March 2026 arXiv papers — page 16

Nivetha Jayakumar, Jonathan Pan, Shuo Wang, Bishow Paudel

Identification and quantification of myocardial scar is important for diagnosis and prognosis of cardiovascular diseases. However, reliable scar segmentation from Late Gadolinium Enhancement Cardiac Magnetic Resonance (LGE-CMR) images remains a challenge due to variations in contrast enhancement across patients, suboptimal imaging conditions such as post con

Ayda Nodel Hokmabadi, Mohamed Elhattab, Chadi Assi

This paper investigates energy efficiency (EE) optimization for an uplink multiuser system assisted by a movable-element reconfigurable intelligent surface (ME-RIS) and a base station equipped with movable antennas (MA-BS). We jointly optimize the uplink postcoder vectors, user transmit powers, RIS phase shift, and the positions of both the BS antennas and R

Adam Laabs

We present a first comparative pilot study of three t-norm operators -- Lukasiewicz (T_L), Product (T_P), and G\"odel (T_G) - as logical conjunction mechanisms in a neuro-symbolic reasoning system for EU AI Act compliance classification. Using the LGGT+ (Logic-Guided Graph Transformers Plus) engine and a benchmark of 1035 annotated AI system descriptions spa

Wenqing Liu, Xenia Miscouridou, Déborah Sulem

Existing spatio-temporal Hawkes process models typically rely on either parametric or semiparametric assumptions, limiting the model's ability to capture complex endogenous and exogenous event dynamics. We propose a fully Bayesian nonparametric framework for spatio-temporal Hawkes processes using additive Gaussian processes for the prior distributions on the

Arsham Gholamzadeh Khoee, Yinan Yu, Robert Feldt

Large pre-trained vision-language models like CLIP have transformed computer vision by aligning images and text in a shared feature space, enabling robust zero-shot transfer via prompting. Soft-prompting, such as Context Optimization (CoOp), effectively adapts these models for downstream recognition tasks by learning a set of context vectors. However, CoOp l

Athos Georgiou

Visual document understanding typically requires separate retrieval and generation models, doubling memory and system complexity. We present Hydra, a dual-head approach that provides both ColBERT-style late-interaction retrieval and autoregressive generation from a single vision-language model. A single LoRA adapter, trained only for retrieval, is toggled at

D. S. Smirnov, E. L. Ivchenko

We present a theory of polarized photoluminescence of triplet excitons in semiconductor nanocrystal ensembles with the random fine structure contributed by the electron-hole exchange and carrier-nuclear hyperfine interactions. The interaction parameters are assumed to be normally and isotropically distributed. In particular, the exchange interaction is descr

Zifan Peng, Mingchen Li

Personalized computer-use agents are rapidly moving from expert communities into mainstream use. Unlike conventional chatbots, these systems can install skills, invoke tools, access private resources, and modify local environments on users' behalf. Yet users often do not know what authority they have delegated, what the agent actually did during task executi

Tim Strohmeyer, Lucas Morin, Gerhard Ingmar Meijer, Valéry Weber

Automatically extracting chemical structures from documents is essential for the large-scale analysis of the literature in chemistry. Automatic pipelines have been developed to recognize molecules represented either in figures or in text independently. However, methods for recognizing chemical structures from multimodal descriptions (Markush structures) lag

Thilo Egenolf, Oliver Boine-Frankenheim

We present the development of a digital twin-based reconstruction framework for dielectric laser acceleration (DLA) based on machine-learning-assisted inversion of single-shot electron energy spectra. DLA as a promising candidate for compact electron accelerator designs using optical nearfields in dielectric nanostructures lacks on direct diagnostics on the

Quan Meng, Yujin Chen, Lei Li, Matthias Nießner

We present Seen2Scene, the first flow matching-based approach that trains directly on incomplete, real-world 3D scans for scene completion and generation. Unlike prior methods that rely on complete and hence synthetic 3D data, our approach introduces visibility-guided flow matching, which explicitly masks out unknown regions in real scans, enabling effective

Zhangqi Jiang, Zheng Sun, Xianfang Zeng, Yufeng Yang

Recent advances in image editing have enabled models to handle complex instructions with impressive realism. However, existing evaluation frameworks lag behind: current benchmarks suffer from narrow task coverage, while standard metrics fail to adequately capture visual consistency, i.e., the preservation of identity, structure and semantic coherence between

Rémi Van Boxem, Tom Barbette, Cristel Pelsser, Ramin Sadre

Automated bots now account for roughly half of all web requests, and an increasing number deliberately spoof their identity to either evade detection or to not respect robots.txt. Existing countermeasures are either resource-intensive (JavaScript challenges, CAPTCHAs), cost-prohibitive (commercial solutions), or degrade the user experience. This paper propos

Jeffrey Uhlmann

A new generalized matrix inverse is derived which is consistent with respect to arbitrary nonsingular diagonal transformations, e.g., it preserves units associated with variables under state space transformations, thus providing a general solution to a longstanding open problem relevant to a wide variety of applications in robotics, tracking, and control sys

Zhen Zhao, Cheng He, Baofeng Feng, Dmitry E. Pelinovsky

An algebraic soliton of the massive Thirring model (MTM) is expressed by the simplest rational solution of the MTM with the spatial decay of $\mathcal{O}(x^{-1})$. The corresponding potential is related to a simple embedded eigenvalue in the Kaup--Newell spectral problem. This work focuses on the hierarchy of rational solutions of the MTM, in which the $N$-t

Hyungrok Kim, Jonah Stalknecht

Positive geometry provides a geometric framework where physical observables are encoded as canonical forms associated to regions of kinematic space. In this paper we consider a generalisation to an infinite union of line segments, which allows us to capture canonical forms beyond rational functions. In the continuum limit of positive geometries, we show that

Feiyu Jia, Xiaojie Niu, Sizhe Yang, Qingwei Ben

Teleoperation is a key approach for collecting high-quality, physically consistent demonstrations for robotic manipulation. However, teleoperation for dexterous manipulation remains constrained by: (i) inaccurate hand-robot motion mapping, which limits teleoperated dexterity, and (ii) limited tactile feedback that forces vision-dominated interaction and hind

Gerardo Odriozola, Péter Gurin

We conducted replica exchange Monte Carlo simulations to investigate the phase diagram of identical hard rhombi systems in two dimensions. The rhombi shape varies from nearly square-like, as their minor angle a approaches 90 degrees, to needle-like, as it approaches 0 degrees. For angles near 90 degrees, we observe an isotropic fluid, a rhombatic fluid, a ro

Yu Han, Aaron Ceross

Medical device regulators in the United States(FDA), China (NMPA), and Europe (EU MDR) all use the language of risk, but classify devices through structurally different mechanisms. Whether these apparently shared concepts carry transferable classificatory signal across jurisdictions remains unclear. We test this by reframing explainable AI as an empirical pr

Linying Cheng, Haiye Guo

This paper investigates the shadowing properties in semi-hyperbolic systems. We introduce three classes of shadowing properties defined on families of manifolds, and prove that a semi-hyperbolic family possesses the $L^p$ bi-shadowing property, the limit bi-shadowing property, and the asymptotic bi-shadowing property under certain conditions. The proof strat

Francesco Vissani

Between 1933 and 1937, the treatment of relativistic spin-1/2 particles, initially rooted in Hole theory, evolved into the modern framework of quantum field theory. This paper reconstructs the crucial stages of that transition by examining the formal and physical progress of the numerous authors who shaped the field's modern formalism. This historical study

Pavel Šindelář, Dávid Slivka, Christopher Bouma, Filip Prášil

Every four years, the PISA test is administered by the OECD to test the knowledge of teenage students worldwide and allow for comparisons of educational systems. However, having to avoid language differences and annotator bias makes the grading of student answers challenging. For these reasons, it would be interesting to consider methods of automatic student

Vincent Maillot, Damian Rössler

In an article published in 1993, P. Colmez formulated a remarkable conjecture, which asserts that the Faltings height of a CM abelian variety can be computed as a linear combination of logarithmic derivatives of Artin $L$-functions. Noting that the Faltings height is an average of transcendental quantities summed over the embeddings of a number field of defi

Pablo D. Carrasco, Federico Rodriguez-Hertz

We give a proof, based on thermodynamic formalism, of a theorem in bounded cohomology extending a foundational result of Burger and Monod: if $\Gamma$ is an irreducible uniform lattice in a non-compact connected semisimple Lie group of real rank at least $2$, then for any finite-dimensional representation $\pi:\Gamma\to \operatorname{O}_N$, every $\pi$-quasi

Younes Javanmard, Tanmoy Pandit, Masoud Mardani

Transformer-based language models achieve strong performance across NLP tasks, but their quadratic parameter scaling with hidden dimension makes deployment on resource-constrained hardware expensive. We study Matrix Product Operator (MPO) decomposition as a principled compression method for transformers. MPO factorises weight matrices into chains of low-rank

Shuwen Xu, Yao Xu, Jiaxiang Liu, Chenhao Yuan

Agentic knowledge graph question answering (KGQA) requires an agent to iteratively interact with knowledge graphs (KGs), posing challenges in both training data scarcity and reasoning generalization. Specifically, existing approaches often restrict agent exploration: prompting-based methods lack autonomous navigation training, while current training pipeline

Ya Zhou, Tianxiang Hao, Ziyi Cai, Haojie Zhu

Low left ventricular ejection fraction (LEF) frequently remains undetected until progression to symptomatic heart failure, underscoring the need for scalable screening strategies. Although artificial intelligence-enabled electrocardiography (AI-ECG) has shown promise, existing approaches rely solely on end-to-end black-box models with limited interpretabilit

James Hornick, Dmitry E. Pelinovsky

We consider families of solitary waves in the Korteweg--de Vries (KdV) equation coupled with the linear Schr\"{o}dinger (LS) equation. This model has been used to describe interactions between long and short waves. To characterize families of solitary waves, we consider a sequence of local (pitchfork) bifurcations of the uncoupled KdV solitons. The first mem

S. R. Mudi, S. Anupam, V. Mourik, S. M. Frolov

Hybrid superconductor-semiconductor systems with large spin-orbit coupling are important platforms for realizing topological or triplet superconductivity. Planar Josephson junctions made using these materials are predicted to enter the topological state by tuning the phase difference between the two superconductors from 0 to $\pi$. The 0-$\pi$ transition can

Samira Abdelrahman, Hossam Farag

6G In-body Subnetworks (IBSs) represent a key enabler for supporting standalone eXtended Reality (XR) applications. IBSs are expected to operate as an underlay to existing cellular networks, giving rise to coexistence challenges when sharing radio resources with other cellular users, such as enhanced Mobile Broadband (eMBB) users. Such resource allocation pr

R. Alfaro, E. Anita-Rangel, M. Araya, J. C. Arteaga-Velázquez

Millisecond pulsars (MSPs) are observed to emit multi-wavelength radiation, from radio to GeV. Spider MSPs, which interact with their low-mass companion in close orbit (orbital periods $< 1$ day), may lead to strong intrabinary shocks that can further accelerate electron and positron pairs produced in the magnetosphere, possibly emitting very-high-energy (0.

Jędrzej Burkat, Sergii Strelchuk, Michał Studziński

We introduce Exchange Quantum Polynomial Time (XQP) circuits, which comprise quantum computation using only computational basis SPAM and the isotropic Heisenberg exchange interaction. Structurally, this sub-universal model captures decoherence-free subspace computation without access to singlet states. We show that XQP occupies an intermediate position betwe

S. Yu. Kirillov, V. V. Klinshov

Finite-size effects in the Kuramoto model are known to induce collective fluctuations even below the critical coupling, where the thermodynamic limit predicts complete asynchrony. While the shot-noise approach developed in our recent work accurately describes the power spectrum of these fluctuations for random frequency sampling, the present study reveals th

Anurag Ghosh, Srinivasa Narasimhan, Manmohan Chandraker, Francesco Pittaluga

We present LAD, a real-time language--action planner with an interruptible architecture that produces a motion plan in a single forward pass (~20 Hz) or generates textual reasoning alongside a motion plan (~10 Hz). LAD is fast enough for real-time closed-loop deployment, achieving ~3x lower latency than prior driving language models while setting a new learn

Loïc Balazi, Matthias Deiml, Daniel Peterseim

We propose a numerical homogenization method for scalar linear partial differential equations with rough coefficients that integrates classical coarse-scale solvers with quantum subroutines for fine-scale corrections. Inspired by the Localized Orthogonal Decomposition, we employ quantum local problem solvers to capture fine-scale features efficiently. Unlike

Ulrik Thinggaard Hansen, Frederik Ravn Klausen

Much recent rigorous study of the classical ferromagnetic Ising model has been powered by its graphical representations, such as the random current and loop O(1) model (high temperature expansion). In this paper, we prove uniqueness of Gibbs measures and exponential ratio weak mixing for the loop O(1) and random current models corresponding to the supercriti

Gaspar Mougin-Trichon, Veronique Boutou, Corinne Felix, David Jegouso

We report implementation and modelling of an efficient photon-triplets generation experiment based on a difference-frequency-mixing of two picosecond beams at 532 nm and 1491 nm in a type II phase-matched KTP crystal. The photon-triplets flux was measured as a function of the energy of the two incident beams using a coincidence protocol. A maximal flux of 11

Zhaoxiang Shen, Raúl I. Sosa, Stéphane P. A. Bordas, Alexandre Tkatchenko

We present a structured force reformulation of the many-body dispersion (MBD) model that enables a physically consistent decomposition of forces into pairwise components. By introducing a many-body correlation matrix that scales dipole--dipole interactions, we derive unified expressions for the MBD energy, force, and Hessian. This reformulation reveals a nat

Matthew Black, Robert V. Harlander, Jonas T. Kohnen, Fabian Lange

We demonstrate the use of the gradient flow combined with the short flow-time expansion (GF+SFTX) as a renormalization procedure for four-quark operator matrix elements and associated bag parameters relevant to neutral heavy-meson mixing ($\Delta Q=2$) and heavy-meson lifetimes ($\Delta Q=0$). Using six RBC/UKQCD 2+1-flavor domain-wall fermion ensembles, we

Matthew Black, Robert V. Harlander, Jonas T. Kohnen, Fabian Lange

We calculate the dimension-six $\Delta Q=0$ four-quark matrix elements describing heavy-meson lifetime ratios using the gradient flow with its short flow-time expansion as a renormalization procedure. On six RBC/UKQCD 2+1-flavor domain-wall fermion ensembles, we determine flowed bag parameters for physical charm and strange quarks and match to the $\overline

Léane Jourdan, Julien Aubert-Béduchaud, Yannis Chupin, Marah Baccari

Scientific writing is an iterative process that generates rich revision traces, yet publicly available resources typically expose only final or near-final versions of papers. This limits empirical study of revision behaviour and evaluation of large language models (LLMs) for scientific writing. We introduce EarlySciRev, a dataset of early-stage scientific te

Fábio Natali, Dmitry E. Pelinovsky, Shuoyang Wang

We study standing periodic waves modeled by the nonlinear Schrodinger equation with the intensity-dependent dispersion coefficient. Spatial periodic profiles are smooth if the frequency of the standing waves is below the limiting frequency, for which the profiles become peaked (piecewise continuously differentiable with a finite jump of the first derivative)

Nicolas Crampé, Quentin Labriet, Lucia Morey, Satoshi Tsujimoto

Finite families of biorthogonal rational functions and orthogonal polynomials of Racah-type are studied within a unified algebraic framework based on the meta Racah algebra and its finite-dimensional representations. These functions are identified as overlap coefficients between eigensolutions of generalized and standard eigenvalue problems posited on the re

Feng Nie, Zhixiu Ye, Sifa Xie, Shuang Wu

WikiKG90Mv2 in NeurIPS 2022 is a large encyclopedic knowledge graph. Embedding knowledge graphs into continuous vector spaces is important for many practical applications, such as knowledge acquisition, question answering, and recommendation systems. Compared to existing knowledge graphs, WikiKG90Mv2 is a large scale knowledge graph, which is composed of mor

J. M. P. Beunen, T. Lappan, P. Malgaretti, O. Aouane

Gas bubble transport through highly porous transport layers (PTLs) is a key process in electrochemical devices such as proton exchange membrane water electrolyzers, where bubbles generated at catalyst surfaces must migrate through complex porous networks. To understand this process, we focus on model systems, namely the motion of single, paired and multiple

Sarah Peluse, Kannan Soundararajan

Computations of Miller and Scheinerman suggest that the vast majority of the zeros appearing in the character table of the symmetric group are of a certain special type. While we cannot prove this, we resolve a conjecture arising in their paper concerning these zeros, and address a related question of Stanley.

Marek Kuchař, Michal Macek

We propose concrete protocols to realize quantum criticality due to excited-state quantum phase transitions (ESQPTs) experimentally in presumably the simplest and most resilient system involving a single trapped ion oscillating in a radio-frequency Paul trap. We identify a specific class of excited states of the Extended Rabi Model (ERM) Hamiltonian, which o

Fei Wu, Guanghao Ding, Zijian Niu, Zhenrui Wang

The malicious use and widespread dissemination of AI-generated images pose a serious threat to the authenticity of digital content. Existing detection methods exploit low-level artifacts left by common manipulation steps within the generation pipeline, but they often lack generalization due to model-specific overfitting. Recently, researchers have resorted t

Chien-Ping Lu

This paper argues that continued AI scaling requires repeated efficiency doublings. Classical AI scaling laws remain useful because they make progress predictable despite diminishing returns, but the compute variable in those laws is best read as logical compute, not as a record of one fixed physical implementation. Practical burden therefore depends on the

Afaf El Kalai, Peter J. Eder, Christian B. Mendl

Adiabatic quantum algorithms must evolve slowly enough to suppress non-adiabatic transitions while remaining fast enough to be practical. In open systems, this trade-off is reshaped by decoherence. For Hamiltonians subject to dephasing Lindbladians, Avron et al. [1] showed that a unique timetable exists that maximizes the fidelity with a target state. This o

Kunming Dong, Shasika Panamaldeniya, Dongming Mei

Rare-event experiments such as LEGEND-1000 require high-purity germanium (HPGe) detectors with excellent energy resolution, low electronic noise, and scalable low-background packaging. The germanium ring-contact (GeRC) concept addresses this need through a recessed ring-and-groove electrode geometry intended to preserve point-contact-like low-capacitance sig

Mingfu Shao, Hui Wang, Liyue Tong, Yuyang Li

Vision-Language Models (VLMs) have achieved breakthrough progress in general knowledge domains, yet adaptation to specialized scientific fields remains challenging due to multimodal representation shifts and the limited integration of domain-specific knowledge. To address the limitations of general-purpose VLMs when applied to solar physics image recognition

Jin Bai, Huiyao Zhang, Qi Wen, Ningyang Li

The segmentation of thin linear structures is inherently topology allowbreak-critical, where minor local errors can sever long-range connectivity. While recent State-Space Models (SSMs) offer efficient long-range modeling, their isotropic serialization (e.g., raster scanning) creates a geometry mismatch for anisotropic targets, causing state propagation acro

François-Grégoire Bierwart, Alexandre Mauroy

In this paper, we develop a comprehensive framework to estimate regions of attraction of equilibria for dynamics associated with general vector fields. This framework combines Koopman operator-based methods with rigorous validation techniques. A candidate Lyapunov function is constructed with approximated Koopman eigenfunctions and further validated through

Ziyu Mu, Xiyu Shi, Safak Dogan

Intrusion Detection System (IDS) is often calibrated to known attacks and generalizes poorly to unknown threats. This paper proposes GMA-SAWGAN-GP, a novel generative augmentation framework built on a Self-Attention-enhanced Wasserstein GAN with Gradient Penalty (WGAN-GP). The generator employs Gumbel-Softmax regularization to model discrete fields, while a

Matthew Fayers

We define and explore semireflection monoids on a finite-dimensional vector space. These are monoids generated by semireflections: linear maps fixing a subspace of codimension 1. We mostly focus on the case of projection monoids (where the generating semireflections are non-invertible). After exploring some general theory, we give some important examples, an

Mehryar Mohri, Clayton Sanford, Jon Schneider, Kiran Vodrahalli

We consider the question of how to employ next-token prediction algorithms in adversarial online decision-making environments. Specifically, if we train a next-token prediction model on a distribution $\mathcal{D}$ over sequences of opponent actions, when is it the case that the induced online decision-making algorithm (by approximately best responding to th

Qing Lyu, Jianxu Wang, Jeremy Hudson, Ge Wang

Accurate MRI-to-CT synthesis could enable MR-only pelvic workflows by providing CT-like images with bone details while avoiding additional ionizing radiation. In this work, we investigate recently proposed drifting models for synthesizing pelvis CT images from MRI and benchmark them against convolutional neural networks (UNet, VAE), a generative adversarial

R. S. Bogadi, G. Leon, M. Govender, K. S. Govinder

We investigate the evolution of the surface of radiating stars by studying the asymptotic behaviour of exact solutions initiated via the stationary boundary condition. This boundary condition leads to a master equation in the form of a second-order nonlinear differential equation that describes the evolution of the scale factor. We examine this master equati

Yaxiong Lei, Thomas Davies, Xinya Gong, Shijing He

Large-scale mobile gaze estimation relies on in-the-wild datasets, yet unsupervised collection makes it difficult to verify whether participants truly foveate logged targets. Prior mobile protocols often use low-entropy validation (e.g., binary probes) that can be satisfied by guessing and may still allow peripheral viewing, introducing label noise. We prese

Yaxiong Lei, Rishab Talwar, Shijing He, Xinya Gong

Conventional mobile eye-tracking maps gaze to static screen coordinates, failing to capture user attention when content is dynamic. As users pinch, zoom, and rotate images, static coordinates lose their semantic meaning relative to the underlying visual content. To address this methodological gap, we present \textit{GazeSync}, a reusable mobile system that s

Yaxiong Lei, Hyochan Cho, Fergus Buchanan, Shijing He

Gaze gestures can provide hands free input on mobile devices, but practical use requires (i) gestures users can learn and recall and (ii) recognition models that are efficient enough for on-device deployment. We present an end-to-end pipeline using commodity ARKit head/eye transforms and a scaffolded guidance-to-recall protocol grounded in learning theory. I

Jintao Chen, Aiming Hao, Xiaoqing Chen, Chengyu Bai

Pre-trained flow-based models excel at synthesizing complex scenes yet lack a direct mechanism for disentangling and customizing their underlying concepts from one-shot real-world sources. To demystify this process, we first introduce a novel differential probing technique to isolate and analyze the influence of individual concept tokens on the velocity fiel

Keiji Yada, Yuri Fukaya, Yukio Tanaka

Flat bands have attracted considerable interest in condensed matter physics because they provide a fertile platform for realizing strongly correlated and topological quantum phases. To date, however, most studies have focused on flat bands in normal-state electronic structures, such as those found in graphene and transition metal dichalcogenides. In this wor

Trung Chau, Tanushree Shah

This article reviews the development of Legendrian graph theory in the standard contact 3-sphere ($S^3, \xi_{std}$). We provide a generalized criterion under which the total Thurston-Bennequin invariant of a Legendrian graph (sum of tb of all cycles of the Legendrian graph) can be computed from the tb of its smaller cycles. We verify this criterion for graph

Alina Joch, Kevin Lively, Benedikt Fauseweh

The performance of the variational quantum eigensolver depends critically on the choice of ansatz. In this work, we experimentally evaluate the emergent-coupling-based ansatz (ECBA), a physically motivated variational ansatz for disordered systems. The ECBA is based on a renormalization (semi-)group approach to determine the dominant effective couplings, res

Sezel Alkan, Nurdagül Anbar, Athina Avrantini, Erroxe Etxabarri-Alberdi

We study generalizations of two classical primary constructions of Boolean bent functions, namely the Maiorana-McFarland ($MM$) class and the (Desarguesian) partial spread ($\mathcal{PS}_{ap}$) class. The construction of bent functions lying outside the completed $MM$ class has attracted considerable attention in recent years. In this direction, we construct

Guido Tapia-Riera, Camille Castera, Nicolas Papadakis

We study alternating first-order algorithms with no inner loops for solving nonconvex-strongly-concave min-max problems. We show the convergence of the alternating gradient descent--ascent algorithm method by proposing a substantially simplified proof compared to previous ones. It allows us to enlarge the set of admissible step-sizes. Building on this genera

Blaise Boissonneau, Mathias Stout, Floris Vermeulen

We consider the model-theoretic Grothendieck ring of definable sets in ordered abelian groups. It is well-known that $\mathrm{K} \mathbb{Q} \cong \mathbb{Z}[T]/(T^2 + T)$ and $\mathrm{K} \mathbb{Z} =0$, but surprisingly little is known about other cases. We present a short computation which shows that they all collapse: $\mathrm{K} G = 0$, unless $G$ is divi

Ruixue Wang, Jiangang Chen, Er Pan, Wunan Wang

The escalating demand for memory scaling requires switching mechanisms that remain reliable at atomic thickness while operating with minimal energy consumption. Sliding ferroelectricity provides a promising platform for this challenge: the spontaneous interfacial polarization emerging at superlubric, atomically thin van der Waals interfaces endows exceptiona

Bosong Zhang, Timothy M. Merlis

The spatial pattern of sea surface temperature (SST) plays a central role in shaping the climate system, yet the influence of land surface temperature (LST) remains poorly understood. Using a state-of-the-art coupled ocean--land--atmosphere model, we examine the model's response to regional LST perturbations imposed through LST nudging and idealized time-dep

Claudia Cuttano, Gabriele Trivigno, Christoph Reich, Daniel Cremers

In-context segmentation (ICS) aims to segment arbitrary concepts, e.g., objects, parts, or personalized instances, given one annotated visual examples. Existing work relies on (i) fine-tuning vision foundation models (VFMs), which improves in-domain results but harms generalization, or (ii) combines multiple frozen VFMs, which preserves generalization but yi

José M. Espinar, Fernán González-Ibáñez, Diego A. Marín

In the first part of the article we develop a comparison method for positive solutions of the semilinear Dirichlet problem $\Delta u+f(u)=0$ on domains $\Omega\subset \mathcal M^n$ of a Riemannian manifold $(\mathcal{M}^n,g)$ with a Ricci lower bound $\operatorname{Ric}_g\ge (n-1)k\,g$. Assuming admissibility and structural conditions on $f$, we prove a shar

Feixue Cai, Hua Zhou, Zhuyin Ren

Calibrating chemical kinetics in a reaction-diffusion system is challenging because of complex dynamics governed by tightly coupled chemistry and transport, while experimental observations are often sparse and noisy. We propose a physics consistent diffusion-chemistry coupled neural ordinary differential equation (Diff-Chem Neural ODE) that embeds Arrhenius-

Wenxiong Chen, Yahong Guo, Congming Li, Yugao Ouyang

In this paper, we establish a convergence result for the fully fractional heat operator $\ma{s}$, also known as the master operator, stated as follows: \[\mbox{If\ }u_i\to u\ \mbox{in}\ C^{2,1}_{x,t,loc}(\R^n\times\R),\ \mbox{then}\ \ma{s} u_i\to \ma{s}u-b\ \mbox{a.e. in}\ \R^n\times\R,\] for some nonnegative constant $b$. This result addresses a fundamental

Giovanni De Toni, Cristian Consonni, Erasmo Purificato, Emilia Gomez

Recommendation systems have become central gatekeepers of online information, shaping user behaviour across a wide range of activities. In response, users increasingly organize and coordinate to steer algorithmic outcomes toward diverse goals, such as promoting relevant content or limiting harmful material, relying on platform affordances -- such as likes, r

Ningyu Yan, Shuai Wang, Xing Shen, Hui Wang

Visuotactile sensors are indispensable for contact-rich robotic manipulation tasks. However, policy learning with tactile feedback in simulation, especially for online reinforcement learning (RL), remains a critical challenge, as it demands a delicate balance between physics fidelity and computational efficiency. To address this challenge, we present Tac2Rea

Wenhan Wang, Zhixiang Zhou, Zhongtian Ma, Yanzhu Chen

The connoisseurship of antique Chinese porcelain demands extensive historical expertise, material understanding, and aesthetic sensitivity, making it difficult for non-specialists to engage. To democratize cultural-heritage understanding and assist expert connoisseurship, we introduce CiQi-Agent -- a domain-specific Porcelain Connoisseurship Agent for intell

Piotr Wielgórski, Grzegorz Pietrzyński, Wolfgang Gieren, Bartlomiej Zgirski

Anomalous Cepheids are radially pulsating stars observed in dwarf galaxies, the Galactic bulge and halo, and globular clusters. Similarly to other radially pulsating stars, they can be used as distance indicators through their Period-Luminosity Relations (PLRs) and the geometrical Baade-Wesselink (BW) method. We aim to calibrate the zero-point of the distanc

Yuan Liu, Ke-Mi Xu, Hong-Bo Sun, Linhan Lin

Quantum metrology exploits quantum resources to enhance measurement precision beyond the classical limit. Conventional protocols normally rely on the preparation of delicate quantum states to acquire these resources, posing a major challenge for scaling and robustness. Here we introduce a paradigm that circumvents this requirement with a collectively enhance

Yu Xie, Ying Qi

Recommendation feeds work well when people are simply browsing, and search works well when they can formulate a query. Between these two cases is a common but poorly supported state: users feel that their feed has become repetitive, yet cannot clearly specify what they want instead. We refer to this state as vague intent. We present Red-Rec, an AI-supported

Georg Keilbar, Sonja Greven

We propose a novel framework for conducting causal inference based on counterfactual densities. While the current paradigm of causal inference is mostly focused on estimating average treatment effects (ATEs), which restricts the analysis to the first moment of the outcome variable, our density-based approach is able to detect causal effects based on general

Zongxiong Ren, Zhipeng Yang

In this paper we establish improved Sobolev inequalities on the quaternionic sphere under higher-order moment vanishing conditions with respect to the measure \(|u|^{p^*}\,d\xi\). As an application, we give a new proof of the existence of extremals for the sharp Sobolev embedding \[ S^{1,2}(S^{4n+3}) \hookrightarrow L^{2^*}(S^{4n+3}). \]

Hitoshi Nakada, Rie Natsui, Jörg Thuswaldner

We discuss complex Farey graphs for the Euclidean imaginary quadratic number fields $\mathbb Q(\sqrt{-d})$, $d\in\{1, 2, 3, 7, 11\}$. We study hyperbolic versions of A. Schmidt's Farey polygons living in $3$-dimensional hyperbolic space $\mathbb{H}^3$. Using these Farey polygons we recover tessellations of the hyperbolic plane $\mathbb{H}^2$ that are defined

Giuseppe Silano, Daniel Bonilla Licea, Davide Liuzza, Antonio Franchi

Multi-Rotor Aerial Vehicles (MRAVs) are increasingly used in communication-dependent missions where connectivity loss directly compromises task execution. Existing anti-jamming strategies often decouple motion from communication, overlooking that link quality depends on vehicle attitude and antenna orientation. In coplanar platforms, ``tilt-to-translate&#39;

Ahcène Boubekki, Line H. Clemmensen

Although standard Convolutional Neural Networks (CNNs) can be mathematically reinterpreted as Self-Explainable Models (SEMs), their built-in prototypes do not on their own accurately represent the data. Replacing the final linear layer with a $k$-means-based classifier addresses this limitation without compromising performance. This work introduces a common

Matteo Tamiozzo

Let $C$ be a complex irreducible plane curve that is not the vanishing locus of a modular polynomial. We show that $C$ contains finitely many real algebraic curves whose projection on each coordinate axis is a union of special geodesics.

Francesco Ferraro, Christian Grilletta, Amos Maritan, Samir Suweis

Randomly-assembled dynamical systems are theoretically predicted to be unstable upon crossing a critical threshold of complexity, as first shown by May. Yet, empirical complex systems exhibit remarkable stability, indicating the presence of additional mechanisms playing a stabilizing role. The relation between complexity and stability is typically assessed b

Shramana Dey, Varun Ajith, Abhirup Banerjee, Sushmita Mitra

Domain generalization in fundus imaging is challenging due to variations in acquisition conditions across devices and clinical settings. The inability to adapt to these variations causes performance degradation on unseen domains for deep learning models. Besides, obtaining annotated data across domains is often expensive and privacy constraints restricts the

Ping Zhang, Naiwen Ying, Wang Miao

We study fairness in decision-making when the data may encode systematic bias. Existing approaches typically impose fairness constraints while predicting the observed decision, which may itself be unfair. We propose a novel framework for characterising and addressing fairness issues by introducing the notion of desert decision, a latent variable representing

Keerthana S Kumar, Abhijit Gogoi, Madhavan DK Nampoothiri, Bhavesh Kumar Acharya

Molybdenum disulfide (MoS2) is a promising 2D transition metal dichalcogenide (TMD) for optoelectronics and quantum technology applications, but faces challenges in scalable synthesis and defect engineering. Oxygen-assisted chemical vapor deposition (O-CVD), which introduces in-situ oxygen during growth, shows excellent potential in resolving both issues at

Linqian Fan, Peiqin Sun, Tiancheng Wen, Shun Lu

Diffusion models achieve state-of-the-art generative performance but are fundamentally bottlenecked by their slow, iterative sampling process. While diffusion distillation techniques enable high-fidelity, few-step generation, traditional objectives often restrict the student's performance by anchoring it solely to the teacher. Recent approaches have attempte

Himanshu Dongre, Lane G. Gunderman

Protecting information in systems that have more than two basis states (qudits) not only offers a promising route for reducing the number of individual quantum locations that must be protected, while more accurately reflecting the structure of realistic quantum hardware, but also has some possibly enticing foundational strengths. While work in the past has l

Yufei Xu, Fanxu Meng, Fan Jiang, Yuxuan Wang

Token-level sparse attention mechanisms, exemplified by DeepSeek Sparse Attention (DSA), achieve fine-grained key selection by scoring every historical key for each query through a lightweight indexer, then computing attention only on the selected subset. While the downstream sparse attention itself scales favorably, the indexer must still scan the entire pr

Tiantian Wang, Xiang Xiang, Simon S. Du

In federated healthcare systems, Federated Class-Incremental Learning (FCIL) has emerged as a key paradigm, enabling continuous adaptive model learning among distributed clients while safeguarding data privacy. However, in practical applications, data across agent nodes within the distributed framework often exhibits non-independent and identically distribut

Prashanth Raman

We review completely monotone (CM) and Stieltjes functions, which are classes of functions obeying an infinite hierarchy of positivity constraints. While these are classical concepts in analysis, such properties have recently been shown to arise in many fundamental building blocks and observables of quantum field theory (QFT), including scalar Feynman integr

Man Zhang, Chongyang Shen, Andrea Arcuri, Tao Yue

Test flakiness is a common problem in industry, which hinders the reliability of automated build and testing workflows. Most existing research on test flakiness has primarily focused on unit and small-scale integration tests. In contrast, flakiness in system-level testing such as REST APIs are comparatively under-explored. A large body of literature has been

Hao Tan, Zhipeng Yang

In this paper, we study symmetry-improved fractional Sobolev embeddings on closed Riemannian manifolds under the action of compact isometry groups. We prove that \(G\)-invariant fractional Sobolev spaces embed into higher \(L^p\) spaces, with corresponding compactness results depending on the minimal orbit dimension. We also investigate the associated optima

Songhao Yang, Zhiguo Hao, Baohui Zhang, Masahide Hojo

With the development of PMUs in power systems, the response-based real-time emergency control becomes a promising way to prevent power outages when power systems are subjected to large disturbances. The first step in the emergency control is to start up accurately and fast when needed. To this end, this paper proposes a well-qualified start-up scheme for the

Yi-Shuai Niu, Artan Sheshmani, Shing-Tung Yau

We propose Yau's Affine Normal Descent (YAND), a geometric framework for smooth unconstrained optimization in which search directions are defined by the equi-affine normal of level-set hypersurfaces. The resulting directions are invariant under volume-preserving affine transformations and intrinsically adapt to anisotropic curvature. Using the analytic repre