March 2026 arXiv papers — page 6

Giovanni Seraghiti, Kévin Dubrulle, Arnaud Vandaele, Nicolas Gillis

Nonnegative matrix factorization (NMF) approximates a nonnegative matrix, $X$, by the product of two nonnegative factors, $WH$, where $W$ has $r$ columns and $H$ has $r$ rows. In this paper, we consider NMF using the component-wise L1 norm as the error measure (L1-NMF), which is suited for data corrupted by heavy-tailed noise, such as Laplace noise or salt a

Kosuke Shibata, Kohji Yanagawa

For a simplicial poset $P$, Stanley assigned the face ring $A_P$, which is the quotient of the polynomial ring $S:=K[t_x \mid x \in P \setminus \{\widehat{0} \}]$ by the ideal $I_P$. This is a generalization of Stanley-Reisner rings, but $S$ and $A_P$ are not standard graded in this case, and $I_P$ is not a monomial ideal. To establish the foundation of the

Francesco Proietto, Alessandra Milloch, Paolo Franceschini, Mohammadjavad Azarm

The coupling between electronic excitations and collective bosonic modes is fundamental to the emergence of high-temperature superconductivity in cuprates. Despite extensive effort, conventional equilibrium and pump-probe optical spectroscopies still struggle to disentangle couplings to different bosonic modes when their energy scales overlap. Here we overco

Yu Liu

Pulse charging can be used to boost up charging speed for lithium-ion batteries and delay battery capacity fading by periodically pausing the current during charging. However, this technique introduces intermittence for current and may thus challenge the electric stability of charger as well as its energy supply source. To deal with this challenge, a coordin

Luca Scarpa, Margherita Zanella

We establish strong Feller property and irreducibility for the transition semigroup associated to a class of nonlinear stochastic partial differential equations with multiplicative degenerate noise. As a by-product, we prove uniqueness of the invariant measure under no strong-dissipativity assumptions. The drift of the equation diverges exactly where the noi

Mahesh Ramani

I present the generation and analysis of the largest known open-source corpus of playable piano chords (approximately 19.3 million entries). This dataset enumerates the two-handed search space subject to biomechanical constraints (two hands, each with 1.5 octave reach) to an unprecedented extent. To demonstrate the corpus's utility, the relationship between

Joakim Edin, Andreas Motzfeldt, Simon Flachs, Lars Maaløe

Medical coding translates free-text clinical documentation into standardized codes drawn from classification systems that contain tens of thousands of entries and are updated annually. It is central to billing, clinical research, and quality reporting, yet remains largely manual, slow, and error-prone. Existing automated approaches learn to predict a fixed s

Soumyodipta Nath, Pranav Tiwari, Ravi Prakash

Robots operating in human-centric environments must be both robust to disturbances and provably safe from collisions. Achieving these properties simultaneously and efficiently remains a central challenge. While Dynamic Movement Primitives (DMPs) offer inherent stability and generalization from single demonstrations, they lack formal safety guarantees. Conver

Hei Jie Lam, Alpár R. Mészáros

We establish the existence and uniqueness of distributed equilibria to possibly nonsymmetric $N$ player differential games with interactions through controls under displacement semimonotonicity assumptions. Surprisingly, the nonseparable framework of the running cost combined with the character of distributed equilibria leads to a set of consistency relation

Yuebo Feng, Jiahao Liu, Mingzhe Han, Dongsheng Li

Generative recommendation commonly adopts a two-stage pipeline in which a learnable tokenizer maps items to discrete token sequences (i.e. identifiers) and an autoregressive generative recommender model (GRM) performs prediction based on these identifiers. Recent tokenizers further incorporate collaborative signals so that items with similar user-behavior pa

Guan-Ru Li, Wei-Liang Qian, Xiao-Mei Kuang, Ramin G. Daghigh

In this work, we investigate the relation between bound states and quasinormal modes within black hole perturbation theory in the context of spectral instability. Our analysis indicates that the reliability of such spectral mapping stretches beyond the domain of validity of the analytic continuation employed to connect the perturbative bound-state problem to

Amos Uderzo

In the present paper, a systematic study is made of quantitative semicontinuity (a.k.a. Lipschitzian) properties of certain multifunctions, which are defined as a solution map associated to a family of parameterized ``split" feasibility problems. The latter are a particular class of convex feasibility problems with well recognized applications to several

Zhenyu Pu, Yu Yang, Liang Yu, Xiaohong Guan

Buildings and data centers (DCs) are energy-intensive sectors, playing a critical role to achieve the low-carbon and sustainable energy transition targets. To this end, integrated energy system (IES) that incorporates diverse renewables, energy generation, conversion, and storage technologies to enable coordinated multi-energy supply have been widely investi

Xiao Mao, Aviad Rubinstein

We present novel randomized approximation schemes for the Edit Distance (ED) problem and the Longest Common Subsequence (LCS) problem that, for any constant $\epsilon>0$, compute a $(1+\epsilon)$-approximation for ED and a $(1-\epsilon)$-approximation for LCS in time $n^2 / 2^{\log^{\Omega(1)}(n)}$ for two strings of total length at most $n$. This running ti

Alfons Van Daele

Discrete quantum groups were introduced as duals of compact quantum groups by Podle\'s and Woronowicz in 1990. They have been studied intrinsically by Effros and Ruan (1994) and by the author (1996). In a more recent note (2025), we have given a slightly updated treatment, viewing the duality between discrete and compact quantum groups as a special case of t

Amie J. Chism, Mary Jane van der Pot, Blaise P. Hasheau, Hans-Joachim Grasmann

We report the first unambiguous detection of cannabinoid molecules in an exoplanetary atmosphere. Using 420 hours of JWST observations combining NIRSpec and MIRI instruments, we identify spectroscopic signatures of tetrahydrocannabinol (THC; $\Delta^9$-C$_{21}$H$_{30}$O$_2$) and cannabidiol (CBD; C$_{21}$H$_{30}$O$_2$) in the transmission spectrum of the tem

Alexander F. Goncharov, Irina Chuvashova, Eric Edmund, JungFu Lin

Thermal conductivity of Earths lower mantle controls heat transfer across the core-mantle boundary (CMB) and strongly influences mantle convection. We report direct measurements of the thermal conductivity of single-crystal ferropericlase (Mg$_{1-x}$Fe$_x$O, $x = 0.09$-0.13), the second most abundant lower-mantle mineral, using optical laser flash and X-ray

Benoît Gay, Eugeny Babichev, Sébastien Galtier, Karim Noui

The theory of gravitational wave turbulence describes the long-term statistical behaviour of a set of weakly nonlinear interacting waves. In this paper, we aim to study aspects of gravitational turbulence within the framework of general relativity using the Hadad-Zakharov (HZ) metric. The latter is parameterised by four functions (the coefficients of a diago

Zohaib Arshid, Daniele Bifolco, Fiorella Zampetti, Massimiliano Di Penta

The increasing availability of Machine Learning (ML) models, particularly foundation models, enables their use across a range of downstream applications, from scenarios with missing data to safety-critical contexts. This, in principle, may contravene not only the models' terms of use, but also governmental principles and regulations. This paper presents a pr

Fengjian Xue, Xuecheng Wu, Heli Sun, Yunyun Shi

Facial expression image editing requires fine-grained control to strictly preserve human identity and background while precisely manipulating expression. However, existing editing benchmarks primarily focus on general scenarios, lacking high-quality facial images and corresponding editing instructions. Furthermore, current evaluation metrics exhibit systemic

Elishan Christian Braun, Gabriella Bretti, Samuele Ferri, Maria Laura Santarelli

In this paper we introduce a new mathematical model describing the erosion process caused in carbonate stones by the dissolution of the porous matrix due to the penetration of carbonic acid present in the environment. Such model is formulated as nonlinear reaction-transport system in porous media governed by Darcy flow. We propose a numerical algorithm based

Kuniko Paxton, Medina Kapo, Amila Akagić, Koorosh Aslansefat

Skin cancer, particularly melanoma, remains a major cause of morbidity and mortality, making early detection critical. AI-driven dermatology systems often rely on skin lesion segmentation as a preprocessing step to delineate the lesion from surrounding skin and support downstream analysis. While fairness concerns regarding skin tone have been widely studied

Ning Wang, Tieyue Wu, Naeha Sharif, Farid Boussaid

Zero-shot skeleton-based action recognition aims to recognize unseen actions by transferring knowledge from seen categories through semantic descriptions. Most existing methods typically align skeleton features with textual embeddings within a shared latent space. However, the absence of contextual cues, such as objects involved in the action, introduces an

Florian Andreas Marwitz, Tanya Braun, Ralf Möller

Real world scenarios can be captured with lifted probability distributions. However, distributions are usually encoded in a table or list, requiring an exponential number of values. Hence, we propose a method for extracting first-order formulas from probability distributions that require significantly less values by reducing the number of values in a distrib

Xian-Peng Zhang, Yan-Qing Feng, Haiwen Liu, Wanxiang Feng

Coherent quantum phenomena can only emerge when decoherence is minimized, and mastery over decoherence is technologically crucial for designing and operating functional quantum devices. However, its microscopic mechanisms in spin-orbit-coupled ferromagnets remain elusive, and quantitative treatments have long been challenging. To solve this fundamentally sig

Zhenning Chen, Hanbei Zhan, Yanwei Huang, Xin Wu

Large Language Models (LLMs) demonstrate exceptional capabilities in factual question answering, yet they sometimes provide incorrect responses. To address this issue, knowledge editing techniques have emerged as effective methods for correcting factual information in LLMs. However, typical knowledge editing workflows struggle with identifying the optimal se

Yuhua Xu, Mingtao Jiang, Chenfei Hu, Yinglong Wang

In low-altitude wireless networks (LAWN), federated learning (FL) enables collaborative intelligence among unmanned aerial vehicles (UAVs) and integrated sensing and communication (ISAC) devices while keeping raw sensing data local. Due to the "right to be forgotten" requirements and the high mobility of ISAC devices that frequently enter or leave the covera

Jishnu Goswami, Dibyendu Bala, Olaf Kaczmarek

We study the thermal static potential for (2+1)-flavor QCD at nonzero density through a Taylor expansion around vanishing chemical potentials. From Taylor expanded Wilson line correlators, we extract the $\hat{\mu}^2$ coefficient of the real and imaginary part of the potential in light and strange flavor channels and in the baryon number and electric charge

Seokhyun Choi, Bo-Hae Im, Beomho Kim

Let $E/k$ be a non-isotrivial elliptic curve over a global function field $k$ of characteristic $p>3$, and $G\subset \mathrm{Gal}(k^{\mathrm{sep}}/k)$ be a topologically finitely generated subgroup. We prove that if $E/k$ has analytic rank $1$, then its rank over the fixed subfield $L^G$ is infinite, where $L$ is the infinite ring class extension of some fin

S. Gratton, Ph. L. Toint

An algorithm is proposed for solving optimization problems with stochastic objective and deterministic equality and inequality constraints. This algorithm is objective-function-free in the sense that it only uses the objective's gradient and never evaluates the function value. It is based on an adaptive selection of function-decreasing and constraint-improvi

Tomasz Kalwarczyk

FcsIT is a platform-independent, open-source tool for calculating the correlation and fitting fluorescence correlation spectroscopy data. The software is written in Python and uses a powerful Dear PyGUI engine for its interface. It provides reading and correlating the TTTR data, as well as TCSPC filtering of the photon time-trace data. The circular-block boo

Philippe Bouafia, Thierry De Pauw

We provide a short proof of the 1-dimensional flat chain conjecture.

Sushree Monalisha Sahu, Hirakjyoti Sarma, Ankit Dhaka, Pintu Bandyopadhyay

We present the first experimental evidence of inhomogeneous melting in a finite dusty plasma crystal confined in an anisotropic potential well. By systematically tuning the confinement anisotropy and applying controlled laser heating, distinct melting patterns are observed. Spectral-mode analysis based on Singular Value Decomposition of particle trajectories

Christopher Koch

The common claim that generative AI simply amplifies the Dunning-Kruger effect is too coarse to capture the available evidence. The clearest findings instead suggest that large language model (LLM) use can improve observable output and short-term task performance while degrading metacognitive accuracy and flattening the classic competence-confidence gradient

Marc Martinez-Gost, Ana Pérez-Neira, Miguel Ángel Lagunas

We present a receiver-side framework for identifying amplitude distortions in frequency-selective OFDM channels. The core novelty is the use of the DCT Neuron, a compact adaptive processor based on the discrete cosine transform (DCT), to characterize the channel's nonlinear response, leveraging its properties for highly efficient estimation. Operating direct

Amihay Hanany, Alessandro Tomasiello, Elias Van den Driessche

Higgs branches of 5d $Sp(k)$ theories with $N_f$ flavours, whether at weak or strong coupling, are described by a pair of instantons transforming as pure spinors of $SO(2N_f)$. The Poisson structure is constrained by symmetry arguments and implies that these Higgs branches are algebraic integrable systems; the degeneration of the symplectic form occurs when

Lvmin Zhang, Maneesh Agrawala

Agent traces carry increasing analytical value in agentic systems and context engineering, yet most prior work treats conversation format as a trivial implementation detail. Modern agent conversations, however, contain deeply structured content, including nested tool calls and results, chain-of-thought reasoning blocks, sub-agent invocations, context-window

Dustin Eisenhardt, Yunhee Jeong, Florian Buettner

Multimodal learning enables neural networks to integrate information from heterogeneous sources, but active learning in this setting faces distinct challenges. These include missing modalities, differences in modality difficulty, and varying interaction structures. These are issues absent in the unimodal case. While the behavior of active learning strategies

Lixin Xiu, Xufang Luo, Hideki Nakayama

Large vision-language models (LVLMs) achieve impressive performance, yet their internal decision-making processes remain opaque, making it difficult to determine if the success stems from true multimodal fusion or from reliance on unimodal priors. To address this attribution gap, we introduce a novel framework using partial information decomposition (PID) to

Alessandro Mangiameli, Christopher J. Stein

We assess the dielectrically consistent reference interaction site model (DRISM) as an implicit electrolyte framework for modeling the electrochemical double layer, and compare it with the Poisson-Boltzmann model and explicit molecular dynamics results from the literature. We use the gold-electrolyte interface as the main test case and analyze solvent and io

Liang Dong, Shen Fang, Jun Gao, Hai Tao Li

Identified hadron production is essential for the study of nucleon structure and QCD hadronization at high energies. We present the first calculation of unpolarized semi-inclusive deep-inelastic scattering (SIDIS) at next-to-next-to-next-to-leading order (N$^3$LO) in perturbative QCD. Our calculation is based on a novel method of two-dimensional transverse-m

Sjoerd Halmans, Lavinia Paganini, Alexander Serebrenik, Alexander Nolte

Hackathons are time-bound collaborative events that often target software creation. Although hackathons have been studied in the past, existing work focused on in-depth case studies limiting our understanding of hackathons as a software engineering activity. To complement the existing body of knowledge, we introduce HackRep, a dataset of 100,356 hackathon Gi

Timur E. Gureyev, David M. Paganin, Harry M. Quiney

In-line phase-contrast imaging, also known as propagation-based imaging or Gabor holography, is capable of delivering significant gains in image quality, compared to attenuation-based imaging at the same radiation dose. Image quality metrics, including signal-to-noise ratio and spatial resolution, are considered, and their relationship to the amount of Shann

Ruochen Gao, Marius Staring, Frank Dankers

Purpose: Deep-learning-based three-dimensional (3D) dose prediction is widely used in automated radiotherapy workflows. However, most existing models are trained with voxel-wise regression losses, which are poorly aligned with clinical plan evaluation criteria based on dose-volume histogram (DVH) metrics. This study aims to develop a clinically guided loss f

William Tighe, George Brumpton, Mark Carney, Benjamin T. H. Varcoe

Quantum key distribution is often regarded as an unconditionally secure method to exchange a secret key by harnessing fundamental aspects of quantum mechanics. Despite the robustness of key exchange, classical post-processing reveals vulnerabilities that an eavesdropper could target. In particular, many reconciliation protocols correct errors by comparing th

Ioannis Karyotakis, Foivos Timotheos Proestakis, Evangelos Talos, Diomidis Spinellis

Mobile messaging apps are a fundamental communication infrastructure, used by billions of people every day to share information, including sensitive data. Security and Privacy are thus critical concerns for such applications. Although the cryptographic protocols prevalent in messaging apps are generally well studied, other relevant implementation characteris

Huaibao Zhang, Yongliang Yang, Guangxue Wang, Mengqi Zhang

This paper presents results of two-dimensional direct numerical simulations (DNS) and global linear stability analyses (based on mean flow and base flow) of a viscous incompressible flow past a circular array of cylinders with six-fold rotational symmetry. Six cylinder arrays, with varied patch density $\phi = N_c (d/D)^2$ (with $N_c$ cylinders of diameter $

Dimitrios Anastasiou, Razvan Caramalau, Jialang Xu, Runlong He

Vision-based surgical skill assessment (SSA) enables objective and scalable evaluation of operative performance. Progress in this field is constrained by the high cost and time demands for manual annotation of quantitative skill scores, as well as the poor generalization of existing regression models to new surgical tasks and environments. Meanwhile, appreci

Shifang Zhao, Yihan Hu, Ying Shan, Yunchao Wei

Editing the video content with audio alignment forms a digital human-made art in current social media. However, the time-consuming and repetitive nature of manual video editing has long been a challenge for filmmakers and professional content creators alike. In this paper, we introduce CutClaw, an autonomous multi-agent framework designed to edit hours-long

Paula Tuzón, Juan Antonio García-Castillo, Juan Fernández-Gracia

Network-based approaches have become increasingly prominent in science education research as tools for analysing relational structures in learning, teaching, and knowledge production. This review presents a PRISMA-informed scoping analysis of 82 articles published in nine leading science education journals, which are organised into four main categories: conc

Brian Felipe Keith-Norambuena, Carolina Inés Rojas-Córdova, Claudio Juvenal Meneses-Villegas, Elizabeth Johanna Lam-Esquenazi

Existing narrative extraction methods face a trade-off between coherence, interactivity, and multi-storyline support. Narrative Maps supports rich interaction and generates multiple storylines as a byproduct of its coverage constraints, though this comes at the cost of individual path coherence. Narrative Trails achieves high coherence through maximum capaci

Andrea DeMarco, Ian Fenech Conti, Hayley Camilleri, Ardiana Bushi

Next-generation radio astronomy surveys are delivering millions of resolved sources, but robust and scalable morphology analysis remains difficult across heterogeneous telescopes and imaging pipelines. We present STRADAViT, a self-supervised Vision Transformer continued-pretraining framework for learning transferable encoders from radio astronomy imagery. Th

Zelong Yuan, Yuzhu Pearl Li

Recent advances in data-driven turbulence modeling have established tensor basis neural networks (TBNN) as a physically grounded framework for Reynolds-stress closure in Reynolds-averaged Navier-Stokes (RANS) simulations. However, their robustness in wall-bounded turbulent flows remains limited across Reynolds numbers and geometries due to the lack of an int

Pietro Zanotta, Panos Stinis, Ján Drgoňa

Certifying the Region of Attraction (ROA) for high-dimensional nonlinear dynamical systems remains a severe computational bottleneck. Traditional deterministic verification methods, such as Sum-of-Squares (SOS) programming and Satisfiability Modulo Theories (SMT), provide hard guarantees but suffer from the curse of dimensionality, typically failing to scale

Kai Wu, Ataru Tanikawa, Francesco Flammini Dotti, Marcelo C. Vergara

Aims. We present eight direct N-body simulations with NBODY6++GPU of extremely massive, initially rotating Population III star clusters with 1.01 x 10^5 stars. Methods. Our models include primordial binaries, a continuous initial mass function, differential rotation, tidal mass loss, updated fitting formulae for extremely massive metal-poor Population III st

Jiao Chen, Jianhua Tang, Xiaotong Yang, Zuohong Lv

Autonomous 6G network management requires agents that can execute tools, observe the resulting state changes, and adapt their decisions accordingly. Existing benchmarks based on static questions or scripted episode replay, however, do not support such closed-loop interaction, limiting agents to passive evaluation without the ability to learn from environment

Pengfei Zhou, Xiangyue Zhang, Xukun Shen, Yong Hu

Masked generative models have become a strong paradigm for text-to-motion synthesis, but they still treat motion frames too uniformly during masking, attention, and decoding. This is a poor match for motion, where local dynamic complexity varies sharply over time. We show that current masked motion generators degrade disproportionately on dynamically complex

Cody Kommers, Ruth Ahnert, Maria Antoniak, Emmanouil Benetos

Generative AI systems are increasingly recognized as cultural technologies, yet current evaluation frameworks often treat culture as a variable to be measured rather than fundamental to the system's operation. Drawing on hermeneutic theory from the humanities, we argue that GenAI systems function as "context machines" that must inherently address three inter

Enrico Parisini, Christopher J. Soelistyo, Ahab Isaac, Alessandro Barp

Aligning human-interpretable concepts with the internal representations learned by modern machine learning systems remains a central challenge for interpretable AI. We introduce a geometric framework for comparing supervised human concepts with unsupervised intermediate representations extracted from foundation model embeddings. Motivated by the role of conc

Kakeru Tanaka, Hiroaki Ishizuka

Recent theoretical studies on the nonlinear response of spin and orbital degrees of freedom have discovered spin and orbital analogs of the photocurrent, with potential for characterizing topological materials and for applications. In this paper, we develop a general theory for calculating spin and orbital currents in semiconductors and study the properties

Giovanni Mazzolari, Hannah Übler, Rodrigo Herrera Camus, Ric Davies

We targeted with deep NOEMA observations the [CII]158$\mu$m emission of three JWST-discovered AGN at z>6. Two of them have the typical features of Little Red Dots (LRDs), while the third one is a blue, extended, Type I AGN. We do not significantly detect [CII] emission or dust continuum in any of the targets, even after stacking. The resulting [CII] luminosi

Brian Felipe Keith-Norambuena, Fausto German, Eric Krokos, Sarah Joseph

Semantic interaction (SI) enables analysts to incorporate their cognitive processes into AI models through direct manipulation of visualizations. While SI frameworks for narrative extraction have been proposed, empirical evaluations of their effectiveness remain limited. This paper presents a user study that evaluates SI for narrative map sensemaking, involv

Ahmad Darwish, Matteo Murdaca, Jami J. Kinnunen

It is a universal empirical observation that socks become unpaired in the laundry. We propose a quasiparticle theory of sock dynamics in which individual socks are modelled as bosonic excitations of the agitated laundry condensate. The sock dispersion relation is material-dependent: nondispersive materials retain their shape, while dispersive materials give

Yaning Zhao, Holger Boche, Christian Deppe

Task-oriented communication is a key enabler of emerging 6G systems, where the objective is to support decisions and actions rather than full message reconstruction. From an information-theoretic perspective, identification (ID) codes provide a natural abstraction for this paradigm by enabling receivers to test whether a task-relevant message was sent, witho

Amit Pando, Eran Bernstein, Tomer Hacohen, Nathan Vigne

We introduce a novel coupling scheme for maximizing the synchronization of Kuramoto oscillator networks under a fixed coupling budget. We show that by scaling the interaction strength between oscillators according to their frequency detuning, synchronization is enhanced. The coupling scheme induces a change in criticality, driving the system from a continuou

Øystein Sørensen, Ethan M. McCormick

Dynamic structural equation modeling (DSEM) is widely used for analyzing intensive longitudinal data (ILD). Although many ILD have categorical (Bernoulli or binomially distributed) responses, currently available Metropolis-within-Gibbs samplers for estimating DSEMs are limited to using the probit link and the Bernoulli distribution. These samplers scale poor

Fikret Anli

This study provides an exact solution to Chandrasekhar's H function for isotropic scattering. The H function, which is governed by a nonlinear integral equation, plays a central role in radiative transfer theory. To facilitate the solution, the differential form of the integral equation is derived using classical integral techniques. The resulting differenti

Anja Bosak, Dorian Erić, Ana Milas, Stjepan Bogdan

In this paper, we present a generalized, comprehensive nonlinear mathematical model and conceptual design for the MetaMorpher, a metamorphic Unmanned Aerial Vehicle (UAV) designed to bridge the gap between vertical takeoff and landing agility and fixed-wing cruising efficiency. Building on the successful design of the spincopter platform, this work introduce

Changhong Liu, Jingjing Wang, Qiaosheng Zhang, Jinpeng Xu

We study the second-order asymptotics of optimal codes for covert communication over quasi-static multi-antenna fading channels, under the covertness metric of Kullback--Leibler (KL) divergence. In particular, we study all four cases regarding the availability of channel state information (CSI) for the legitimate transmitter and receiver, assume that the war

Cheng Yang, Yu Hao, Qi Zhang, Chuan Shi

When testing data and training data come from different distributions, deep neural networks (DNNs) will face significant safety risks in practical applications. Therefore, out-of-distribution (OOD) detection techniques, which can identify OOD samples at test time and alert the system, are urgently needed. Existing graph OOD detection methods usually characte

André Carneiro, Pedro T. Monteiro, Rui Henriques

Blood donation centers face challenges in matching supply with demand while managing donor availability. Although targeted outreach is important, it can cause donor fatigue via over-solicitation. Effective recruitment requires targeting the right donors at the right time, balancing constraints with donor convenience and eligibility. Despite extensive work on

Xiaoyu Huang, Yuxiang Ni, Zhongwei Zhang, Yangyu Guo

While spatial phonon coherence manifested through band folding is believed to be a key factor governing the anomalous thermal conductivity of periodic structures, we investigate phonon transport from the perspective of temporal coherence. Using mode-resolved analyses, we quantify temporal coherent contributions and elucidate the interplay between phonon cohe

Kevin Jäckel, Holger Grisk, Niklas Dornquast, Maik Gaerner

Altermagnets constitute an emerging materials platform for spintronic technologies by combining compensated magnetic order with ferromagnet-like spin-split electronic bands. Here, we investigate the proposed d-wave altermagnetic material RuO2 using circularly polarized ultrashort laser pulses. Time-resolved magneto-optical Kerr effect measurements, which are

Weixian Xu, Tiantian Mi, Yixiu Liu, Yang Nan

Can AI accelerate the development of AI itself? While recent agentic systems have shown strong performance on well-scoped tasks with rapid feedback, it remains unclear whether they can tackle the costly, long-horizon, and weakly supervised research loops that drive real AI progress. We present ASI-Evolve, an agentic framework for AI-for-AI research that clos

Daniel Arreola, Shlomo Gelaki

We classify equivalence classes of Hopf algebra quotient pairs $(D,\theta)$ of the Drinfeld double $D(G)$ of a finite group scheme $G$ over an algebraically closed field $\mathbf{k}$ of characteristic $p\ge 0$, in terms of group scheme-theoretical data. We prove that such Hopf algebra quotients $D$ are Hopf algebra extensions $\mathscr{O}(K)^{\mathrm{cop}}\#

Michael Chertkov

An agent that operates sequentially must incorporate new experience without forgetting old experience, under a fixed memory budget. We propose a framework in which memory is not a parameter vector but a stochastic process: a Bridge Diffusion on a replay interval $[0,1]$, whose terminal marginal encodes the present and whose intermediate marginals encode the

Keita Akutagawa, Shinsuke Imada, Munehito Shoda

Magnetic reconnection drives a wide range of astrophysical plasma phenomena, including solar flares, by converting magnetic energy into plasma energy through changes in magnetic field topology. Petschek reconnection is a magnetohydrodynamic (MHD) model in which magnetic field lines reconnect within a localized diffusion region, and a pair of switch-off slow

Julian Sturm, Daniel Fraunholz, Oliver Zeidler, Katharina Schaar

Mobile networks are essential for modern societies. The most recent generation of mobile networks will be even more ubiquitous than previous ones. Therefore, the security of these networks as part of the critical infrastructure with essential communication services is of the uttermost importance. However, these systems are still vulnerable to being compromis

C. Hall, L. N. H. P. Hall

Anitmatter-based propulsion is often cited as a physically plausible route to relativistic interstellar travel, and thus as a potential mechanism by which technologically advanced civilizations could expand throughout the galaxy. Its difficulty may be central to the resolution of Fermi's paradox. Since the Universe should be teaming with advanced technologic

Hengyu Zeng, Xin Gao, Guanghao Li, Yuxiang Yan

Continuous image tokenizers enable efficient visual generation, and those based on variational frameworks can learn smooth, structured latent representations through KL regularization. Yet this often leads to posterior collapse when using fewer tokens, where the encoder fails to encode informative features into the compressed latent space. To address this, w

Mingkun Tan, Xilu Wang, Michael Kloster, Tim W. Nattkemper

Label-scarce visual classification under decentralized and heterogeneous data is a fundamental challenge in pattern recognition, especially when sites exhibit partially overlapping class sets. While self-supervised federated learning (SSFL) offers a promising solution, existing studies commonly assume the same data heterogeneity pattern throughout pre-traini

Yang Shen, Zhenyi Yi, Ziyi Zhao, Lijun Sun

As AI agents evolve, the community is rapidly shifting from single Large Language Models (LLMs) to Multi-Agent Systems (MAS) to overcome cognitive bottlenecks in automated research. However, the optimal multi-agent coordination framework for these autonomous agents remains largely unexplored. In this paper, we present a systematic empirical study investigati

Sherif Abdelwahab

Always-on edge cameras generate continuous video streams where redundant frames degrade cross-modal retrieval by crowding correct results out of top-k search. This paper presents a streaming retrieval architecture: an on-device epsilon-net filter retains only semantically novel frames, building a denoised embedding index; a cross-modal adapter and cloud re-r

Johann-Ludwig Herzog, Mathis Jürgen Adler, Leonard Hackel, Yan Shu

Vision-langugage models (VLMs) have shown strong performance in computer vision (CV), yet their performance on remote sensing (RS) data remains limited due to the lack of large-scale, multi-sensor RS image-text datasets with diverse textual annotations. Existing datasets predominantly include aerial Red-Green-Blue imagery, with short or weakly grounded capti

Tanmoy Bar

This work presents a detailed covariance and correlation matrix analysis for experimentally measured cross sections obtained using the activation technique. Both statistical and systematic contributions to the covariance matrix were explicitly calculated using sensitivity coefficients. The detector efficiency was determined by refitting standard source data

Huichang Yun, Seungho Yoo

Recent advances in large AI models (VLMs and LLMs) and joint use of the 3D dense maps, enable mobile robots to provide more powerful and interactive services grounded in rich spatial context. However, deploying both heavy AI models and dense maps on edge robots is challenging under strict memory budgets. When the memory budget is exceeded, required keyframes

Krystal Guo, Ross J. Kang, Gabriëlle Zwaneveld

We investigate `almost counterexamples' to Seymour's second neighbourhood conjecture. In what we call Seymour-tight orientations, the size of the first neighbourhood of each vertex equals the size of its second neighbourhood. We give several examples and constructions. Specifically, we prove that the class of Seymour-tight orientations is closed under taking

M. Jakha, S. Mouslih, M. Ouhammou, R. Chahri

We investigate the impact of a circularly polarized laser field on the top quark decay process into a charged Higgs boson ($t\rightarrow bH^+$) within the type-I two Higgs doublet model. Our study aims to explore how an external electromagnetic field can modify key observables and potentially facilitate the experimental detection of the charged Higgs boson,

Hikaru Wakaura, Taiki Tanimae

When modelling decoherence in a biological spin system it is tempting to seek a critical rate beyond which the channel is entanglement-breaking (EB) and quantum resources are gone. We show that for the two channel families in which such a model would be posed, no critical rate exists. For uniform dephasing at rate $γ$ the partial transpose of the Choi state

Elna Svegborn, Armin Tavakoli

The most elementary prepare-and-measure scenarios have no independent measurement inputs. No inputs mean that quantum advantages require two indispensable ingredients: shared entanglement and measurements that can be adapted to the communicated messages. Understanding these scenarios is therefore conceptually natural, but also practically relevant, since the

Yuan Si, Ming Wang, Daming Li, Hanyuan Shi

Scratch is the most popular programming environment for novices, with over 1.15 billion projects created worldwide. Unlike traditional languages, correctness in Scratch is defined by visible behavior on the stage rather than by code structure alone, so programs that appear correct in the workspace can still fail at runtime due to timing, event ordering, or c

Hassan Ugail, Newton Howard

This paper introduces a biharmonic interpolatory subdivision framework on Riemannian manifolds. In the Euclidean setting, the six-point Deslauriers-Dubuc stencil is characterised as the unique minimiser of a discrete curvature-variation energy under symmetric six-point support and degree-five polynomial reproduction conditions, linking a classical interpolat

Xiangyang Xiao, Huaxun Huang, Rongxin Wu

In the development and maintenance of Android apps, the quick and accurate reproduction of user-reported bugs is crucial to ensure application quality and improve user satisfaction. However, this process is often time-consuming and complex. Therefore, there is a need for an automated approach that can explore the Application Under Test (AUT) and identify the

Peter Munch, Marc Fehling, Martin Kronbichler, Nils Margenberg

In this article, we solve the Stokes and Navier-Stokes equations with the deal$.$II finite-element library. In particular, we use its multigrid, adaptive-mesh, and matrix-free infrastructures to design efficient linear and nonlinear iterative solvers, respectively. We solve the stationary Stokes equations on hp-adaptive meshes with a hp-multigrid approach, t

Shuang Chen, Quanxin Shou, Hangting Chen, Yucheng Zhou

Unified multimodal models provide a natural and promising architecture for understanding diverse and complex real-world knowledge while generating high-quality images. However, they still rely primarily on frozen parametric knowledge, which makes them struggle with real-world image generation involving long-tail and knowledge-intensive concepts. Inspired by

Eduard Feireisl

This is a survey highlighting several recent results concerning well/ill posedness of the Euler system of gas dynamics. Solutions of the system are identified as limits of consistent approximations generated either by physically more complex problems, notably the Navier- Stokes-Fourier system, or by the approximate schemes in numerical experiments. The role

Zainab Alsuwaykit, Yousef Rajeh, Alexandre Kouyoumdjian, Steve Kieffer

Orthogonal graph layout algorithms aim to produce clear, compact, and readable network diagrams by arranging nodes and edges along horizontal and vertical lines, while minimizing bends and crossings. Most existing orthogonal layout methods focus primarily on quality criteria such as area usage, total edge length, and bend minimization. Explicitly controlling

Chiara Giverso, Denise Grappein, Stefano Scialò

Tumor growth beyond a critical size relies on the development of a functional vascular network, which ensures adequate oxygen and nutrient supply. In this work, we present a modeling framework based on an optimization-based 3D-1D coupling strategy to simulate perfusion in a tumoral tissue with growing mass, interacting with a dynamically evolving capillary n

Marco Baldovin, Marco Cattaneo, Dario Lucente, Paolo Muratore-Ginanneschi

In their seminal work, Fermi, Pasta, Ulam and Tsingou explored the connection between statistical mechanics and dynamical properties, such as chaos and ergodicity. Even today, seventy years later, the topic is not fully understood: while most results of statistical mechanics require the ergodic hypothesis to be rigorously proved, there are many indications t

Haichao Wang, Alexander Okupnik, Yuxing Han, Gene Wen

Long-range human movement generation remains a central challenge in computer vision and graphics. Generating coherent transitions across semantically distinct motion domains remains largely unexplored. This capability is particularly important for applications such as dance choreography, where movements must fluidly transition across diverse stylistic and se