April 2026 arXiv papers — page 35

Haosong Xiao, Yamini Ramesh, Rishabh Shukla, Swarat Sarkar

In this paper, we report the world's first infrastructure-guided communication-enhanced road crack detection pipeline that is effective and implementable on passenger vehicles. We first design a customized communication protocol to transmit the region of interest from the infrastructure to the vehicle. With proper camera image processing (e.g., dynamic cropp

Francisco Barriga, Patrick Concha, Nelson Merino, Evelyn Rodríguez

In this work, we construct a three-dimensional non-relativistic Chern--Simons supergravity theory with both curvature and torsion within the Mielke--Baekler framework. We show that a consistent non-relativistic supergravity formulation requires starting from a $\mathcal{N}=2$ supersymmetric extension of the Mielke--Baekler algebra and implementing a non-rela

Tanu Raghav, Daniel Guerrero, Uttara Tipnis, Julie Sara Benny

Functional connectivity varies across individuals due to genetic and environmental factors, yet classical twin models typically confound non-shared environment with measurement error and are largely limited to resting-state analyses. We hypothesized that: i) explicitly modeling measurement error from repeated fMRI sessions enables more accurate application o

Wei-Qi Fan, Yi Liao, Xiao-Dong Ma

Nucleon decays into a lepton and two pseudoscalar mesons represent key channels for probing baryon number violation, complementing conventional two-body modes. In this Letter, we model-independently correlate two- and three-body processes within the framework of low-energy effective field theory, performing a global analysis that avoids single-operator-domin

Daniel Romero Schellhorn, Till Mossakowski

ULLER (Unified Language for LEarning and Reasoning) offers a unified first-order logic (FOL) syntax, enabling its knowledge bases to be used directly across a wide range of neurosymbolic systems. The original specification endows this syntax with three pairwise independent semantics: classical, fuzzy, and probabilistic, each accompanied by dedicated semantic

Md All Shahria, Sanjeda Dewan Mithila, Touhid Alam, Mohammad Sakib Mahmood

The widespread adoption of social media has heightened interest in its psychological effects, particularly on mental health indicators such as anxiety, depression, loneliness, and sleep quality, as these platforms increasingly influence social interactions and well-being. Although previous research has examined correlations between social media use and menta

Catherine O'Brien, Gerard Sant, Mathias Müller, Sarah Ebling

Many sign language translation (SLT) systems operate on pose sequences instead of raw video to reduce input dimensionality, improve portability, and partially anonymize signers. The choice of pose estimator is often treated as an implementation detail, with systems defaulting to widely available tools such as MediaPipe Holistic or OpenPose. We present a syst

Yuxing Tian, Fengran Mo, Zhiqi Huang, Weixu Zhang

Large Language Models (LLMs) have recently been explored as fine-grained zero-shot re-rankers by leveraging attention signals to estimate document relevance. However, existing methods either aggregate attention signals across all heads or rely on a statically selected subset identified by heuristic rules. This solution can be suboptimal because the informati

Matthias Kellner, Teitur Hansen, Thomas Bligaard, Karsten Wedel Jacobsen

Machine-learning models of atomic-scale interactions achieve the accuracy of the quantum mechanical calculations on which they are trained, but at a dramatically lower computational cost. Their predictions can be made trustworthy by uncertainty quantification techniques that estimate the residual error relative to their reference. These errors, however, do n

Xincheng Cao, Haochong Chen, Bilin Aksun-Guvenc, Levent Guvenc

Reverse parking maneuvering of a vehicle with trailer system is a difficult task to complete for human drivers due to the multi-body nature of the system and the unintuitive controls required to orientate the trailer properly. The problem is complicated with the presence of other vehicles that the trailer and its connected vehicle must avoid during the rever

Tapas Mondal, Debdulal Ghosh, Zai-Yun Peng, Yong Zhao

In this article, we develop an efficient algorithm based on three special variants of the nonlinear conjugate gradient method, namely, the Polak--Ribiere--Polyak, Hestenes--Stiefel, and Liu--Story schemes for computing Pareto critical points in unconstrained interval-valued multiobjective optimization problems. The proposed algorithm incorporates a Wolfe lin

Junlin Wu, Erqi Xu, Qihui Lin, Jiaqing Yue

We develop a general theory of crystal truncation rod (CTR) scattering from vicinal surfaces with a coherently strained heteroepitaxial film. The formalism incorporates film-induced interference fringes, full elastic lattice distortion, terrace ordering, surface reconstruction, and real-time growth evolution within a unified description. Comparison between N

Victor Henner, Alexander Nepomnyashchy, Tatyana Belozerova

We investigate the spin dynamics of a dipole-coupled system by comparing a direct solution of the Schrodinger equation for quantum spins with simulations of classical spins. Although classical spins have long been used in microscopic spin dynamics simulations, we demonstrate that their results differ significantly from those of quantum spins. Using Free Indu

Lixian Chen, Mingxuan Huang, Yanhui Chen, Junyi Lin

Vision--language models can face asymmetric visual and textual shifts at deployment. These shifts expose a multimodal failure mode in which an unreliable branch remains overconfident, dominates fusion, and causes entropy-based test-time adaptation to sharpen an incorrect prediction. We model this behavior as doubly stochastic posterior mixing and cast adapta

Zinan Zhang, Xinning Gui, Yubo Kou

Emerging extended reality technologies are reshaping how children play, learn, and socialize. Yet, they also present serious safety risks. Gaming, a primary form of entertainment for children, is also one of the key applications of XR. While XR platforms offer immersive and engaging gaming experiences, recent news has highlighted safety concerns such as car

Chen Chaoran, Zhang Yuhao, Pan Zhiwen, Liu Nan

This paper investigates a joint hybrid digital-analog beamforming and trajectory design for a cell-free multi-static integrated sensing and communication (ISAC) system supported by multiple unmanned aerial vehicles (UAVs). Specifically, these UAVs cooperatively serve ground users and perform multi-static sensing to detect the target. We formulate a weighted

Dazhuang Liu, Yanqi Qiao, Rui Wang, Kaitai Liang

Object detection (OD) is critical to real-world vision systems, yet existing backdoor attacks on detection transformers (DETRs) for OD tasks rely on patch-wise triggers optimized at fixed locations with minimal perturbations. Such attacks overlook that backdoor triggers in the real world may appear at different sizes, fields of view (FoVs), and locations in

Jia-Zheng Li, Stephen W. Bougher, Cheng Li, Erdal Yigit

Aphelion Thermospheric Polar Warming (TPW), first identified in 2024 by Mars Atmosphere and Volatile EvolutioN (MAVEN) observations, is a dynamical heating phenomenon in the Martian atmosphere that exists in the winter hemisphere near the aphelion solstice. Studying the formation mechanism of aphelion TPW will help us better understand the energy budget of t

Sebastian Cajas Ordóñez, Felipe Ocampo Osorio, Dax Enshan Koh, Rafi Al Attrach

We provide evidence of quantum kernel advantage under noiseless simulation in binary insurance classification on MIMIC-CXR chest radiographs using quantum support vector machines (QSVM) with frozen embeddings from three medical foundation models (MedSigLIP-448, RAD-DINO, ViT-patch32). We propose a two-tier fair comparison framework in which both classifiers

Mrinmay Medhi, Mami Deka, Krishna Saha, Vivek Baruah Thapa

HD~20794 is a nearby, bright, metal-poor G-type dwarf hosting a compact planetary system, including a super-Earth near the habitable zone. Its low stellar activity and the availability of precise radial-velocity and photometric data make it an excellent benchmark for studying stellar structure and chemical abundances in low-metallicity planet-hosting stars.

Ioannis Emmanouil

If $(A_n)_n$ is a decreasing filtration of a module $A$ and $\widehat{A} = \lim_n A/A_n$, then $\lim^1_n A_n$ is identified with the cokernel of the canonical map $A \longrightarrow \widehat{A}$. In this note, we show that any $\lim^1$-group is canonically of that form: For any inverse sequence of modules $(X_n)_n$ there exists an inverse sequence $(A_n)_n$

Jingyi Chao, Kun Xu

We investigate the dynamics and mass spectra of charged pseudoscalar ($\pi^+$) and vector ($\rho^+$) mesons in a background magnetic field at finite temperature using the two-flavor Nambu-Jona--Lasinio (NJL) model. By employing a quark propagator that isolates the Schwinger phase from its Landau level expansion, we formulate an exact non-commutative phase-sp

Haruka Sugai

Every homogeneous manifold of negative curvature is known to be isometric to a Lie group with a left invariant metric. We define an SNC-algebra to be a Lie algebra which admits an inner product of strictly negative curvature. In the author's joint paper in 2022, we classified SNC-algebras in dimension four. In this article, we classify SNC-algebras in dimens

Lidia Losavio, Luca Persia, Madan Sathe, Dimosthenis Pasadakis

Technological advancements in cryptocurrency markets have increased accessibility for investors, but concurrently exposed them to the risks of market manipulations. Existing fraud detection mechanisms typically rely on machine learning methods that treat each financial asset (i.e., token) and its related transactions independently. However, market manipulati

Wenke Ren, Hengxiao Guo, Wenwen Zuo, Xiaoman Zhang

Vision-language models (VLMs) are increasingly proposed as general-purpose tools for scientific data interpretation, yet their reliability on real astronomical observations across diverse modalities remains untested. We present AstroVLBench, a comprehensive benchmark comprising over 4,100 expert-verified instances across five tasks spanning optical imaging,

Marco A. Gallegos-Herrada, Vianey Leos-Barajas, Jeffrey S. Rosenthal

Bayesian inference in hidden Markov models (HMMs) can be challenging due to the presence of multimodality in the likelihood function, and consequently in the joint posterior distribution, even after correcting for label switching. The parallel tempering (PT) algorithm, a state-space augmentation method, is a widely used approach for dealing with multimodal d

Yuta Baba, Keiji Yanai

Single-image point cloud reconstruction must infer complete 3D geometry, including occluded parts, from a single RGB image. While diffusion-based reconstructors achieve high accuracy, they typically require many denoising iterations, resulting in slow and expensive inference. We propose Point-MF, a Mean-Flow-based framework for low-NFE single-image point clo

Niloufar Dadkhah, Walter R. L. Lambrecht

Group-V monolayer materials exhibit intriguing electronic and optical properties, influenced by their unique crystal symmetries and structural phases. In this work, we study arsenic monolayers, investigating their electronic and optical properties across different phases, including planar, and puckered forms, using density functional theory (DFT) and quasi-p

Yuye Wu, Hong-Bo Jin

We study adjacent Kerr quasinormal-mode overtones under a spin scan with overtone labels held fixed, using a public Leaver-type solver on a uniform grid. The observable is the modulus of the complex-frequency separation between neighbors; its minima are analyzed through the spin derivative of the squared separation, which supplies a smooth real diagnostic wi

Hanlin Tang, Kidae Shin, Ashwin K. Boddeti, Sebastian P. Horvath

Rare earth ion (REI)-doped oxide thin films are attractive for the application of quantum interconnects due to their stable optical levels and scalability$^{1-3}$. Among them, Er$^{3+}$ doped CaWO$_{4}$ is promising because it possesses narrow optical linewidth transitions and a long spin coherence time$^{4-6}$. The electron spin coherence is limited at high

Simon Rossel, Wentao Zhang, Hassan A. Hafez, Savio Fabretti

Many components for terahertz (THz) optical filtering are mechanically fragile and are hard to produce with large aperture, making them unsuitable for applications where larger THz beam diameter is required. In this work, the THz optical properties of industrial-grade, readily available and inexpensive woven wire meshes are studied using THz time-domain spec

Phat T. Tran-Truong, Xuan-Bach Le

Large language model (LLM) agents increasingly operate as sequential software systems, but their reliability is often summarized by scalar benchmark metrics. Metrics such as pass$@k$, pass$^k$, and the reliability decay curve (RDC) are useful summaries, but they do not identify the success-time distribution being estimated, test whether traces support that d

Omar Benhar

Low-energy neutrino interactions with isolated nucleons are accurately described by the effective theory based on Fermi's groundbreaking description of neutron $\beta$-decay. On the other hand, the extension of this scheme to the case of neutrino interactions with nuclear matter -- the understanding of which is critical for the description of a variety of as

Haoxiao Wang, Antao Xiang, Haiyang Sun, Peilin Sun

Diffusion models are primarily trained for image synthesis, yet their denoising trajectories encode rich, spatially aligned visual priors. In this paper, we demonstrate that these priors can be utilized for text-conditioned semantic and open-vocabulary segmentation, and this approach can be generalized to various downstream tasks to make a general-purpose di

Wei Tang, Gunnar Möller, Frank Verstraete, Laurens Vanderstraeten

The Hamiltonian for a system of itinerant particles on a two-dimensional lattice in a uniform magnetic field reduces the translational symmetry to a magnetic translation group, because of the need to choose a particular gauge for the vector potential. Nonetheless, in many situations all physical observables of the ground state remain entirely translation inv

Sara Billey, Herman Chau, Kevin Liu

The higher Bruhat orders are partial orders that generalize the weak order on the symmetric group $S_n$, and the second higher Bruhat order is a poset on commutation classes of reduced words for the longest element in $S_n$, where covering relations correspond to braid relations. Constructing analogs in other settings is an area of recent interest, and we pr

Bikram Keshari Behera, Rhitabrata Bhattacharyya, Shyamal Biswas

We have analytically determined attenuation constant, phase constant, and reflectivity of Drude metals over the entire frequency range ($0<ω<\infty$) for an incident electromagnetic (plane) wave, within a single framework of classical electrodynamics, taking into account bound charges and currents in the background. We have compared our result with existing

Niko Moeller-Grell, Shihao Shenzhang, Zhangshu Joshua Jiang, Richard JB Dobson

The Observational Medical Outcomes Partnership Common Data Model (OMOP CDM), maintained by the Observational Health Data Sciences and Informatics (OHDSI) collaboration, enabled the harmonisation of electronic health records data of nearly one billion patients in 83 countries. Yet generating real-world evidence (RWE) from these repositories remains a manual p

Tsutomu T. Takeuchi

We develop a measure-theoretic framework for galaxy evolution in which galaxy populations are described as probability measures on a state space. Galaxy evolution is represented as the time evolution of a measure $\nu_t$, governed by the sum of a continuous transport term and a jump operator. The transport term describes internal galaxy evolution, while the

Petr A. Golovach, Diptapriyo Majumdar, Saket Saurabh

Given a connected undirected graph $G$, a spanning tree is a subgraph $T$ of $G$ such that $V(T) = V(G)$ and $T$ is a tree. A collection of $\ell$ spanning trees $T_1,\ldots,T_\ell$ is pairwise $k$-diverse if for every $i \neq j$, $|E(T_i) \triangle E(T_j)| \geq k$. Given a connected undirected graph $G$ and integers $p, q, k, \ell$, Leaf & Internal-Constrai

B. Vaia, S. T. Zeegers, I. Abril-Cabezas, E. Costantini

Context. High-resolution X-ray spectroscopy offers a powerful tool to investigate the physical and chemical properties of dust grains, especially through the analysis of absorption edges of elements such as oxygen, magnesium, silicon, and iron, which are the main constituents of interstellar dust. In all previous X-ray studies, these absorption edges have be

Steven Lapp, Marina Tvalavadze

We introduce the Limiter, a universal extension of the real numbers and of the limit functional that assigns a canonical limit in an enlarged space to every real sequence. Motivated by generalized summation methods such as Borel summation and Ramanujan's assignments to divergent series, we require our extension to respect classical limits and assign limits i

Luqiao Xu

The additive structure of $\mathbb{F}_1$-modules (in the sense of Segal's $\Gamma$-sets) differs fundamentally from that of abelian groups: addition is encoded through a family of $n$-ary hyper-operations that are multivalued and do not satisfy classical associativity. We establish a \emph{law of generalized associativity} showing that, despite this failure

Fei Li, Qingguo Hong, Ming Tang, Liuqiang Zhong

We propose, analyze, and numerically validate a correction adaptive two-grid finite element method (CAT-GFEM) for nonselfadjoint or indefinite elliptic problems. In contrast to the adaptive two-grid finite element method (ATGFEM) of Li and Zhang [SIAM J. Sci. Comput., 43 (2021), pp. A908-A928], which is restricted to symmetric positive-definite problems, the

J. Durech, D. Vokrouhlicky, P. Pravec, K. Hornoch

On April 13, 2029, the asteroid Apophis will pass near Earth at a geocentric distance of about 38,000 km. Numerical models have suggested that the post-encounter spin state will critically depend on the orientation of Apophis during the flyby. We aim to determine the spin state of Apophis from its photometric observations collected during two apparitions in

Alexander Moretó

This article is essentially an English translation of a paper of mine, published in \emph{La Gaceta de la RSME}. Its aim is to present, for a broad mathematical audience, a research programme in local representation theory that goes beyond the classical restrictions to characters of $p'$-degree, characters of height zero, and blocks of abelian defect. The fi

Xihang Wang, Zihan Wang, Chengkai Huang, Quan Z. Sheng

Multimodal Retrieval-Augmented Generation (MRAG) addresses key limitations of Multimodal Large Language Models (MLLMs), such as hallucination and outdated knowledge. However, current MRAG systems struggle to distinguish whether retrieved multimodal data truly supports the semantic core of an answer or merely provides superficial relevance. Existing metrics o

Mihail Bogojeski, Muhammad R. Hasyim, Leslie Vogt-Maranto, Klaus-Robert Müller

Machine-learning interatomic potentials (MLIPs) have enabled molecular dynamics at near ab initio accuracy, yet remain limited to energies and forces by construction, leaving electronic observables such as dipole moments and polarizabilities inaccessible. We introduce DenSNet, a density-first approach to machine-learned electronic structure that learns the H

Bowen Jian, Rongjie Yu, Hong Wang, Liqiang Wang

Driving in compliance with traffic laws and regulations is a basic requirement for human drivers, yet autonomous vehicles (AVs) can violate these requirements in diverse real-world scenarios. To encode law compliance into AV systems, conventional approaches use formal logic languages to explicitly specify behavioral constraints, but this process is labor-int

Zhihan Zhang, Lizi Liao

Chart-to-code generation converts a chart image into an executable plotting script, enabling faithful reproduction and editable visualizations. Existing methods are largely Python-centric, limiting practical use and overlooking a critical source of supervision: the same chart can be expressed by semantically equivalent scripts in different plotting languages

Michael Tryfan Matthews, Anssi Kanervisto, Jakob Foerster, Pierluca D'Oro

Recent work in hierarchical reinforcement learning has shown success in scaling to billions of timesteps when learning over a set of predefined option reward functions. We show that, instead of using a single reward function per option, the reward functions can be effectively used to induce a space of behaviours, by letting the controller specify linear comb

L. A. Machado, N. D. Chavda, B. Chatterjee, M. A. Caracanhas

We investigate the nonequilibrium dynamics of a two-dimensional rotating Bose gas confined in a symmetric anharmonic trap, employing the multiconfigurational time-dependent Hartree method for bosons (MCTDHB). We study states ranging from vortex-free configurations to multicharged (giant) vortices, prepared by tuning the rotation frequency, and analyze their

Mauricio Achigar

Building on the author's earlier work on topological and abstract expansivity, this paper introduces and explores the notion of algebraic expansivity for endomorphisms of abelian groups. We analyze the fundamental properties of this algebraic analogue, establish its relationship with Weiss's algebraic entropy, and prove that positively expansive epimorphisms

Tomas Kocak, Gergely Neu, Michal Valko, Remi Munos

We consider online learning problems under a partial observability model capturing situations where the information conveyed to the learner is between full information and bandit feedback. In the simplest variant, we assume that in addition to its own loss, the learner also gets to observe losses of some other actions. The revealed losses depend on the learn

Karim S. Elsayed, Amr Rizk

At the core of the quantum Internet lie quantum repeaters that enable remote end-to-end entanglement generation. Fundamentally, the entanglement generation rate and fidelity of quantum repeaters constitute the bottleneck for end-to-end performance. To achieve high rates, quantum repeaters employ quantum memory multiplexing. In a high-rate standard repeater,

Ermu Qiu, Tianyi Chen, Jun Gao, Xing Wei

Hybrid queries, which combine vector nearest neighbor searches with scalar predicates, represent a fundamental challenge in managing vector databases. Existing methods often restrict the number of vector columns involved or the complexity of scalar predicates, thereby limiting their flexibility in handling diverse query patterns. Moreover, these approaches t

Steven Szachara, Sheeraja Rajakrishnan, Dylan Jay Van Allen, Jason Pollack

Quantum error mitigation (QEM) is essential for extracting reliable results from near-term quantum devices, yet practical deployments must balance mitigation strength against runtime overhead under time-varying noise. We introduce \emph{GSC-QEMit}, a telemetry-driven, \textbf{context--forecast--bandit} framework for \emph{adaptive} mitigation that switches b

Xingyan Chen, Yuxin Su, Zishan Su, Yang Yu

Cloud computing platforms offer elastic scaling, managed infrastructure, and pay-per-use pricing, but moving existing monolithic backends to them remains a difficult software engineering task. In practice, the migration requires coordinated changes to program structure, source code, infrastructure configuration, and cloud-specific design decisions, and these

Yihong Zhou, Hongtai Zeng, Thomas Morstyn

Coordinating large populations of grid-edge devices requires learning methods that remain fully decentralised in deployment while still respecting three-phase AC distribution-network physics. This paper proposes gradient-based multi-agent proximal learning (GradMAP) to address this challenge. GradMAP trains independent neural-network policies for each agent

Taeyoon Kim, Kyumin Kim, Kyunghwan Kim, Hayoung Kim

Cloud vendors offer discounted spot instances to maximize surplus resource utilization, but these instances are subject to the risk of sudden interruption. Traditional pricing datasets have been employed to predict this risk, yet recent policy changes by cloud vendors have diminished their effectiveness. To promote spot instance usage, public cloud vendors p

Kalyani P. Pande, Evan Yang, Bryan Zhu, Sandeep K. Mallipattu

Progression to dialysis or end-stage renal disease is a rare but clinically important outcome. Clinicians need evidence on how medication exposures influence downstream risk. We constructed a fixed-window EHR cohort (90-day observation, 730-day prediction; N=81401; dialysis/ESRD prevalence: 1.1%) and modeled sequences of diagnoses, procedures, and medication

Christopher Blier-Wong, Jean-Gabriel Lauzier

Regulatory and contractual constraints on individual exposures are standard in insurance and reinsurance markets, but a poorly designed constraint can distort the economic incentives of risk-averse agents. In the unconstrained problem, the classical comonotonic improvement theorem guarantees Pareto-optimal allocations that are nondecreasing in the aggregate

Alexandra Carpentier, Michal Valko

In many areas of medicine, security, and life sciences, we want to allocate limited resources to different sources in order to detect extreme values. In this paper, we study an efficient way to allocate these resources sequentially under limited feedback. While sequential design of experiments is well studied in bandit theory, the most commonly optimized pro

Alessio Sordo, Lingxiao Du, Meeka-Hanna Lenisa, Evgeny Bogdanov

The increasing reliance on Large Language Models (LLMs) across diverse sectors highlights the need for robust domain-specific and language-specific evaluation datasets; however, the collection of such datasets is challenging due to privacy concerns, regulatory restrictions, and the time cost for manual creation. Existing automated benchmarking methods are of

Jinghao Shi, Mengqi Lei, Kunliang He, Yun Li

RGB-Thermal (T) crowd counting aims to integrate visible-spectrum and thermal infrared information to improve the robustness of crowd density estimation in complex scenes. Although existing studies generally improve counting accuracy through cross-modal feature fusion, most current methods rely on implicit cross-modal fusion strategies and lack explicit mode

Nay Myat Min, Long H. Pham, Jun Sun

Large language models deployed at runtime can misbehave in ways that clean-data validation cannot anticipate: training-time backdoors lie dormant until triggered, jailbreaks subvert safety alignment, and prompt injections override the deployer's instructions. Existing runtime defenses address these threats one at a time and often assume a clean reference mod

Raúl López-March, Andrés Macho-Ortiz, Francisco Javier Fraile-Peláez, José Capmany

Analog Programmable-Photonic Computation (APC) leverages programmable integrated photonics (PIP) to perform high-speed matrix operations using optical waves. However, the continuous nature of optical waves that implement the analog bits or anbits - the fundamental unit of information in APC - makes computational results intrinsically sensitive to physical no

Ben M. Andrew, Louise A. Dennis, Michael Fisher, Marie Farrell

Systems deployed for long periods of time in dynamic environments may experience performance degradation that affects timing guarantees, even when their functional behaviour remains unchanged. In the design and verification of critical systems, such timing guarantees are often expressed using Metric Temporal Logic (MTL). Under degradation, these specificatio

Santiago Guzmán Pro, Jakub Rydval

In 2008, Bodirsky and Grohe showed that for every $\Pi_n^{\mathrm{P}}$-level of the Polynomial Hierarchy (PH) there are $\omega$-categorical Constraint Satisfaction Problems (CSPs) complete for this level. We show that, in fact, there are $\omega$-categorical CSPs complete for any level of the PH. To this end, we use a recent result of Bodirsky, Kn\"{a}uer,

Yuchen Zhang, Pinjun Zheng, Tareq Y. Al-Naffouri

In large antenna arrays, hardware power consumption becomes a dominant design constraint, making energy efficiency (EE) a first-class objective alongside spectral efficiency (SE). Microwave linear analog computer (MiLAC)-aided beamforming, whose front end is a passive reciprocal stream-to-antenna network, addresses this tension by reducing the active radio-f

Franziska Kaltenberger, Wei-Ling Chen, Enkeleda Thaqi, Enkelejda Kasneci

Remote and webcam-based eye tracking in multi-line reading suffers from various noise factors and layout ambiguity, precisely where real-time reading support needs reliable, per-fixation line assignment. Prior work largely addresses this challenge post hoc or by restricting behavior (e.g., disallowing re-reading), undermining interactive use. We propose CONF

Michal Valko, Alexandra Carpentier, Rémi Munos

We study the problem of global maximization of a function f given a finite number of evaluations perturbed by noise. We consider a very weak assumption on the function, namely that it is locally smooth (in some precise sense) with respect to some semi-metric, around one of its global maxima. Compared to previous works on bandits in general spaces (Kleinberg

Sumanta Bhattacharyya, Francine Chen, Scott Carter, Yan-Ying Chen

Large Language Models (LLMs) excel academically but struggle with social intelligence tasks, such as creating good compromises. In this paper, we present methods for generating empathically neutral compromises between two opposing viewpoints. We first compared four different prompt engineering methods using Claude 3 Opus and a dataset of 2,400 contrasting vi

Minh-Hieu Do, François Madiot, Karim Ammar, Nicolas Gérard Castaing

Physics-Based Loss Scaling (PBLS) is introduced for Mixed-Formulation PINNs (MF-PINNs) applied to the neutron diffusion equation. In particular, we propose a new \textit{scaled} loss function based on the material cross sections, which is equivalent to the classical MF-PINN loss, but accelerates the convergence and improves accuracy of MF-PINNs. Several nume

Xifeng Li, Shuzhen Yang

Uncertainty is ubiquitous in real-world data, and the assumptions underlying classical linear regression models are often violated in practice. Inspired by the theory of sublinear expectation, we consider a linear regression model where the random intercept term has mean uncertainty and the error term has variance uncertainty. We develop a novel two-step app

Jorge Pellegrini

Digital travel platforms often operate multiple marketing journeys simultaneously, resulting in overlapping user exposures that bias the standard A/B lift estimation. Because traditional lift experiments assume treatment isolation, the observed lifts reflect only marginal effects and may substantially underestimate the total incremental impact of each journe

Ying-Tu Chen, Wei Hung, Bing-Shu Wu, Zhang-Wei Hong

Many sequential decision-making tasks involve optimizing multiple conflicting objectives, requiring policies that adapt to different user preferences. In multi-objective reinforcement learning (MORL), one widely studied approach} addresses this by training a single policy network conditioned on preference-weighted rewards. In this paper, we explore a novel a

CMS Collaboration

A search for Higgs boson (H) production in association with two vector bosons (V = W, Z) via vector boson scattering (VBS) is presented using proton-proton collision data collected at $\sqrt{s}$ = 13 TeV by the CMS experiment, corresponding to an integrated luminosity of 138 fb$^{-1}$. Events containing two forward jets consistent with VBS, a large-radius je

Samir Hamad

We discuss an example of a non-complete normed space with the Daugavet property such that the norm is G\^ateaux differentiable at every nonzero point. In contrast, we note that the dual norm of a normed space with the Daugavet property is not G\^ateaux differentiable at any point. Furthermore, we show that quasilacunary M\"untz spaces form a natural class of

Malcolm Fairbairn, William S. A. Shellard

Both scalar and vector dark matter can be produced during a cosmological first order phase transition if the dark matter is coupled to the field undergoing the transition. Both kinds of particle are also produced by the plasma through the normal freeze out scenario. For different dark matter masses, we identify the regions of parameter space where there are

Diego Candia-Rivera

This review proposes an integrative framework grounded on interoception and embodied AI-termed the interoceptive machine framework-that translates biologically inspired principles of internal-state regulation into computational architectures for adaptive autonomy. Interoception, conceived as the monitoring, integration, and regulation of internal signals, ha

Fiza Naseer, Javed Ali Khan, Muhammad Yaqoob, Alexios Mylonas

Context: Software vulnerabilities pose significant security threats to software systems, especially as software is increasingly used across many areas of daily life, including health, government, and finance. Recently, transformer-based models have demonstrated promising results in automatic software vulnerability identification due to their robust contextua

Veli Karakaya, Utku Boran Torun, Baykal Mehmet Uçar, Eray Tüzün

Automated code review (ACR) bots are increasingly used in industrial software development to assist developers during pull request (PR) review. As adoption grows, a key challenge is how to evaluate the usefulness of bot-generated comments reliably and at scale. In practice, such evaluation often relies on developer actions and annotations that are shaped by

Ni Yao, Xiangyu Liu, Shaojie Tang, Danyang Sun

Clinical fusion of Single Photon Emission Computed Tomography Myocardial Perfusion Imaging (SPECT MPI) and Computed Tomography Angiography (CTA) remains limited by cross-modality misregistration and reliance on manual landmarks, which can hinder accurate ischemia localization and lesion-level functional assessment. To address this issue, we propose a registr

Enrique Artal Bartolo, Pedro D. González Pérez, Manuel González Villa, Edwin León Cardenal

The holomorphy conjecture for suspensions of plane curve singularities and the holomorphy and monodromy conjectures for L\^e-Yomdin singularities of surfaces are proved. The first part of this paper provides formul{\ae} for the motivic and topological zeta functions for a family of hypersurfaces, including the suspensions by an arbitrary number of points and

Michael Mircea, Elisa Schmid, Jakob Droste, Kurt Schneider

Real-world Capstone Projects (RWCPs) are a key component of software engineering education, enabling students to develop software for external clients under authentic conditions. Their high ecological validity, combined with substantial variation in domains, technologies, and stakeholders, typically requires flexible and minimally prescriptive teaching appro

Vivek Kumar, Prasoon Suchandra, Jason Rom, Shivam Prajapati

We hypothesize that combining extreme turbulence with a minute reduction in surface tension $\sigma$ (surface tension of the liquid) using surfactant provides a simple and scalable route for controlling micron scale bubble size in gas--liquid systems. To test this, we generate high-intensity turbulence using a multiphase pump [turbulent intensity $\ge 40\%$;

Edyta Bogucka, Sanja Šćepanović, Daniele Quercia

AI risk assessment is the primary tool for identifying harms caused by AI systems. These include intersectional harms, which arise from the interaction between identity categories (e.g., class and skin tone) and which do not occur, or occur differently, when those categories are considered separately. Yet existing AI risk assessments are still built around i

Shubham Sawarkar, P Sangeerth, S Saharsh, Pushpak Jagtap

This paper presents a unified control framework for robust trajectory tracking and moving obstacle avoidance applicable to a broad class of mobile robots. By formulating a generalized kinematic transformation, we convert diverse vehicle dynamics into a strict feedback form, facilitating the design of a Sliding Mode Control (SMC) strategy for precise and robu

Junyao Ding, Xiaodian Chen, Xinyi Gao, Xiaoyu Tang

With the rapid development of time-domain surveys, the availability of massive light curve data offers new opportunities for studying stellar evolution and variable star classification, while simultaneously posing challenges for feature extraction and modeling. We present StarCLR, a contrastive pretraining framework for large-scale light curves. By construct

Yuqing Fu, Yimin Deng, Wanyu Wang, Yuhao Wang

Multi-hop Question Answering (MHQA) aims to answer questions that require multi-step reasoning. It presents two key challenges: generating correct reasoning paths in response to the complex user queries, and accurately retrieving essential knowledge in the face of potential limitations in large language models (LLMs). Existing approaches primarily rely on pr

Konrad Waldorf

Higher gauge theory for non-abelian structure 2-groups faces significant challenges when extending beyond the fake-flat sector, which suffers from limited applicability in physical models. A promising resolution involves equipping 2-groups with additional structure, known as adjustments. We present a comprehensive theory of adjusted connections on non-abelia

Dahlia Shehata, Ming Li

As LLM agents transition to autonomous digital coworkers, maintaining deterministic goal-directedness in non-linear multi-turn conversations emerged as an architectural bottleneck. We identify and formalize a systemic failure mode termed the Attention Latch in decoder-only autoregressive Transformers. This phenomenon, a behavioral manifestation of Informatio

V. M. Rivilla, D. San Andrés, M. Sanz-Novo, L. Colzi

In recent years, several aromatic molecules (benzene-based rings) have been detected in the cold molecular cloud TMC-1, with its CN-derivative, benzonitrile (c-C$_6$H$_5$CN), also identified in other nearby cold sources. However, observed abundances differ significantly from chemical model predictions, indicating an incomplete understanding of its chemistry

Xiaoyu Cheng, Benyamin Shnirman, Alexandra Köpf, Guangcanlan Yang

Strong coupling between atomic ensembles and high-quality optical cavities enables collective and nonlinear phenomena that are central to cavity quantum electrodynamics (cQED). Although many experiments have been performed on this topic, most of them have focused on cold atoms. Here, we experimentally demonstrate collective strong coupling between thermal ru

Geoffrey Deperle, Christine Fricker, Philippe Jacquet, Alessia Rigonat

We study the asymptotic behaviour of the distance to the first available parking slot in a recursive Manhattan street network endowed with a hyperfractal intensity structure, where slot-release events occur according to Poisson processes along the streets. We establish, by analysing the associated self-similar harmonic sums via Mellin-transform asymptotics,

Stephen S. -T. Yau, Qiwei Zhu, Huaiqing Zuo

The long-standing Nakai Conjecture concerns a very natural question: can differential operators detect singularities on algebraic varieties? On a smooth complex variety, it is well known that the ring of differential operators is generated by derivations. Nakai asked whether the converse holds: if the ring of differential operators is generated by derivation

Anastasios Giannopoulos, Sotirios Spantideas, Panagiotis Trakadas

The rapid proliferation of latency-sensitive and battery-constrained Internet-of-Things (IoT) applications has intensified the need for intelligent workload placement mechanisms across the Edge-Cloud computing continuum. In such environments, far-edge nodes must dynamically decide whether to execute workloads locally or offload them to neighboring nodes or t

Siavash Golkar, Jake Kovalic, Irina Espejo Morales, Samuel Sledzieski

Biological function emerges from coupled constraints across sequence, structure, regulation, evolution, and cellular context, yet most foundation models in biology are trained within one modality or for a fixed forward task. We present MIMIC, a generative multimodal foundation model trained on our newly curated and aligned dataset, LORE, linking nucleic acid

Jan-Christoph Schlage-Puchta, Christoph Schwerdt

We give a generalized and effective version of Bekehermes' improvement of Newman's Tauberian theorem. To do so we prove an effective version of the Riemann-Lebesgue Lemma for functions of bounded $p$-variation. We apply our Tauberian theorem to abstract analytic semigroups and prove a version of the prime number theorem as well as an estimate for Mertens' fu