April 2026 arXiv papers — page 70

Jiaying Meng, Bojie Li

Real-time multimodal agents transport raw audio and screenshots using networking stacks designed for human receivers, which optimize for perceptual fidelity and smooth playout. Yet agent models act as event-driven processors with no inherent sense of physical time, consuming task-relevant semantics rather than reconstructing signals in real time. This fundam

Alessandro Morosini, Matea Gjika, Tomaso Poggio, Pierfrancesco Beneventano

Modern neural networks can achieve high accuracy while remaining poorly calibrated, producing confidence estimates that do not match empirical correctness. Yet calibration is often treated as a post-hoc attribute. We take a different perspective: we study calibration as a training-time phenomenon on small vision tasks, and ask whether calibrated solutions ca

Zhiming Pan, Chen Lu, Fan Yang, Congjun Wu

Discovery of high-$T_c$ superconductivity (SC) in the bilayer nickelate series La$_3$Ni$_2$O$_7$ have attracted substantial interest, providing a new platform for exploring unconventional SC. Certain experimental evidence has pointed to a correlated electronic nature, which is the driving force responsible for its high critical temperature ($T_c$). This work

Sara Antonijevic, Danielle Sitalo, Brani Vidakovic

Incomplete reporting of diagnostic accuracy data remains a persistent problem in medical research. In many studies, only part of the 2x2 diagnostic table is reported, leaving denominators for diseased and non-diseased groups unknown and preventing direct calculation of sensitivity, specificity, predictive values, and related operating characteristics. To add

Bowen Li, Jiping Luo, Themistoklis Charalambous, Nikolaos Pappas

Timely information delivery in low-altitude networks is critical for many time-sensitive applications, such as unmanned aerial vehicle (UAV) navigation, inspection, and surveillance. The key challenge lies in balancing three competing factors: stringent data freshness requirements, UAV onboard energy consumption, and interference with terrestrial services. A

Ailing Wang, Hua Feng, Tao An, Yijia Zhang

We present high-sensitivity Very Long Baseline Interferometry (VLBI) observations of four ultraluminous X-ray sources (ULXs): Holmberg II X-1, IC 342 X-1, NGC 6946 X-1, and NGC 925 X-1. No compact emission was detected on milliarcsecond scales, with rms noise levels reaching approximately 5--20 $\mu$Jy. The corresponding $5\sigma$ flux density upper limits r

Sujoy Basak, Arpit Babbar, Harish Kumar, Praveen Chandrashekar

The relativistic hydrodynamics (RHD) equations can give rise to solutions which have shocks, contact discontinuities, and other sharp structures, which interact and evolve over time. Capturing these sharp waves effectively requires a mesh with high resolution, making the scheme computationally expensive. In this work, adaptive mesh refinement is used with th

Philip Trøst Kristensen, Thomas Kiel, Kurt Busch, Francesco Intravaia

Surface deformations of optical cavities and plasmonic nanoparticles are inevitable in nanophotonics. The random morphology changes of different realizations modify the associated resonance frequencies and quality factors, which may be characterized by specified distributions instead of their nominal values. As an alternative to statistical analyses based on

Fady Ibrahim, Guangjun Liu, Guanghui Wang

Vision Mamba, as a state space model (SSM), employs a zero-order hold (ZOH) discretization, which assumes that input signals remain constant between sampling instants. This assumption degrades temporal fidelity in dynamic visual environments and constrains the attainable accuracy of modern SSM-based vision models. In this paper, we present a systematic and c

Janna Wilhelmsen, Longzhu Liu, Harry Miyosi Silalahi, Suraya Kazi

Phase-gradient metasurfaces provide powerful wavefront control through two-dimensional arrangement of nanostructures acting as metaatoms. While dynamic tuning forms a major driver for future breakthroughs and applications in this area, current metaatoms are generally static or limited to operation in the infrared. Here, we present a metaatom that is both ele

Marco Mackaay, Vanessa Miemietz, Pedro Vaz

In this article, we develop a generalization of finitary birepresentation theory applicable to Soergel bimodules for infinite Coxeter groups. We establish a reduction process for the classification of simple birepresentations of almost finitary bicategories, and consider in detail the case of Soergel bimodules in extended affine type A.

Matthew Collinson

We display a family of Stone-type dualities linking categories of frames carrying pairs of modal operators to categories of spaces carrying a binary relation. Different notions of morphism used on the relational side lead to significant variations in the point construction. We show how the situation simplifies in the case of semicontinuous relations, allowin

Zoya Volovikova, Nikita Sorokin, Dmitriy Lukashevskiy, Aleksandr Panov

We introduce SuperIgor, a framework for instruction-following tasks. Unlike prior methods that rely on predefined subtasks, SuperIgor enables a language model to generate and refine high-level plans through a self-learning mechanism, reducing the need for manual dataset annotation. Our approach involves iterative co-training: an RL agent is trained to follow

Weicong Su, Zhuang Wang, Yi Ru-Ya Zhang

We investigate the geometric behavior of $\tau(E)$ for bounded finite-perimeter sets $E \subset \mathbb R^n$, where $\tau(E)$ is the trace constant introduced by Figalli--Maggi--Pratelli [Invent. Math. 2010]. This quantity is a key ingredient in proving a quantitative isoperimetric inequality with the optimal exponent. We first show that for every $\epsilon>

Seongmin Kim, Vincent R. Pascuzzi, Travis S. Humble, Thomas Beck

Many real-world problems are naturally formulated as higher-order optimization (HUBO) tasks involving dense, multi-variable interactions, which are challenging to solve with classical methods. Quantum optimization offers a promising route, but hardware constraints and limitations to quadratic formulations have hampered their practicality. Here, we develop a

Naizhong Xu

Modern retrieval-augmented generation (RAG) systems treat vector embeddings as static, context-free artifacts: an embedding has no notion of when it was created, how trustworthy its source is, or which other embeddings depend on it. This flattening of knowledge has a measurable cost: recent work on VersionRAG reports that conventional RAG achieves only 58% a

Ying Xiao, Shimiao Tang, Xitong Ling, Weiming Chen

Liver cancer, especially hepatocellular carcinoma (HCC), imposes a substantial global disease burden. Accurate diagnosis and prognostic assessment directly influence treatment selection and patient survival, and pathological examination remains the gold standard for liver cancer diagnosis. Identifying diverse tissue components and pathological subtypes on hi

Pasquale Ambrosio, Simone Ciani, Giovanni Cupini

We investigate the regularity of local weak solutions to evolution equations of the form \[ \partial_{t}u\,=\,\sum_{i=1}^{n}\,\partial_{x_{i}}\left[a_{i}(x,t)\,(\vert\partial_{x_{i}}u\vert-\delta_{i})_{+}^{p_{i}-1}\,\frac{\partial_{x_{i}}u}{\vert\partial_{x_{i}}u\vert}\right]\,\,\,\,\,\,\,\,\,\,\mathrm{in}\,\,\,\Omega_{T}\,=\,\Omega\times(0,T)\,, \] where $\

Jie Xu, Haaris Mehmood, Rogier Van Dalen, Karthikeyan Saravanan

Federated learning (FL) enables training of a global model while keeping raw data on end-devices. Despite this, FL has shown to leak private user information and thus in practice, it is often coupled with methods such as differential privacy (DP) and secure vector sum to provide formal privacy guarantees to its participants. In realistic cross-device deploym

Anif N. Shikder, Ramit Dey, Sayantan Auddy, Luisa Liboni

We establish a mathematical correspondence between state space models, a state-of-the-art architecture for capturing long-range dependencies in data, and an exactly solvable nonlinear oscillator network. As a specific example of this general correspondence, we analyze the diagonal linear time-invariant implementation of the Structured State Space Sequence mo

Qian Chen, Yuehao Chen, Qiang Wang, Lei Zhu

Retinal laser speckle contrast imaging (LSCI) is a noninvasive optical modality for monitoring retinal blood flow dynamics. However, conventional temporal LSCI (tLSCI) reconstruction relies on sufficiently long speckle sequences to obtain stable temporal statistics, which makes it vulnerable to acquisition disturbances and limits effective temporal resolutio

Ruda Guo, Yi Liu, Cong Xiao, Zhe Yuan

We develop a theory for the second-order time-reversal-odd ($\mathcal{T}$-odd) angular-momentum current, incorporating both spin and orbital components. We reveal that besides spin and orbital Berry curvature dipoles, $\mathcal{T}$-odd nonlinear angular-momentum current can originate from disorder-induced mechanisms including coordinate shift, side-jump spin

Mohsen Asghari Ilani, Yaser Mike Banad

This paper presents an IoT-enhanced deep learning framework for automated crack detection in Additive Manufacturing (AM) surfaces using convolutional neural networks (CNNs). By integrating IoT-enabled real-time monitoring, high-resolution imaging, and edge computing, the system enables continuous in-situ defect detection and classification. Real-time data ac

Keli Niu, He Zhao, Qianhui Men

In low-resource settings, blind-sweep ultrasound provides a practical and accessible method for identifying fetal growth restriction. However, unlike freehand ultrasound which is subjectively controlled, detection of biometry plane in blind-sweep ultrasound is more challenging due to the uncontrolled fetal structure to be observed and the variaties of obliqu

Syed Sajid Ullah, Muhammad Zunair Zamir, Ahsan Ishfaq, Salman Khan

Accurate vehicle detection is a critical component of autonomous driving, traffic surveillance, and intelligent transportation systems. This paper presents an enhanced YOLOv8n-based model that integrates the Ghost Module, Convolutional Block Attention Module (CBAM), and Deformable Convolutional Networks v2 (DCNv2) to improve detection performance. The Ghost

Martin Bachratý

A skew morphism of a finite group $B$ is a permutation of $B$ fixing the identity and satisfying $\varphi(xy) = \varphi(x)\varphi^{i_x}(y)$ for some integers $i_x$ indexed by $x \in B$. The enumeration of skew morphisms of finite cyclic groups remains an open problem. The most substantial progress to date concerns cyclic $p$-groups with $p$ odd, for which a

Micha Christoph, Sahar Diskin, Lyuben Lichev, Benny Sudakov

We study the edge-expansion of the graph of a random $0/1$ polytope $P^d_p$, defined as the convex hull of a random subset of the points in $\{0,1\}^d$ where every point is retained independently and with probability $p$. This problem was introduced more than twenty years ago in a work of Gillmann and Kaibel, and has been extensively studied ever since. We p

Ji Ho Bae

Let H(k) be the smallest N such that every finite coloring of [N] contains a monochromatic or rainbow k-term arithmetic progression. Erd\H{o}s and Graham asked whether $H(k)^{1/k}/k \to \infty$ (Problem #190 of the Erd\H{o}s Problems database). We prove that there is an absolute constant $k_0 \ge 2$ such that for all $k \ge k_0$, \[ H(k)^{1/k}/k \ge (1/e - \

Jian Zhang, Shuai Mu, Cheng Tan

Checking whether database transactions adhere to isolation levels is a crucial yet challenging problem. We present Boomslang, the first general-purpose checking framework capable of verifying configurations that were previously uncheckable. Boomslang advances beyond prior work in three key aspects: (1) it supports arbitrary operation types provided by modern

Patrick Wilk, Ethan Cantor, Yikui Liu, Jie Li

The ongoing shift towards decentralization of the electric energy sector, driven by the growing electrification across end-use sectors, and widespread adoption of distributed energy resources (DERs), necessitates their active participation in the electricity markets to support grid operations. Furthermore, with bi-directional energy and communication flows b

Eduarda Caldeira, Guray Ozgur, Fadi Boutros, Naser Damer

This study investigates the impact of face image background correction through segmentation on face recognition and morphing attack detection performance in realistic, unconstrained image capture scenarios. The motivation is driven by operational biometric systems such as the European Entry/Exit System (EES), which require facial enrolment at airports and ot

Filipe Rodrigues da Silva, Azadeh Mohammadi

We present a non-Abelian model for magnetic monopoles in inhomogeneous media, based on a generalization of the standard 't~Hooft-Polyakov model. The medium is described by spatially dependent couplings in the gauge and scalar sectors, constrained by $P(|\Phi|,r)M(|\Phi|,r)=1$ so that the Bogomol'nyi-Prasad-Sommerfield (BPS) bound is preserved. For static sph

Sotiris Droulias, Giorgos Stratidakis, Angeliki Alexiou

Wavefront engineering for applications in near-field wireless connectivity is gradually becoming common ground. In this landscape, beams that propagate on bent paths are ideal candidates for dynamic blockage avoidance and suppression of potential eavesdropping. In this work we study the physical layer security offered by bending beams, and we demonstrate the

Suveen Ellawela

We study emergent social dynamics in LLM agents playing The Resistance: Avalon, a hidden-role deception game. Unlike prior work on single-game performance, our agents play repeated games while retaining memory of previous interactions, including who played which roles and how they behaved, enabling us to study how social dynamics evolve. Across 188 games, tw

Yan Shao, Zhen-hua Zhao

Low-scale leptogenesis scenarios, such as the resonant or ARS leptogenesis, typically require a highly degenerate mass spectrum of right-handed neutrinos (RHNs). This requirement can be circumvented by extending the seesaw framework with a scalar singlet $S$ that couples to RHNs via the $S N^{}_I N^{}_J$ terms (with $I \neq J$), which opens up new decay chan

Antoine Faulconnier, Laura Michel, Mokhtar Adda-Bedia, Jérôme Crassous

Laddering is the propagation of a topological defect in an everyday-life material: weft knitted fabrics, following a broken thread or a dropped stitch. What is a minor frustration when damaging a pair of tights is a more serious issue for industrial-scale production, but might inspire new solutions to limit and mitigate damage to architected materials. In th

Steven A. Fromm, Vassilios Mewes, O. E. Bronson Messer, Eric J. Lentz

We present formulations of effective potentials suitable for approximating general relativistic effects in Newtonian simulations of core-collapse supernovae. Assuming a spherically symmetric spacetime and a stress-energy tensor that includes both fluid and neutrino contributions, Eulerian and Lagrangian projections of the Einstein equations are made to deter

Tianyuan Wang, Daniël M. Pelt, Felix Lucka, Tristan van Leeuwen

Traditional X-ray computed tomography (CT) scanning strategies typically select projection angles uniformly and allocate dose equally. In practice, however, CT scans often need to be fast, radiation-efficient, and adaptive. Sparse-view tomography addresses these requirements by reducing both the number of angles and the total dose budget. Under such constrai

Hartosh Singh Bal

Let \(G\) be a finite simple graph and let \(T\) be its Hashimoto operator on the directed-edge space. We show that edge reversal induces a canonical symmetric/antisymmetric splitting under which \(T\) acquires an explicit \(2\times 2\) block form. The diagonal blocks are \(\tfrac12 L(G)\) and \(-\tfrac12 A(G)\), where \(L(G)\) is the line-graph adjacency an

Fariz Ikhwantri, Dusica Marijan

An assurance case is a structured argument document that justifies claims about a system's requirements or properties, which are supported by evidence. In regulated domains, these are crucial for meeting compliance and safety requirements to industry standards. We propose a graph diagnostic framework for analysing the structure and provenance of assurance ca

Jumin Kim, Seungmin Baek, Hwayong Nam, Minbok Wi

As DRAM scaling exacerbates RowHammer, DDR5 introduces per-row activation counting (PRAC) to track aggressor activity. However, PRAC indiscriminately increments counters on every activation -- including benign refreshes -- while relying solely on explicit RFM operations for resets. Consequently, counters saturate even in an idle bank, triggering cascading mi

Keqi Chen, Séraphin Baributsa, Lilien Schewski, Vinkle Srivastav

Purpose: Gaze-following, the task of inferring where individuals are looking, has been widely studied in computer vision, advancing research in visual attention modeling, social scene understanding, and human-robot interaction. However, gaze-following has never been explored in the operating room (OR), a complex, high-stakes environment where visual attentio

Víctor Zapatero, Marcos Curty

Device-independence is the gold standard of quantum cryptography. To meet this standard, a central assumption is that no information leakage occurs during protocol execution. We relax this assumption by analyzing CHSH-based randomness certification and key distribution with partial leakage of the inputs, modeled in terms of a noisy channel. Our results quant

Caiyan Li, Guofang Wang, Wei Wei

Let $n\ge 25$ be an integer. In this paper, we construct a smooth metric $g_{0}$ on $\mathbb{S}^n$ with the property that the set of metrics in the conformal class of $g_{0}$ having positive scalar curvature and positive constant quotient $Q/R$ is non-compact. Equivalently, we construct families of solutions exhibiting blow-up behavior for the following equa

Muzhi Zhu, Shunyao Jiang, Huanyi Zheng, Zekai Luo

Spatial intelligence is essential for multimodal large language models, yet current benchmarks largely assess it only from an understanding perspective. We ask whether modern generative or unified multimodal models also possess generative spatial intelligence (GSI), the ability to respect and manipulate 3D spatial constraints during image generation, and whe

Umberto Domanti, Moritz Mock, Sergio Agnoli, Antonella De Angeli

Automatic systems are increasingly used to assess the originality of responses in creative tasks. They offer a potential solution to key limitations of human assessment (cost, fatigue, and subjectivity), but there is preliminary evidence of a self-preference bias. Accordingly, automatic systems tend to prefer outcomes that are more closely related to their s

Houman Safaai

Modeling high-dimensional dependencies while keeping likelihoods tractable remains challenging. Classical vine-copula pipelines are interpretable but can be expensive, while many neural estimators are flexible but less structured. In this work, we propose Vine Denoising Copula (VDC), an amortized vine-copula pipeline for continuous-data, simplified-vine depe

Giovanni Savaré

The equilibrium shape of a thin, elastic, inextensible ribbon minimizes its bending energy. It has been shown that, as the width of the ribbon tends to zero, the bending energy Gamma-converges to the so called Sadowsky functional. In this paper we consider geometrically frustrated anisotropic ribbons with a possibly curved reference configuration. We prove t

Pavle Pandžić, Ana Prlić, Vladimír Souček, Vít Tuček

We classify unitary highest weight modules with a given integral infinitesimal character for the real Lie algebras $\mathfrak{su}(p,q)$ and $\mathfrak{so}^*(2n)$. We treat both regular and singular cases. For $\mathfrak{su}(p,q)$ we identify the unitarizable modules in the Hasse diagrams of the highest weight orbit. Analogous results for the other Hermitian

Robert Lipshitz, Peter Ozsváth

Fix a 3-manifold $Y$ with boundary $F\amalg F$ and an orientation-preserving involution $\tau: Y\to Y$ exchanging the boundary components, with nonempty fixed set. To an appropriate kind of Heegaard diagram for $Y$, we describe how to associate a module over the bordered Heegaard Floer algebra of $F$. These modules satisfy a gluing, or pairing, theorem, and

Seunghyun Park, Yuanyuan Lei

While LLMs demonstrate impressive reasoning capabilities, they remain fragile in multi-step logical deduction, where a single transition error can propagate through the entire reasoning chain, leading to unstable performance. In this work, we identify logical connectives as primary points of this structural fragility. Through empirical analysis, we show that

Biswa Sengupta, Jinhua Wang

Long-horizon language-model agents are dominated, in lines of code and in operational complexity, not by their underlying model but by the harness that wraps it: context compaction, tool caching, semantic memory, trajectory reuse, speculative tool prediction, and the glue that binds the model to a sandboxed execution environment. We argue that harness design

P. A. Grizzi, A. A. Aligia, P. Roura-Bas

We investigate the topology of the different phases of the extended Su-Schrieffer-Heeger (eSSH) model, which includes hopping processes between translationally inequivalent atoms beyond nearest neighbors. Exact analytical expressions for the edge states of a semi-infinite eSSH chain are derived, with wave functions that decay exponentially from the boundary

Serhii Zabolotnii

Automatically filling Case Report Forms (CRFs) from clinical notes is challenging due to noisy language, strict output contracts, and the high cost of false positives. We describe our CL4Health 2026 submission for Dyspnea CRF filling (134 items) using a contract-driven two-stage design grounded in Schema-Guided Reasoning (SGR). The key task property is extre

ATLAS Collaboration

High-energy photonuclear ($\gamma+A$) scattering in ultra-peripheral heavy-ion collisions provides a unique probe of nuclear structure. This Letter studies the dependence of $\gamma+A$ jet production in ultra-peripheral Pb+Pb collisions at $\sqrt{s_{_\text{NN}}} = 5.02$ TeV on the presence of forward neutron emission from either nucleus. The data was taken i

Matthew Mosse, Jonathan J. P. Peters, Eoin Moynihan, James A. Gott

Scanning transmission electron microscopy (STEM) is widely used tool for materials characterisation. However, being a scanned technique, STEM is susceptible to sample, stage or beam drift, manifesting as distortions within images or movement in the field-of-view during multi-frame imaging. Often this is corrected post-acquisition using image registration of

Yuhang Wu, Qinyuan Liu, Qiuyang Zhao, Qingwei Chong

Currently, Large Language Models (LLMs) feature a diversified architectural landscape, including traditional Transformer, GateDeltaNet, and Mamba. However, the evolutionary laws of hierarchical representations, task knowledge formation positions, and network robustness bottleneck mechanisms in various LLM architectures remain unclear, posing core challenges

Sisi Miao, Mert Birincioglu, Laurent Schmalen

We propose an enhanced Chase-Pyndiah decoder that scales extrinsic messages based on decoder confidence of the component decoder, achieving a 0.1 dB gain over the original with negligible complexity increase.

Alexandru Chirvasitu

We construct examples of abelian categories with no non-zero injective (or projective) objects satisfying Grothendieck's AB5 condition. The procedure combines Rickard's examples of AB5 categories without products but some non-trivial injectives (also addressing an apparent gap in the literature) with a 2-functorial construct attaching to any category $\mathc

Amir Shetaia, Sean Kauffman

Modern distributed systems produce massive, heterogeneous logs essential for reliability, security, and anomaly detection. Converting these free-form messages into structured templates (log parsing) is challenging due to evolving formats and limited labeled data. Machine-learning-based parsers like Drain are fast but accuracy often degrades on complex variab

L. Westrich, B. Shergelashvili, H. Fichtner, V. N. Melnik

Polytropic models of stellar winds remain to be useful tools because they allow for a simple description of the energy balance of the expanding plasma without explicitly specifying potentially complex energy transport processes like, e.g., heat conduction or extended wave heating. Among recent applications to stellar winds and to the solar wind was a study o

Nicola Bariletto, Huy Nguyen, Nhat Ho, Alessandro Rinaldo

Mixture-of-experts models provide a flexible framework for learning complex probabilistic input-output relationships by combining multiple expert models through an input-dependent gating mechanism. These models have become increasingly prominent in modern machine learning, yet their theoretical properties in the Bayesian framework remain largely unexplored.

Xiaofeng Jin, Wentao Huo, Lingwei Ma, Zhenqiu Zhang

We establish the homogenization results for a class of nonlocal operators of convolution type with integrable jumping kernel $p$ multiplied by rapidly oscillating periodic or locally periodic coefficients. The associated measure $p(z)dz$ is assumed to belong to the domain of attraction of a symmetric $\alpha$-stable law. We also assume that $p$ satisfies a p

Yassine Turki, Vinko Sabolčec, Bettina Messmer, Martin Jaggi

As Large Language Models (LLMs) scale, data curation has shifted from maximizing volume to optimizing the signal-to-noise ratio by performing quality filtering. However, for many languages, native high quality data is insufficient to train robust quality classifiers. This work investigates the idea that quality markers in embedding space may show cross-lingu

Shuai Chen, Chengzhi Zhang

Scientific progress depends on the continual generation of innovative re-search ideas. However, the rapid growth of scientific literature has greatly increased the cost of knowledge filtering, making it harder for researchers to identify novel directions. Although existing large language model (LLM)-based methods show promise in research idea generation, the

Xingwei Shi, Geng Li, Zhan Wang, Chuqi Zhang

Nonmagnetic kagome metals and superconductors AV3Sb5 (A = K, Rb, Cs) host unconventional charge density wave (CDW) and superconducting (SC) phases accompanied by multiple electronic symmetry breaking. Due to the centrosymmetric crystal structure, inversion symmetry has generally been assumed to hold. Here, using scanning tunneling microscopy complemented by

Rebecca L. Johnson

In measurement theory, instruments do not simply record reality; they help constitute what is observed. The same holds for generative AI evaluation: benchmarks do not just measure, they shape what models appear to be. Functionalist benchmarks treat models as isolated predictors, while prescriptive approaches assess what systems ought to be. Both obscure the

Zimu Jia, Mingjie Xu, Andrew Estornell, Jiaheng Wei

The efficacy of Large Vision-Language Models (LVLMs) is critically dependent on the quality of their training data, requiring a precise balance between visual fidelity and instruction-following capability. Existing datasets, however, are plagued by inconsistent quality, and current data filtering methods rely on coarse-grained scores that lack the granularit

Guyue Hu, Hao Song, Yuxing Tong, Duzhi Yuan

Referring detection refers to locate the target referred by natural languages, which has recently attracted growing research interests. However, existing datasets are limited to ground images with large object centered in relative small scenes. This paper introduces a large-scale challenging dataset for referring detection in aerial images, termed as RefAeri

Riccardo Conte, Lucienne van der Geest, Minu Sheeja, Przemyslaw Gawel

Voltage-driven memristive switching has been reported in molecular junctions, yet its microscopic origin often remains elusive. Here, we study three rigid OPE-like derivatives that lack an obvious internal switching pathway using mechanically controlled break junctions (MCBJs) and observe non-volatile, bistable hysteretic IV characteristics at cryogenic temp

Gianmarco Gatti, Amalie H. Svaneborg, Wu Bing, Gesa-R. Siemann

The bulk and surface electronic structure of MoAlB(010) is studied by a combination of angle-resolved photoemission spectroscopy and density functional calculations. The observed bulk Fermi-level crossings agree with the previously reported bulk Fermi surface of the material. Additionally, we find several surface states in the wide projected bulk band gaps a

Mingze Sun, Cheng Zeng, Jiansong Pei, Junhao Chen

Skeleton generation is essential for animating 3D assets, but current deep learning methods remain limited: they cannot handle the growing structural complexity of modern models and offer minimal controllability, creating a major bottleneck for real-world animation workflows. To address this, we propose an animator-centric SG framework that achieves high-qua

Claudia Magi, Peter Schuerger, David Lauvergnat, Federica Agostini

We employ the exact factorization of a multi-component wavefunction to analyze the dynamics of interacting photons, electrons and nuclei. We consider physical situations emerging in the regime of strong coupling between light excitations and molecular - electronic excitations, giving rise to the so-called molecular polaritons. Nonadiabatic molecular dynamics

Wenqing Dai, Jan Herbst, Jan Petershans, Christoph Lipps

Reconfigurable Intelligent Surfaces (RIS) have emerged as a key enabler for programmable wireless environments in future Beyond-5G (B5G) and 6G networks. In the meantime, Integrated Sensing and Communication (ISAC) and Physical-Layer Security (PLS) are becoming essential functionalities for next-generation wireless systems, particularly in safety and mission

Emma Nel, Nicholas Hale

In this paper, we present a stable and efficient approach for constructing Laguerre pseudospectral differentiation matrices. The proposed method reformulates the off-diagonal entries and computes all required quantities simultaneously using an existing fast algorithm that also generates the collocation nodes. For the diagonal entries, a closed-form expressio

Hawau Olamide Toyin, Mutiah Apampa, Toluwani Aremu, Humaid Alblooshi

Atypical speech is receiving greater attention in speech technology research, but much of this work unfolds with limited interdisciplinary dialogue. For stuttered speech in particular, it is widely recognised that current speech recognition systems fall short in practice, and current evaluation methods and research priorities are not systematically grounded

Tapas Kumar Pa, Dibakar Ghosh

The Murali-Lakshmanan-Chua (MLC) circuit is a well-recognized prominent nonlinear, nonautonomous, and dissipative electronic circuit having a versatile chaotic nature. Unraveling the dynamical synergy responsible for the genesis of extreme events in nonlinear dynamical systems is a prolific and spellbinding research area. The present study unveils the dynami

Dan-Dan Yuan, Jia-Geng Jiao, Yu-Qi Lei, Jun-Xi Shi

Chaos in extreme-mass-ratio inspirals is often thought to require unrealistically large secondary spins, making its astrophysical relevance uncertain. However, we find that chaos persists across the astrophysically realistic spin range for a spinning secondary orbiting a Schwarzschild black hole. This nonintegrable dynamics leaves clear signatures in the emi

Adam Cole, Mick Grierson

We present AttentionBender, a tool that manipulates cross-attention in Video Diffusion Transformers to help artists probe the internal mechanics of black-box video generation. While generative outputs are increasingly realistic, prompt-only control limits artists' ability to build intuition for the model's material process or to work beyond its default tende

Mohammed Zeehan Saleheen, Markus Wagner, Reza Razzaghi, Hao Wang

Reliable operation is a central motivation for deploying renewable-based microgrids. This paper presents a systematic rapid review that positions reliability as the central organizing principle for microgrid design. Specifically, this review systematically synthesizes recent literature to examine how planning assumptions, optimization formulations, operation

Anar Yeginbergen, Maite Oronoz, Rodrigo Agerri

This paper investigates Multilingual Medical Question Answering across high-resource (English, Spanish, French, Italian) and low-resource (Basque, Kazakh) languages. We evaluate three types of external evidence sources across models of varying size: curated repositories of specialized medical knowledge, web-retrieved content, and explanations from LLM's para

Eric Tönges, Andrea Schoen, Frank Marten, Marco Pau

This paper outlines a pathway towards active operation of lowvoltage distribution grids. In these grids, the growing deployment of distributed generation, controllable demand and storage, together with the roll-out of intelligent metering systems, creates new requirements and opportunities for distribution system operators. On the basis of the German and Eur

Jiayi Hao, Chengzhi Zhang

Research methods constitute an indispensable tool for scholars engaged in scientific inquiry. Investigating how scholars use research methods throughout their careers can reveal distinct patterns in method adoption, providing valuable insights for novice researchers in selecting appropriate methods. This study employs a comprehensive dataset comprising full-

Markus Klemetti, Ran Levi, Henri Riihimaki, Daniel Solch

Let $C_\bullet$ be a simplicial object in the category $Cat$ of small categories. For a field $k$, taking the Grothendieck groups of isomorphism classes of $kC_n$-modules gives rise to a cochain complex, whose cohomology, which we refer to as representation cohomology, is the object studied in this article. In particular, to any small category $C$, we associ

An-Xiao Han, Peng-Yu Duan, Ming-Ze Ma, Xi Chen

A particular interest on two-dimensional turbulence is the inverse energy cascade from small to large sales, which leads to an energy condensation accompanied by the formation of large-scale vortical structures. Indeed, such a phenomenon is observed in the two-dimensional channel (2DCH) with large Reynolds numbers, where prominent large-scale wavy structures

D. Borthwick, S. Eswarathasan, P. D. Hislop

We prove spectral properties for random Landau Schr\"odinger operators on $L^2(\mathbb{R}^2)$ with bounded, random potentials supported in a square $\Lambda_L \subset \mathbb{R}^2$ of side length $L>0$, using semiclassical pseudodifferential calculus. The semiclassical parameter $h$ is the inverse of the magnetic field strength $B > 0$. By means of the Grush

Viet-Man Le, Thi Ngoc Trang Tran, Sebastian Lubos, Alexander Felfernig

We study whether Large Language Models (LLMs) can perform feature model analysis operations (AOs) directly on semi-formal textual blueprints, i.e., concise constrained-language descriptions of feature hierarchies and constraints, enabling early validation in Software Product Line scoping. Using 12 state-of-the-art LLMs and 16 standard AOs, we compare their o

Nan Xu, Shiheng Li, Shengchao Hou

We propose a new approach for a practical two-stage Optical Music Recognition (OMR) pipeline, with a particular focus on its second stage. Given symbol and event candidates from the visual pipeline, we decode them into an editable, verifiable, and exportable score structure. We focus on complex polyphonic staff notation, especially piano scores, where voice

Jiamu Guo, Hailang Jia, Guanxiong Shen, Junqing Zhang

Physical layer (PHY) steganography conceals secrets by making subtle modifications to transmitted radio waveforms, which can be applied to establish covert communication systems. Given the widespread deployment of Wi-Fi infrastructures, hiding secrets within Wi-Fi transmissions exhibits significant covertness and has attracted increasing research attention.

Ryota Tajima

Let $F^{+}$ be a mock modular form associated to a normalized newform $g$. K. Bringmann et. al. obtained a $p$-adic modular form starting from $F^{+}$ by adding a suitable linear combination of Eichler integrals of $g(q)$ and $g(q^{p})$. We denote the coefficients of the Eichler integrals of $g(q)$ and $g(q^{p})$ by $\gamma_{g}$ and $\delta_{g}$. These const

Ruben Van Assche, Sarah Masaad, Peter Bienstman

Photonic reservoir computing is a machine learning paradigm in which a recurrent neural network remains fixed while only the output weights are trained. This makes it a well-suited approach for high-speed signal equalisation in optical communication systems, offering a trainable, low-power, and low-complexity solution. However, achieving strong performance t

Jonas Eppelt, Torben Ferber

The Belle~II electromagnetic calorimeter consists of 8376 CsI(Tl) scintillation crystals and is not only used for measuring electromagnetic particles but also for identifying and determining the position of hadrons, particularly neutral\textbf{} hadrons. Recent data-taking periods have presented challenges for the current clustering method: Firstly, the reco

Benjamin Hollering, Pratik Misra, Nils Sturma

Determining identifiability of causal effects from observational data under latent confounding is a central challenge in causal inference. For linear structural causal models, identifiability of causal effects is decidable through symbolic computation. However, standard approaches based on Gr\"obner bases become computationally infeasible beyond small settin

Thomas Rocke, Thomas Hudson, Richard Beanland, James Kermode

We present Atomic Cluster Expansion (ACE) and MACE models trained on a new dataset of Density Functional Theory (DFT) calculations, constructed for the task of studying the mobility of dislocations in Indium Phosphide (InP). The models are validated in a suite of tests against RSCAN DFT, and compared with previously published potentials from literature. Our

Andreas Klippel

We study the random loop model with crosses and bars on sparse random graphs. Our main objective is to prove the existence of macroscopic loops, in the sense that a loop visits a positive proportion of the vertices. We develop a deterministic drift method on arbitrary finite graphs based on three ingredients: a local split--merge--rewire analysis for the loo

Matthias Deiml, Daniel Peterseim

Quantum linear system solvers typically realize the inverse map as a polynomial transformation of the spectrum, so their practical cost hinges on implementing this transformation at a low polynomial degree. We introduce constrained optimal polynomials as a framework for this task, drawing on classical Krylov subspace theory. Within this framework, we develop

Jingyi Zheng, Tianyi Hu, Yule Liu, Zhen Sun

Current benchmarks for evaluating large language models (LLMs) in social media moderation completely overlook a serious threat: covert advertisements, which disguise themselves as regular posts to deceive and mislead consumers into making purchases, leading to significant ethical and legal concerns. In this paper, we present the CHASM, a first-of-its-kind da

Ashutosh Kinikar, Vukan Levajac, Kristof Moors, George Simion

We present a flexible modeling framework for flopping-mode spin qubits that captures the spatial structure of the double-well confinement and magnetic-field-gradient profile going beyond conventional low-energy descriptions. By using this approach, we simulate electric dipole spin resonance-based single-qubit control and evaluate the frequency and spectral p

Zirui Niu, Antoine Girard, Giordano Scarciotti

Controlling complex dynamical systems to satisfy sophisticated specifications remains a significant challenge in modern engineering. A promising approach to this problem is the approximate simulation-based hierarchical control (ASHC) technique. In this method, a simplified representation of the complex system, called the abstract system, is first designed an

Jesus Gonzalez-Rosa, Alexis Nikolakopoulos, Maria B. Barbaro, Juan A. Caballero

In this work, we present a detailed comparison of the SuSAv2 (SuperScaling Approach version 2) and RDWIA (Relativistic Distorted-Wave Impulse Approximation) models with measurements of charged-current neutrino-induced single-pion production from different experiments (T2K, MINERvA and MiniBooNE), studying the differences between the two theoretical descripti