April 2026 arXiv papers — page 67

Liqi Jing, Dingming Zhang, Peinian Li, Lichen Zhu

We build on the Visual Autoregressive Modeling (VAR) framework and formulate style transfer as conditional discrete sequence modeling in a learned latent space. Images are decomposed into multi-scale representations and tokenized into discrete codes by a VQ-VAE; a transformer then autoregressively models the distribution of target tokens conditioned on style

Mohammad Farhad, Shuvalaxmi Dass

Software security assurance relies on effective vulnerability detection and patching, yet determining whether a patch fully eliminates risk remains an underexplored challenge. Existing vulnerability benchmarks often treat patched functions as inherently benign, overlooking the possibility of residual security risks. In this work, we analyze vulnerable-benign

Andrea Kubin, Enrico Pasqualetto

We develop a measure and integration theory for random normed modules. Given a probability space $({\rm X},\Sigma,\mathfrak m)$, we introduce and study measures taking values into the space $L^0(\mathfrak m)$ of $\mathfrak m$-measurable functions quotiented up to $\mathfrak m$-a.e. equality. Moreover, we develop a Bochner-type integration theory with respect

Pedro Iván Suárez Navarro

We study complex one-dimensional parameter slices in a three-parameter family of rational maps with two free critical points, obtained by imposing the existence of periodic orbits with prescribed multipliers. Using explicit parametrizations, we explore these slices numerically by analyzing the behavior of the critical orbits and approximating the correspondi

Ali Aghababaei-Harandi, Aude Sportisse, Massih-Reza Amini

Semi-supervised learning has emerged as a powerful paradigm for leveraging large amounts of unlabeled data to improve the performance of machine learning models when labeled data are scarce. Among existing approaches, methods derived from FixMatch have achieved state-of-the-art results in image classification by combining weak and strong data augmentations w

Siqi Ouyang, Shuoyang Ding, Oleksii Hrinchuk, Vitaly Lavrukhin

Simultaneous speech translation (SST) generates translations while receiving partial speech input. Recent advances show that large language models (LLMs) can substantially improve SST quality, but at the cost of high computational overhead. To reduce this cost, prior work reformulates SST as a multi-turn dialogue task, enabling full reuse of the LLM's key-va

Richard Arthur, Virginia DiDomizio, Louis Hoebel

In some complex domains, certain problem-specific decompositions can provide advantages over monolithic designs by enabling comprehension and specification of the design. In this paper we present an intuitive and tractable approach to reasoning over large and complex data sets. Our approach is based on Active Data, i.e., data as atomic objects that actively

Travis LaCroix, Fintan Mallory, Sasha Luccioni

This paper examines the strategic use of language in contemporary artificial intelligence (AI) discourse, focusing on the widespread adoption of metaphorical or colloquial terms like "hallucination", "chain-of-thought", "introspection", "language model", "alignment", and "agent". We argue that many such terms exhibit strategic polysemy: they sustain multiple

Valentin Lemaire, Gaël Aglin, Siegfried Nijssen

The field of machine learning is subject to an increasing interest in models that are not only accurate but also interpretable and robust, thus allowing their end users to understand and trust AI systems. This paper presents a novel method for learning a set of optimal quantile regression trees. The advantages of this method are that (1) it provides predicti

Aljalila Aladawi, Mohammed Talha Alam, Fakhri Karray

Machine unlearning for text-to-image diffusion models aims to selectively remove undesirable concepts from pre-trained models without costly retraining. Current unlearning methods share a common weakness: erased concepts return when the model is fine-tuned on downstream data, even when that data is entirely unrelated. We adapt Projected Gradient Unlearning (

Ahmed Alkhonain, Kiran Kumar Challa, Amarsagar Reddy Ramapuram Matavalam, Alok Kumar Bharati

The rapid growth of inverter-based resources (IBRs) and distributed energy resources (DERs) has fundamentally altered the long-term voltage stability characteristics of modern power systems. This article leverages the advantages of machine learning (ML) for the online estimation of long-term voltage stability margin (VSM) and enhancement of VSM through coord

Habib Yousefi Dezdarani, Ryan Curry, Cassandra L. Armstrong, Alexandros Gezerlis

We study uncertainties in the equation of state of neutron stars using conformal prediction as a distribution-free and model-agnostic method that provides coverage guarantees. In particular, we apply the Conformalized Quantile Regression (CQR) method to posterior samples calculated from Bayesian inference, creating reliable uncertainty bands without assuming

Yi-Hsin Shen, Shane Smolenski, Ming Wen, Yimo Hou

Combining topological insulators with topological semimetals in the form of homologous superlattices is a promising approach for generating correlated quantum matter based upon Fermi level alignment with band extrema. For antimony telluride, a saddle point is predicted to occur at the M-point, while antimonene layering is predicted to move the M-point valenc

Marzia Binta Nizam, James Davis

Text-to-image(T2I) models like Stable Diffusion and DALL-E have made generative AI widely accessible, yet recent studies reveal that these systems often replicate societal biases, particularly in how they depict demographic groups across professions. Prompts such as 'doctor' or 'CEO' frequently yield lighter-skinned outputs, while lower-status roles like 'ja

Ambre Visive, Roberto Ruiz de Austri, Polina Moskvitina, Clara Nellist

Anomaly detection in High Energy Physics requires identifying rare signals against overwhelming backgrounds, without prior knowledge of the signal. We present the first application of masked-token prediction, a technique from Large Language Models, to this problem. A lightweight encoder architecture trained solely on background events captures the structure

Allan Kipyator Kipkemboi Cheboi, Julie Hawke, Hussam Abualfatah, Andrew Sutjahjo

This paper documents a collaborative research process involving peacebuilders and data scientists in Kenya and Sudan to develop AI-based text classifiers for monitoring online polarization and hatespeech. The method describes a participatory annotation process in which practitioners and domain experts contributed to problem definition, annotation design, ite

Dahun Kim, Ganesh Satish Mallya, Anelia Angelova

Multi-spectral imagery is a valuable input signal for Remote Sensing applications, such as land-use and land-cover classification and environmental monitoring. However, generalist Large Multi-modal Models (LMMs) are typically trained on RGB images, limiting their applicability to the RGB domain. At the same time, training multi-spectral multi-modal models is

Tapiwa Amion Chinodakufa, Ashfaq Ali Shafin, Khandaker Mamun Ahmed

Synthetic data generation offers promise for addressing data scarcity and privacy concerns in educational technology, yet practitioners lack empirical guidance for selecting between traditional resampling techniques and modern deep learning approaches. This study presents the first systematic benchmark comparing these paradigms using a 10,000-record student

Viktor Emil Korladinov, Antonin Novak, Zdeněk Hanzálek, Erik Sonntag

The recent emergence of planar transport systems necessitates re-evaluation of Flexible Manufacturing Systems (FMS) to address the simultaneous scheduling of internal logistics and production operations. By operating on a tile-based planar grid, these systems allow independent movers full two-dimensional freedom, mitigating inefficiencies inherent to traditi

Christian Lammers, Fernando Arévalo, Leonie Märker-Neuhaus, Daniel Heinenberg

The increasing frequency and severity of global flood events highlights the need for the development of rapid and reliable flood prediction tools. This process traditionally relies on computationally expensive hydraulic simulations. This research presents a prediction tool by developing a deep-learning based surrogate model to accurately and efficiently pred

Anurita Das

Deploying large language models to heterogeneous hardware is often constrained by memory, not compute. We introduce MCAP (Monte Carlo Activation Profiling), a load-time per-layer importance estimator that enables dynamic precision and memory placement decisions on the target device. MCAP produces a lightweight per-layer signal that drives both precision disp

Felix Hommelsheim, Pia Jehmlich, Moritz Mühlenthaler

Given an edge-colored graph, the Maximum Rainbow Matching problem asks for a maximum-cardinality matching of the graph that contains at most one edge from each color. We provide the following complexity dichotomy for this problem based on the structure of the color classes: Maximum Rainbow Matching admits a polynomial-time algorithm if almost every color cla

Rayan Mazouz, Marco Quadrelli, Rashied Amini, Maria Hakuba

This paper presents a modeling and control framework for distributed systems in low Earth orbit, with the scientific objective of obtaining high accuracy estimates of the Earth's Energy Imbalance (EEI). This metric robustly quantifies the difference between the absorbed solar radiation, and the infrared radiation emitted into space. Formally, the EEI represe

Tyler Ikehara, Ibrahim Pehlivan, Danijela Cabric, Thomas L. Marzetta

The FR3 band has emerged as the major focus of 6G wireless research. FR3 cellular operation presents the challenge of extreme bandwidth combined with physically large antenna arrays. In this regime, conventional phase-shift beamforming entails a loss of coherence (beam-squint), and has to be replaced by true time delay beamforming (TTD). It happens that TTD

Weitung Yang, Choongjae Won, Cory Cress, Weihang Lu

Altermagnetism, a third class of collinear magnetism with spin-split bands and vanishing net magnetization, has emerged in hexagonal α-MnTe, a promising platform for ultrafast, stray-field-free spintronics. Whether MnTe's macroscopic symmetry-breaking signatures reflect ideal altermagnetic order or are activated by defects remains open. Here we report gi

Emily Hsiao, Layla Parast

A surrogate marker is a biomarker or other physical measurement used to replace a primary outcome in clinical trials to evaluate a treatment effect when the primary outcome of interest is costly, invasive, or takes a long time to observe. However, replacing a primary outcome with a surrogate can lead to the "surrogate paradox," in which a treatment appears b

Jingwei Kang, Maarten de Rijke, Harrie Oosterhuis

Carousel interfaces have been the de-facto standard for streaming media services for over a decade. Yet, there has been very little research into user behavior with such interfaces, which thus remains poorly understood. Due to this lack of empirical research, previous work has assumed that behaviors established in single-list web-search interfaces, such as t

Bowen Zuo, Dongruo Zhou, Yinglun Zhu

While scaling test-time compute can substantially improve model performance, existing approaches either rely on static compute allocation or sample from fixed generation distributions. In this work, we introduce a test-time compute allocation framework that jointly adapts where computation is spent and how generation is performed. Our method begins with a wa

Vishwanath Saragadam, Niki Nezakati, Amit Roy-Chowdhury, Vivek Boominathan

Traditional glass-based optics are typically optimized for narrow spectral bands, such as the visible (400-700nm) or shortwave infrared (1000-1800nm). While the emergence of VIS-SWIR sensors (400-1700nm) offers transformative potential, refractive optics struggle to focus this entire range simultaneously. Mirrors represent a promising achromatic alternative;

Adam Cushman, William O'Regan

Utilising recent advances in incidence geometry for balls and tubes, and advances in sum-product theory in the discrete setting, we show that for $0 < s \leq 1/2$ and for any $A \subset \mathbb{R}$ with Hausdorff dimension $s$, either the upper-box dimension of $AA$, or the lower-box dimension of $A+A$ must be at least $29s/23$. We obtain the slightly better

Fangshuo Liao, Afroditi Kolomvaki, Anastasios Kyrillidis

When training neural networks with full-batch gradient descent (GD) and step size $\eta$, the largest eigenvalue of the Hessian -- the sharpness $S(\boldsymbol{\theta})$ -- rises to $2/\eta$ and hovers there, a phenomenon termed the Edge of Stability (EoS). \citet{damian2023selfstab} showed that this behavior is explained by a self-stabilization mechanism dr

Jaazib Charanya, Anthony Morales, Natalie M. Paquette

The chiral algebra bootstrap (CAB) is a novel bootstrap program for form factors in quantum-integrable self-dual gauge theories, some of which in turn are helicity amplitudes in the corresponding gauge theories. The singularities that recursively generate a given (loop-level) form factor are holomorphic collinear splitting functions, equivalently celestial c

Tommaso Marini, Xiao-Liang Qi, Herman Verlinde

We present a dual gravity interpretation of the complex reparametrization mode $\psi(u)$ that governs the soft dynamics of double-scaled SYK in the presence of a time-dependent Maldacena-Qi coupling. We find that the dual gravity system takes the form of 2+1-dimensional Einstein-de Sitter gravity with an energy distribution localized on a dS$_2$ slice within

Alexander W. Criswell, Stephen R. Taylor, Kris Pardo, Alberto Sesana

While massive black hole binaries (MBHBs) merge at gravitational-wave frequencies above the pulsar timing array (PTA) sensitivity band, we show that they leave orphaned low-frequency contributions in the PTA pulsar term. Due to the light-propagation time between each pulsar in the array and Earth, the pulsar term acts as a time-delayed probe of a chirping me

Sara Molló-Guri, Oriol Rubies-Bigorda, Raphael Holzinger, Jonah S. Peter

We investigate how laser-driven, cooperative dipole-dipole interactions in weakly trapped atomic arrays give rise to self-organized configurations. Starting from an analytically tractable two-emitter system, we identify the possible steady-state spatial arrangements accessible to the atoms. We then extend this analysis to larger ensembles in both linear and

Naga VS Raviteja Chappa, Evangelos Sariyanidi, Lisa Yankowitz, Gokul Nair

Micro-actions are subtle, localized movements lasting 1-3 seconds such as scratching one's head or tapping fingers. Such subtle actions are essential for social communication, ubiquitously used in natural interactions, and thus critical for fine-grained video understanding, yet remain poorly understood by current computer vision systems. We identify a fundam

Qinyuan Zheng, Bence Bécsy, Chiara M. F. Mingarelli

Pulsar timing arrays record gravitational waves from supermassive black hole binaries at two spacetime points: an Earth term, measured when the wave passes the Earth, and a pulsar term, measured when the wave passed each pulsar at an earlier epoch. We show that a future $\mu$Hz-band detection of a nearby massive binary by a mission such as $\mu$Ares would tu

Leo L Duan

Variable selection in linear regression has been a central topic in statistical research for decades. Bayesian variable selection methods, which account for uncertainty in both the regression coefficients and the noise variance, have achieved broad success through the use of discrete or continuous shrinkage priors and efficient collapsed Gibbs samplers. Desp

Yuekun Dai, Zhoutong Zhang, Shangchen Zhou, Nanxuan Zhao

The life of a photo begins with photons striking the sensor, whose signals are passed through a sophisticated image signal processing (ISP) pipeline to produce a display-referred image. However, such images are no longer faithful to the incident light, being compressed in dynamic range and stylized by subjective preferences. In contrast, RAW images record di

Takumi Kakimoto, Masayuki Tanaka, Kei Ito, Francesco Valentino

We report on the spectroscopic confirmation of overdense regions of massive quiescent galaxies (QGs) in the early Universe with JWST/NIRSpec. Based on data from the DeepDive NIRSpec program and archival data from the Dawn JWST Archive, we confirm three QGs in the vicinity of Jekyll & Hyde, a pair of massive QG and a dusty star-forming galaxy, at $z=3.71$ and

Mirazul Haque, Antony Papadimitriou, Samuel Mensah, Zhiqiang Ma

We introduce Deep FinResearch Bench, a practical and comprehensive evaluation framework for deep research (DR) agents in financial investment research. The benchmark assesses three dimensions of report quality: qualitative rigor, quantitative forecasting and valuation accuracy, and claim credibility and verifiability. Particularly, we define corresponding qu

J. François, L. Ravera

We present an invariant relational path-integral quantization framework for general-relativistic gauge field theories based on the Dressing Field Method. The construction implements an automatic anomaly-cancellation mechanism that encompasses Bardeen-Wess-Zumino counterterms. The resulting framework unifies invariant schemes across contexts ranging from elec

Haebin Seong, Li Yin, Haoran Zhang, Zhan Shi

AI agents are increasingly deployed on complex, domain-specific workflows -- navigating enterprise web applications that require dozens of clicks and form fills, orchestrating multi-step research pipelines that span search, extraction, and synthesis, automating code review across unfamiliar repositories, and handling customer escalations that demand nuanced

Samuel Belo

We study compact $m$-quasi-Einstein manifolds and derive geometric estimates relating the oscillation of the potential function to the diameter of the manifold. We obtain lower bounds for the diameter in terms of the oscillation of the potential function. As an application in dimension four, we derive diameter conditions ensuring that compact $m$-quasi-Einst

Yijun Yuan, Na Du, Adam J. Lee, Balaji Palanisamy

Password-based authentication is one of the most commonly used methods for verifying user identities, and its widespread usage continues in virtual reality (VR) applications. As a result, various forms of attacks on password-based authentication in traditional environments such as keystroke inference and shoulder surfing, are still effective in VR applicatio

Jeremiah Hockaday

Rex, short for Reverse Hex, is a set coloring game in which players try to avoid connecting terminals of their color. Combinatorial game theory (CGT) is the study of perfect strategy games. Until recently, both Rex and Hex were not examined through the lens of CGT. In this thesis we take inspiration from the study of normal play games by Berlekamp, Conway, a

Megan Mazzatenta, Samuel M. Koblensky, Luc Deike

Bubbles entrained by breaking waves rise to the ocean surface where they cluster and burst, emitting sea spray aerosols into the atmosphere. Bubble bursting thereby links seawater biogeochemistry and aerosol chemistry, influencing the ability of emitted aerosols to serve as cloud condensation nuclei or ice nucleating particles. The mechanisms of film drop an

CMS Collaboration

A search for dark matter produced in association with a dark Higgs boson decaying into a bottom quark-antiquark pair has been performed using proton-proton collision data at a center-of-mass energy of 13 TeV. The search uses data collected with the CMS detector at the CERN LHC during the 2016$-$2018 data-taking period, corresponding to an integrated luminosi

Santiago Chaves, Andreas Debrouwere, Alberto Hernández Alvarado, Jasson Vindas

We establish new strong factorization properties for the smooth vectors of representations of exponential solvable Lie groups on Fr\'{e}chet spaces. In particular, our results improve upon the Dixmier-Malliavin factorization theorem for simply connected nilpotent Lie groups.

Dmitry I. Garagash, Alice-Agnes Gabriel

The localization of slow and fast slip in fault gouges may play a crucial role in understanding the mechanics of earthquakes and slow slip events. Here, we investigate the fracture energy accompanying this localization and the subsequent thermal weakening. We develop an analytical framework, complemented by numerical simulations, for a gouge governed by rate

Michael Hellus, Reinhold Hübl, Anton Rechenauer

This article discusses numerical semigroups having a generator which is as large as possible. This turns out to be $2g+1$, where $g$ is the genus of the semigroup. We will show that these semigroups are closely related to symmetric semigroups and have interesting symmetry properties themselves. Furthermore we will show that Wilf's question has a positive ans

Inderjeet Nair, Jie Ruan, Lu Wang

Alignment faking, where a model behaves aligned with developer policy when monitored but reverts to its own preferences when unobserved, is a concerning yet poorly understood phenomenon, in part because current diagnostic tools remain limited. Prior diagnostics rely on highly toxic and clearly harmful scenarios, causing most models to refuse immediately. As

Yannis Belkhiter, Giulio Zizzo, Sergio Maffeis, Seshu Tirupathi

The growth of agentic AI has drawn significant attention to function calling Large Language Models (LLMs), which are designed to extend the capabilities of AI-powered system by invoking external functions. Injection and jailbreaking attacks have been extensively explored to showcase the vulnerabilities of LLMs to user prompt manipulation. The expanded capabi

Ganesh Sahadeo Meshram, Partha Pratim Chakrabarti, Suman Chakraborty

Spreading of liquid droplets on solid substrates constitutes a classic multiphysics problem with widespread applications ranging from inkjet printing, spray cooling, to biomedical microfluidic systems. Yet, accurate computational fluid dynamic (CFD) simulations are prohibitively expensive, taking more than 18 to 24 hours for each transient computation. In th

Jiguang Yu

In this workshop, we present a compact but rigorous introduction to second-order optimality conditions for mathematical programs with equilibrium constraints (MPECs). We start from the classical nonlinear programming template, then explain why it fails in the equilibrium-constrained setting, and develop the three main viewpoints used in the literature: (i) m

Vittoria Bruni, Paola Erminia Calabrese, Rosanna Campagna, Domenico Vitulano

This paper explores the use of artificial neural networks for the stable and data-driven selection of the frequency parameter in hyperbolic polynomial penalized splines (HP-splines). This parameter defines the underlying spline space and is essential for adapting the model to exponential patterns in the data, such as those encountered in signal processing. T

I-Chia Chang, Xinyan Huang, Tzu-Yuan Lin, Sangli Teng

Legged robots have demonstrated remarkable agility on rigid, stationary ground, but their locomotion reliability remains limited in non-inertial environments, where the supporting ground moves, tilts, or accelerates. Such conditions arise in ground transportation, maritime platforms, and aerospace settings, and they introduce persistent time-varying disturba

Didam Duniya, Isaac Opio, Bishop Mongwane, Hassan Abdalla

Relativistic effects are sensitive to subtle changes in dark energy. These effects grow on very large scales and at high redshifts, which will be the reach of upcoming surveys. We investigate these effects in both the linear and the angular galaxy power spectra in a late-time universe dominated by cold dark matter and k-essence, focusing on three core models

Jiguang Yu

In this workshop, we present a compact but rigorous introduction to the basic language of nonlinear programming, variational inequalities, and complementarity systems. The goal is twofold. First, we explain the mathematical logic of hypotheses under which first-order optimality conditions for MPECs become valid. Second, we explain how to use that theory in r

Xiyang Wu, Zongxia Li, Guangyao Shi, Alexander Duffy

Long horizon interactive environments are a testbed for evaluating agents skill usage abilities. These environments demand multi step reasoning, the chaining of multiple skills over many timesteps, and robust decision making under delayed rewards and partial observability. Games are a good testbed for evaluating agent skill usage in environments. Large Langu

Jordan M. Adams

Optical vortex knots have been realized in monochromatic laser beams, but monochromatic fields are stationary and their topology is frozen. Here we show that knotted spatiotemporal vortices, whose phase singularities form closed loops in spacetime, undergo topology changing reconnections with free space propagation. When null lines of different vector compon

S. Mandal, S. Ghosh, S. Das, S. Biswas

The Gas Electron Multiplier (GEM) detectors are widely used in high-energy physics (HEP) experiments as tracking devices because of their excellent position resolution and to handle high particle rates capability. Charging-up effect is a well known phenomenon in GEM detectors because of the presence of the dielectric medium -- Kapton in the foil. Charging-up

Edith J. Zhang, James Scott, Qiang Du

A graph reaction--diffusion (RD) equation is a system of differential equations that is defined on the nodes of a graph. Consider a sequence of growing graphs that converges in cut norm to a limiting graphon. We show that the solutions of the sequence of graph RD equations converge in $L^p$ norm, for $p \in [1,\infty]$, to the solution of a limiting nonlocal

Syed Nazmus Sakib, Nafiul Haque, Shahrear Bin Amin, Hasan Muhammad Abdullah

Vision evaluations are typically done through multi-step processes. In most contemporary fields, experts analyze images using structured, evidence-based adaptive questioning. In plant pathology, botanists inspect leaf images, identify visual cues, infer diagnostic intent, and probe further with targeted questions that adapt to species, symptoms, and severity

Aditya Bali, Rupsha, Vidur Kaushik, Anirban Sen

We present MediaGraph, a network-theoretic framework for analyzing reporting preferences in news media through entity co-occurrence networks. Using articles from four Indian news-sources, two mainstream (The Times of India and The Indian Express) and two fringe outlets (dna and firstpost), we construct source-specific co-occurrence networks around the 2020-2

Sunny Joy Ma, Xiang Ma

Pancreatic tumor segmentation in contrast-enhanced computed tomography (CT) is clinically important yet technically challenging: lesions are often small, heterogeneous, and easily confused with surrounding soft tissue, and models that perform well on one cohort frequently degrade under cohort shift. Our goal is to improve cross-cohort generalization while ke

Douglas R. Frey

The Riccati differential equation is examined in light of its connection to second order linear time varying systems. In that light it becomes the clear generalization for the characteristic equation of linear time invariant systems, and is called the Riccati Characteristic Equation (RCE). Consequently, the RCE becomes the unifying centerpiece for the study

Douglas R. Frey

This paper presents a unifying theory of Linear second order systems that allows time-varying and time invariant systems to be treated in the same way for the first time. In the process, a transformation is given that diagonalizes an arbitrary time varying state matrix in a spectrum invariant way. A canonical form for the fundamental matrix is given that dep

Nils Lid Hjort, Cristiano Varin

In many spatial and spatial-temporal models, and more generally in models with complex dependencies, it may be too difficult to carry out full maximum likelihood (ML) analysis. Remedies include the use of pseudo-likelihood (PL) and quasi-likelihood (QL) (also called the composite likelihood). The present article studies the ML, the PL and the QL methods for

M. Lozada-Cassou

We show that finite-size violations of local electroneutrality in confined electrolytes are governed by the topology of the confining domain, yielding a universal hierarchy of deviations across spherical, cylindrical, and planar geometries. Within Poisson-Boltzmann theory, we introduce an electroneutrality deviation ratio that quantifies how global electrost

Hippolyte Quelquejay Leclere

By monitoring the times of arrival of radio pulses from millisecond pulsars, Pulsar Timing Arrays (PTAs) serve as unique gravitational wave (GW) laboratories in the nanohertz band. To date, the primary astrophysical sources of GWs targeted in this frequency range have been inspiraling supermassive black hole binaries (SMBHBs) on circular and eccentric orbits

Alessandra Lingua, Arturo Chao Correas, François Hild, David S. Kammer

Architected materials can exhibit remarkable combinations of stiffness, strength, and toughness, yet their application is currently limited by an incomplete understanding of how cracks initiate and propagate through their discrete architecture. Elucidating the mechanisms that underpin these processes is challenging because lattice failure is governed by high

Eljohn Evangelista, Alyssa Cea, Axel Balitaan, Clark Vince Diala

Effective hyperlocal communication is critical in the Philippines, where delayed or algorithm-filtered updates can leave residents uninformed about emergency advisories and community events. We conducted a user-centered study consisting of contextual inquiry and semi-structured interviews to identify four key barriers: delayed alerts, algorithm-driven noise,

Michael O'Herlihy, Rosa Català

Content moderation systems are typically evaluated by measuring agreement with human labels. In rule-governed environments this assumption fails: multiple decisions may be logically consistent with the governing policy, and agreement metrics penalize valid decisions while mischaracterizing ambiguity as error -- a failure mode we term the Agreement Trap. We f

Mudit Garg, Lucio Mayer, Yinhao Wu, Yacine Ali-Haïmoud

Gravitational wave (GW) detector LISA will observe near-coalescence extreme mass ratio inspirals (EMRIs), which typically form in galactic central accretion disks. Torques from the disk can alter the GW-driven inspiral trajectory of an embedded EMRI from the vacuum expectation, leading to potentially observable GW dephasing ($Δψ_{\rm gas}$). So far, all stud

Thomas Krämer, Daniel Litt, Marco Maculan

We produce infinitely many local systems on (level covers of) the moduli space of smooth cubic threefolds, with algebraic monodromy group equal to the exceptional group $E_6$. These local systems arise in the middle cohomology of abelian \'etale covers of the Fano scheme parametrizing lines in the universal cubic threefold.

Lukas Weber, Leonardo dos Anjos Cunha, Johannes Flick, Shiwei Zhang

We investigate the effects of coupling a quantum-magnetic cavity field to molecules. Our high-precision auxiliary-field quantum Monte Carlo calculations capture the effect of the cavity field in the presence of electron correlations, and their interplay and competition. In H$_2$, we find that a strong enough cavity coupling makes the original bound ground st

Roberto Feola, Riccardo Montalto, Federico Murgante

We study the long-time dynamics of small-amplitude solutions to the three-dimensional gravity-capillary water waves equations for an inviscid and irrotational fluid with periodic boundary conditions. We prove that, for almost all values of the surface tension parameter, solutions with initial size $\varepsilon$ exist and remain small over time intervals of o

Juwairiya S. Khan, Mostafa Mohammadi, Alexander L. Ammitzbøll, Ellen-Merete Hagen

Upper-limb exoskeletons (ULEs) have the potential to restore functional independence in individuals with severe motor impairments; however, the clinical relevance of wrist degrees of freedom (DoF), particularly abduction-adduction (Ab-Ad), remains insufficiently evaluated. This study investigates the functional and user-perceived impact of wrist Ab-Ad assist

Pratika Dayal

The James Webb Space Telescope (JWST) has revealed a puzzling population of massive black holes in the first billion years, many of which are over-massive compared to their hosts (obese black holes), and reside in metal-poor hosts, posing a challenge for theoretical models at these early epochs. In this work, we compare the observational properties of astrop

Ranit Das, Marie Hein, Gregor Kasieczka, Michael Krämer

An enormous amount of R&D effort has resulted in many new resonant anomaly detection methods being proposed in recent years. However, the vast majority of previous R&D studies have suffered from two limitations: they have focused on a very small set of simulated signal benchmark models; and they have either used small sets of carefully crafted high-level jet

Sébastien Labbé, Peter Selinger

We present a simple construction of hat tilings. The construction can be carried out by superimposing a triangular grid on a specially colored image and reading off the orientation of the tiles. We show that our construction produces valid hat tilings, and conversely, in an appropriate sense that is made precise in the paper, that every valid hat tiling can

Veronica Bitonti, Emma Hogan, Tommy Walker Mackay

Let $n(k_1, k_2)$ be the least integer $n$ such that there exists a graph on $n$ vertices in which every vertex is contained in both a clique of size $k_1$ and an independent set of size $k_2$. Recently, Feige and Pauzner showed that ${n(k, k) \geq 4k-O(k^\frac{2}{3})}$, and conjectured that $n(k,k)=4k-4$. We prove this conjecture, and also establish the opt

Emma Jarvis, Ting S. Li, Sergey E. Koposov, Raymond G. Carlberg

GD-1 is among the longest, coldest stellar streams in the Milky Way, making it an ideal target for probing dark matter substructure through dynamical heating. We present a catalog of 608 spectroscopically confirmed GD-1 members from the first three years of Dark Energy Spectroscopic Instrument (DESI) observations. This constitutes the largest homogeneous spe

João Paulo Pinheiro, Salvador Urrea

The determination of leptonic CP violation is a primary goal of future long-baseline neutrino experiments such as DUNE and T2HK. The extraction of $\delta_{\mathrm{CP}}$ relies on the near-to-far extrapolation and on the assumed knowledge of the cross-section ratios $\sigma_{\nu_e}/\sigma_{\nu_\mu}$ and $\sigma_{\bar{\nu}_e}/\sigma_{\bar{\nu}_\mu}$, which ar

Sameer Dambal, Eric R. Bittner

This work investigates the emergent thermalization regimes in a chaotic Tavis-Cummings (TC) model and their implications in quantum spectroscopy. While the TC model is a cornerstone of cavity quantum electrodynamics, traditional treatments often overlook many-body effects that arise in the thermodynamic limit. We utilize the Eigenstate Thermalization Hypothe

Mathieu Giroux, Sebastian Mizera, Giulio Salvatori

We present SubTropica, a Mathematica package that performs symbolic integration of multi-polylogarithmic integrals using recent advances in tropical geometry. It focuses on the class of linearly-reducible Euler integrals, such as Feynman integrals, and expands them using a tropical subtraction scheme. The engine behind it is HyperIntica, a native Mathematica

Josu Hernández-García, Jacobo López-Pavón, Salvador Urrea

Upcoming long-baseline neutrino oscillation experiments such as DUNE aim to achieve unprecedented precision, but their physics reach is ultimately constrained by systematic uncertainties in neutrino flux predictions and neutrino-nucleus cross sections. These limitations are especially critical for new-physics searches in neutrino oscillations at the near det

Maria Werhahn, Christoph Pfrommer, Philipp Girichidis, Joseph Whittingham

Radio continuum observations are widely used to study cosmic ray (CR) electron populations and transport processes in star-forming galaxies, but their interpretation relies on several simplifying assumptions. Here, we revisit three common assumptions: that some vertical radio profiles can be explained by CR advection alone, that radio spectra directly trace

Lukas Hof, Pavel Kroupa, Gerhard Hensler, Jan Pflamm-Altenburg

Semi-analytical evolution models of galaxies are a useful and computationally inexpensive tool for fast assessment of individual properties and their evolution. In this work, specifically the influence of a metallicity and star-formation rate (SFR) dependent galaxy-wide stellar initial mass function (IGIMF) on the self-regulation of star-formation in a galax

Ruohan Liu, Shukang Yin, Tao Wang, Dong Zhang

Paralinguistic cues are essential for natural human-computer interaction, yet their evaluation in Large Audio-Language Models (LALMs) remains limited by coarse feature coverage and the inherent subjectivity of assessment. To address these challenges, we introduce SpeechParaling-Bench, a comprehensive benchmark for paralinguistic-aware speech generation. It e

Hyeonwoo Kim, Jeonghwan Kim, Kyungwon Cho, Hanbyul Joo

Recent advances in video generative models enable the synthesis of realistic human-object interaction videos across a wide range of scenarios and object categories, including complex dexterous manipulations that are difficult to capture with motion capture systems. While the rich interaction knowledge embedded in these synthetic videos holds strong potential

Clifford Taubes, Yingying Wu

We describe novel local singularity models for $\mathbb Z/2$ harmonic 1-forms, self-dual 2-forms and spinors in dimension 4. These models are homogeneous versions on $\mathbb{R}^4$ whose singular sets are cones on the 1-skeletal of certain regular 4-dimensional polytopes.

Jie Gu, Jue Hou, Yunfeng Jiang

We apply harmonic analysis to study the $T\bar{T}$-deformed torus partition function. We first express the CFT partition functions in terms of Maass waveforms, including the Eisenstein series and cusp forms. These basis functions turn out to deform in a very simple way under the $T\bar{T}$-deformation. The spectral decomposition provides a numerically stable

Koki Okada, Kenta Kasai

We construct a quantum low-density parity-check code family from a length-$512$ Calderbank--Shor--Steane base matrix pair. The base pair is permutation-equivalent to the known SPC(3) product CSS code, and the present affine-coset description gives a direct proof that both Tanner graphs are $(3,8)$-regular with girth $8$. The base code has parameters $[[512,1

Benjamin K. Gutierrez, Yingchu Xu, Nicolas Englebert, Rithvik Ramesh

Optical frequency combs have revolutionized precision science and technology, yet their nanophotonic implementations have failed to simultaneously achieve high efficiency, power, and coherence. Optically driven microcombs provide broad and stable spectra but low usable power, whereas active comb generators, including mode-locked lasers, can be efficient yet

Bernhard Haeupler, Slobodan Mitrović, Srikkanth Ramachandran, Wen-Horng Sheu

This paper proves that a wide class of local search algorithms extend as is to the fully dynamic setting with an adaptive adversary, achieving an amortized $\tilde{O}(1)$ number of local-search steps per update. A breakthrough by Moser (2009) introduced the witness-tree and entropy compression techniques for analyzing local resampling processes for the Lov\'

Zhaofeng Wu, Shiqi Wang, Boya Peng, Anuj Goyal

Modern language models demonstrate impressive coding capabilities in common programming languages (PLs), such as C++ and Python, but their performance in lower-resource PLs is often limited by training data availability. In principle, however, most programming skills are universal across PLs, so the capability acquired in one PL should transfer to others. In

Yupeng Zheng, Xiang Li, Songen Gu, Yuhang Zheng

Recent advances in Vision-Language-Action (VLA) models have opened new avenues for robot manipulation, yet existing methods exhibit limited efficiency and a lack of high-level knowledge and spatial awareness. To address these challenges, we propose PokeVLA, a lightweight yet powerful foundation model for embodied manipulation that effectively infuses vision-

Mikko Lempinen, Joni Kemppainen, Niklas Raesalmi

As artificial intelligence (AI) systems are increasingly deployed across critical domains, their security vulnerabilities pose growing risks of high-profile exploits and consequential system failures. Yet systematic approaches to evaluating AI security remain underdeveloped. In this paper, we introduce AVISE (AI Vulnerability Identification and Security Eval