foundational task for scene modeling in computer vision, graphics, and robotics. In this work, we present WorldFlow3D, a novel method capable of generating unbounded 3D worlds. Building upon a foundational property of flow matching - namely, defining a path of transport between two data distributions - we model

Fabian Gloeckle, Mantas Baksys, Darius Feher, Kunhao Zheng

Recent progress in large language models (LLMs) has substantially advanced automatic code generation and formal theorem proving, yet software verification has not seen comparable gains. To address this gap, we propose WybeCoder, an agentic code verification framework that enables prove-as-you-generate development, in which code, invariants, and proofs co-evo

Yassine El Kheir, Amit Meghanani, Mostafa Shahin, Omnia Ibrahim

We present the findings of the second edition of the IQRA Interspeech Challenge, a challenge on automatic Mispronunciation Detection and Diagnosis (MDD) for Modern Standard Arabic (MSA). Building on the previous edition, this iteration introduces \textbf{Iqra\_Extra\_IS26}, a new dataset of authentic human mispronounced speech, complementing the existing tra

Ivar Frisch, Jackie Kay, Philip Moreira Tomei

In this paper, we introduce the concept of synthetic counteradaptation, a process where human and AI systems co-evolve by adapting to each other's strategies and behaviors. Synthetic counteradaptation occurs when AI systems develop novel strategies or social protocols, prompting humans to extract insights and adapt their own behaviors in response, leadin

Yutaro Yamada, Robert Tjarko Lange, Cong Lu, Chris Lu

The automation of science is a long-standing ambition in the field of AI. While the community has made significant progress in automating individual components of the scientific process, a system that autonomously navigates the entire research lifecycle -- from conception to publication -- has remained out of reach. Here, we present the strongest demonstrati

Khalid Zguaid, Fatima Zahrae El Alaoui, Delfim F. M. Torres

Observability is a fundamental concept in control theory. Its primary purpose is to look into whether it is possible to reconstruct the system's initial state using only the information from its outputs. This paper focuses on the regional reconstruction problem of the initial state for a semilinear time-fractional system, which refers to the possibility

Masoud Shokrnezhad, Tarik Taleb, Yan Chen, Qize Guo

Key Value Indicators (KVIs) provide a decision oriented view of a service by summarizing how operational performance translates into stakeholder value, risk, and outcomes. However, in many domains KVIs are difficult to compute in practice because they require selecting relevant KVI categories, defining measurable Key Performance Indicators (KPIs), collecting

Yichen Liu, Imam Akintomiwa Akinlade, Xiaochong Jiang, Wenting Yang

Environmental monitoring is a crucial component of the smart city infrastructure. It enables informed decision making which enhances sustainability, public health and urban planning. However, the large-scale deployments of the smart sensors have raised concerns on excessive energy consumption and redundant data collection as well as limited sensor lifespan.

Danny Butvinik, Yonit Marcus, Nitzan Tal, Gabrielle Azoulay

We introduce the Temporal Contrastive Transformer (TCT), a representation learning framework designed to capture contextual temporal dynamics in sequences of financial transactions. The model is trained using a self-supervised contrastive objective to produce embeddings that encode behavioral patterns over time, with the goal of supporting downstream fraud d

Atmaram Yarlagadda, Eranga Bandara, Ross Gore, Anita H. Clayton

Modern military operations expose soldiers to sustained psychological stress, leading to acute reactions, post-traumatic stress symptoms, and other mental health issues. Although the U.S. Department of Defense offers evidence-based therapies, access to trained professionals in forward-deployed and contested environments is limited. As a result, soldiers with

Alankar Atreya, Stefan Sylvius Wanger, Devesh Batra, Robert Hankache

Banks receive millions of reports of fraud, scams, and disputed transactions every year, making it challenging to accurately direct customers to the appropriate specialist teams for assistance. The existing manual process driven by humans is slow and stressful for both customers and staff. To address this, we develop a customer-facing AI powered triaging age

Haoran Bu, Litian Zhang, Chuxuan Zhang, Zhanyuan Liu

Driven by large language models (LLMs), social bot can autonomously engage in local interactions, whose human-like behaviors enable them to evade social bot detection. However, while these botnets exhibit realistic local social interactions, they fail to preserve human-like social network. This is because LLM-based bots are graph-unaware and cannot coordinat

Song-Ze Zhong, Xian-Gai Deng, Xu-Guang Huang, Yu-Gang Ma

We study the generation and space-time evolution of fluid acceleration in heavy-ion collisions using AMPT and UrQMD transport models combined with a Gaussian smearing method. The peak proper acceleration reaches several hundred MeV, with mild model dependence. Transverse acceleration points outward and is strongest at the fireball boundary due to steep press

Filip J. Kucia, Anirban Chakraborty, Anna Wróblewska

Despite growing interest in using Large Language Models (LLMs) for educational assessment, it remains unclear how closely they align with human scoring. We present a systematic evaluation of instruction-tuned LLMs across three open essay-scoring datasets (ASAP 2.0, ELLIPSE, and DREsS) that cover both holistic and analytic scoring. We analyze agreement with h

Ibrahim Sadiek, Aleksandr A. Balashov, Adrian Hjältén, Michael Rey

Quantitative spectroscopic detection of dibromomethane, CH$_2$Br$_2$, for environmental monitoring, workplace safety, and exoplanetary studies is limited by the lack of accurate absorption cross-section data and rigorous spectroscopic models. We report the first high-resolution (6.3 MHz point spacing) absorption cross-section of CH$_2$Br$_2$ in the 1180-1210

J. J. González-Avilés, N. Baltazar Pérez-Negrón, A. Segura

Close-in terrestrial exoplanets around M dwarfs reside in dense, magnetized winds, where non-ideal plasma coupling can strongly affect how electromagnetic energy is redistributed within the dayside interaction region. We present three-dimensional resistive magnetohydrodynamic simulations of the TRAPPIST-1 wind interacting with a dipolar TRAPPIST-1e magnetosp

Ruben Alfaro Molina, Juan Carlos Cabanillas Noris, Edmundo García Solis, Laura Helena González Trueba

This paper reports on the design and construction of a chamber for the muon identifier detector (MID) of the ALICE 3 upgrade project. The chamber consists of two sensitive layers separated by a 1 cm air gap. Each layer holds 24 scintillator bars ($1\times4\times100$ cm$^3$) manufactured by FNAL-NICADD. The bars are equipped with Kuraray wavelength shifting f

Balark Tiwari, Nishan Khadka, Nicholas Capps, Andre Bos

Digital Glass Forming (DGF) is a new manufacturing process for low-batch glass fabrication. The work zone temperature in DGF processes must be maintained in the glass's working range to ensure good fabrication. If the temperature is too low, the filament will not wet to the substrate or previously deposited material and, if the temperature is too high, t

Lorenzo Bertassi, Maria Charisi, Fabio Rigamonti, Stefano Covino

Since their discovery, AGN light curves are known to be intrinsically variable. In the optical/UV band, this variability is consistent with correlated or red noise and is particularly well described by the damped random walk (DRW) model. In this work, we evaluate the feasibility of a new method for identifying spatially unresolved couples of AGN through a fu

Matthew C. Smith

Coupling stellar feedback to the evolution of individual stars, as opposed to averaging over the initial mass function (IMF), substantially improves the fidelity of galaxy formation simulations by capturing stochastic population effects. Existing treatments can typically only operate at a narrow mass resolution range, limiting their applicability. We present

M. Loriga, M. Cadelano, C. Pallanca, F. R. Ferraro

In this paper, we present the results of a detailed photometric analysis of Glimpse-C02, one of the most extincted globular clusters of the Milky Way. We built a deep color magnitude diagram spanning $\approx$ 10 magnitudes, enabling the first identification of the cluster's main sequence turnoff. Due to the extreme reddening affecting the region, a diff

Ema Mauko, Shane D Johnson, Enrico Mariconti

Cloud computing has drastically altered the ways in which it is possible to deliver information technologies in a service-led structure, however, this has also been reflected in the cybercrime domain. Cybercrime as a Service is an economic model where a technically skilled actor offers a given cyberattack as an end-to-end service to non-technical actors who

Luigi Altamura, Alessio Cicero, Mateo Vázquez Maceiras, Mohammad Ali Maleki

The currently dominant AI/ML workloads, such as Large Language Models (LLMs), rely on the efficient execution of General Matrix-Matrix Multiplication (GEMM) operations. Thus, most systems are equipped with dedicated matrix hardware accelerators based on square Systolic Arrays (SAs) of Processing Elements (PEs). While this organization was effective for tradi

Michael P. Adams, Elizabeth M. Jefremovas, Andreas Michels

We present a symmetry-resolved classification of two-dimensional spin-flip small-angle neutron scattering (SANS) patterns arising from dilute ensembles of spherical nanoparticles hosting magnetic vortex states. Based on a linear vortex ansatz with an axially symmetric distribution of vortex axes and the corresponding analytical expression for the orientation

Manakkumar Parmar, Ajay Kumar Rai

This study investigates the sensitivity of two-body non-leptonic branching fractions to theoretical mass variations in heavy-light mesons ($D$, $D_s$, $B$, and $B_s$). Utilizing the factorization framework, we compare predictions derived from phenomenological masses evaluated with Gaussian and hydrogenic wavefunctions. For bottom meson decays, naive factoriz

Itay Asher Zimet, Shiri Alouf-Heffetz, Nimrod Talmon

Purpose: Multiwinner voting rules typically require full knowledge of voter preferences, which becomes impractical in large-scale or attention-limited settings. This paper investigates how accurately a winning committee can be approximated when voter preferences are elicited using a limited budget of structured queries. Methods: We introduce a query-based fr

Cliò Efthimia Agrapidis, Satoshi Nishimoto

We study the hole-doped Kitaev-Heisenberg chain using the density-matrix renormalization group. In the Kitaev-only limit, the bond-directional exchange itself promotes pairing, favoring spin-singlet and spin-triplet superconducting tendencies for antiferromagnetic and ferromagnetic Kitaev couplings, respectively, together with finite-size Majorana edge corre

Heribertus Bayu Hartanto, Rene Poncelet

We derive two-loop scattering amplitudes for bottom-quark pair production in association with a Higgs boson at the LHC, focusing on terms proportional to the top-quark Yukawa coupling. We treat the bottom quark as a massless parton and employ both the leading-colour and heavy-top-quark approximations. The finite remainder of the two-loop amplitude is express

Devansh Kaushik, Sajal K. Ghosh, Syed M. Kamil

The self-assembling behaviour of ionic liquids in aqueous solution is important for understanding their physicochemical properties and for their industrial applications. While the influence of ionic liquids on surfactant micellization has been widely studied, much less attention has been given to how surfactants affect the aggregation of ionic liquids, parti

Luigi Camerano, Laura Martella, Lorenzo Battaglia, Federico Giannessi

Plasmons in low dimensional materials provide a powerful platform for nanoscale control of light matter interactions, yet strategies to tailor their coherence and dissipation remain limited. Here, we demonstrate that transition metal intercalation offers a fundamentally distinct route to engineer plasmonic response in layered materials. By combining high-res

Anass Sedrati, Mounir Afifi, Reda Benkhadra

This paper introduces the L-ReLF (Low-Resource Lexical Framework), a novel, reproducible methodology for creating high-quality, structured lexical datasets for underserved languages. The lack of standardized terminology, exemplified by Moroccan Darija, poses a critical barrier to knowledge equity in platforms like Wikipedia, often forcing editors to rely on

J. Tong, G. Chen, H. Li, E. Hoenig

Recent work investigated graphene's hydrogenation with independent control of the electric field, E, and charge density, n, in the crystal and showed that the process is controlled by n. Here, we demonstrate layer-selective conductor-insulator transitions in twisted bilayer graphene, driven by hydrogenation at fixed n under strong E. This process is acco

Lele Liu, Bo Ning

Let $G$ be a simple graph, and denote by $λ(G)$ its spectral radius. Sun and Das (2020) established that for any non-isolated vertex $v$ with degree $d(v)$, \[ λ(G)\leq \sqrt{λ(G-v)^2 + 2d(v) - 1}, \] which is a conjecture original posed by Guo, Wang, and Li (2019). Sun and Das's proof uses several tools from spectral graph theory. In this short note, we

Nephtalí Eliceo Martínez Pérez, Cupatitzio Ramírez Romero

We study Cosmological Einsteinian Cubic Gravity (CECG) arXiv:1810.08166v3 in the context of minisuperspace quantum cosmology. CECG is a modification of Einstein's gravity by cubic curvature terms that yield a nontrivial contribution to the dynamics of FRW backgrounds while keeping the Friedmann equations at second order. First, we study the Hamiltonian f

Moirangthem Tiken Singh, Surajit Borkotokey, Rajnish Kumar

Autonomous artificial intelligence agents in negotiation systems must generate equitable utility allocations satisfying individual rationality (IR), ensuring each agent receives at least its outside option, and the Nash Bargaining Solution (NBS), which maximizes joint surplus. Existing generative models often learn suboptimal human behaviors, producing solut

Zhao-Sai Jia, Gang Li, Zhen-Hua Zhang

The cusp structure at the $π^+π^-$ threshold in the $π^0π^0$ invariant mass spectrum serves as a sensitive probe for extracting the $S$-wave $ππ$ scattering lengths in processes where an $S$-wave $π^0π^0$ pair is produced in the final states. Within the framework of nonrelativistic effective field theory with coupled channels $π^0π^0$ and $π^+π^-$, we revisi

Yi Pang, Robert J. Saskowski

String theories naturally exhibit dualities that lead to hidden symmetries in the low-energy effective description, which have been used to great effect to generate supergravity solutions. We review recent progress in using hidden symmetries arising from T-duality to generate higher-derivative-corrected solutions, as well as the problems that arise from non-