April 2026 arXiv papers — page 18

Emilie Durrieu, Christophe Hurter, Philippe Muller, Victor Boutin

When humans play geolocation games such as GeoGuessr, they rely on concrete visual cues, such as road markings, vegetation, or architectural details, to infer where an image was captured. Whether image geolocation models rely on similar object-level evidence remains difficult to determine, as attribution methods like Grad-CAM typically highlight diffuse regi

Romeo Valentin

Safety-critical prediction systems, such as autonomous vehicles, weather forecasters, and medical monitors, commonly rely on probabilistic forecasters. These forecasters make predictions about possible future outcomes, and their quality and robustness needs to be validated and certified. Often, only accuracy -- the mean of the predictions -- is evaluated aga

Nick Theisen, Peer Neubert

Hyperspectral imaging (HSI) semantic segmentation typically relies on in-domain training, but limited data availability often restricts model performance in real-world applications. Current approaches to leverage foundation models in proximal sensing use cross-modality techniques, bridging RGB and HSI to exploit vision foundation models. However, these metho

Lin Sun, Wang Dexian, Jingang Huang, Linglin Zhang

Industrial Retrieval-Augmented Generation (RAG) systems depend on optical character recognition (OCR) to transform visual documents into text. Existing OCR benchmarks rely on character-level metrics, which inadequately measure downstream RAG effectiveness under real-world conditions. We introduce an OCR benchmark for industrial RAG systems covering 11 challe

L. L. T. C. Jansen, E. Petri, M. van Berkel, W. P. M. H. Heemels

Nuclear fusion is a promising clean energy source in which deuterium and tritium fuse inside a magnetically confined plasma in a tokamak, releasing energy. A key challenge on the route to practical nuclear fusion is the control of the plasma density which has to be done through adding fuel in the form of deuterium and tritium to the plasma. Pellet injection,

Nadav Yovel, Eyal Heifetz

The internal dynamics of baroclinic fronts are governed by a fundamental interplay: turbulent eddies systematically act to disrupt thermal wind balance, with baroclinic eddies flattening isopycnals and barotropic momentum fluxes intensifying the primary jet, while the ageostrophic overturning circulation acts to restore it. In quasi-balanced models, this res

Do Won Park, Samuele Bordini, Giorgio Grioli, Manuel G. Catalano

As with every emerging technology, new tools in the hands of artists reshape the nature of artwork creation. Current frameworks for robotics in arts deploy the robot as an autonomous creator or a collaborator, thus leaving a certain gap between the human artist and the machine. Now, we stand at the dawn of an era where artists can escape physical limitations

Dmitry Pasechnyuk-Vilensky

We study sequential interventions under prerequisite constraints. In this setting, admissible intervention sequences are paths in the ideal lattice of a finite prerequisite poset rather than unconstrained action strings. We give an exact local-to-global theory of order sensitivity on this state space. First, we prove that any two admissible paths with the sa

Mats Julius Stensrud

Target trial emulation has improved comparative effectiveness research by making the causal question, assumptions, and analysis plan explicit. However, target trial protocols are usually developed iteratively. After examining the data, investigators revise the protocol to reflect which target trials the observational data can realistically support. While thi

Francesco Daghero, Mahyar Tourchi Moghaddam, Mikkel Baun Kjærgaard

Industrial systems increasingly depend on Machine Learning (ML), and operate on heterogeneous nodes that must satisfy tight latency, energy, and memory constraints. Dynamic ML models, which reconfigure their computational footprint at runtime, promise high energy efficiency and lower average latency for modest accuracy tradeoffs; however, their deployment is

Yijia Li, Junkai Chen, Xing Hu, Xin Xia

Large Language Models (LLMs) have become widely used for Software Engineering (SE) tasks, spanning from function-level code generation to complex repository-level workflows. However, the high latency of autoregressive inference remains a significant bottleneck, hindering their deployment in interactive environments. While Speculative Decoding (SD) offers a p

Mengzhu Xu, Nemanja Cabrilo, Merel van Gilst, Jean-Paul Linnartz

Accurate estimation of the human circadian phase plays an important role in personalized health monitoring, but most existing wearable-based approaches operate retrospectively and require full circadian cycle recordings, leading to high estimation latency and substantial data and computational burden for real-time deployment on edge devices. In this study, w

Jake Mendelsohn, Simone Scaringi, Martina Veresvarska, Krystian Iłkiewicz

Cataclysmic variables can show rapid increases in optical flux. Intermediate polars (IPs), a subset with strong magnetic fields that disrupt the inner accretion disc, have been thought to possess truncated discs that rarely undergo the disc-instability outbursts seen in dwarf novae. However, the discovery of micronovae and magnetic-gating bursts suggests tha

Kecen Li, Chen Gong, Zinan Lin, Tianhao Wang

Differentially private (DP) contrastive learning aims to learn general-purpose representations from sensitive data, alleviating the privacy leakage concerns of organizations deploying or sharing embedding models trained on private user content. However, existing approaches suffer from severe utility degradation due to the over-strong inter-sample dependency

Giovanna Tosato, Leon Merker, Monika Vogler, Michael Selzer

The time-consuming formation process critically impacts the longevity of sodium-ion coin cells and End Of Life (EOL) performance. This study aims to optimize formation protocols for duration efficiency, targeting high-performance outcomes while minimizing the number of experiments to reduce resource consumption and accelerate discovery. Specifically, we cons

Ignacio Baena-Jimenez, Angel Ballesteros, Ivan Gutierrez-Sagredo

The Fock-Darwin (FD) quantum system describes the motion on the plane of a charged particle under the action of an isotropic oscillator potential together with a perpendicular constant magnetic field. When the isotropic oscillator is suppressed, the FD system leads to the Landau Hamiltonian with infinitely degenerate Landau levels. The Fock-Darwin-Darboux (F

Tibor Kiss, Paweł Pasteczka

We show that every family of quasi-arithmetic means generated by (a subset of) $\mathcal{C}^1$ functions with nonvanishing derivative which is bounded (from below or from above) by a quasi-arithmetic mean, possesses the best (lower or upper) bound which is a quasi-arithmetic mean generated by a function belonging to the same family.

Bo Cheng, Songjun Cao, Xiaoming Zhang, Jie Chen

Achieving robust generalization against unseen attacks remains a challenge in Audio Deepfake Detection (ADD), driven by the rapid evolution of generative models. To address this, we propose a framework centered on hard sample classification. The core idea is that a model capable of distinguishing challenging hard samples is inherently equipped to handle simp

Caroline Kopecz-Muller, Joshua D Mcgraw, Thomas Salez

When a hydrophilic and deformable porous material is immersed in a bath, it may absorb the solvent and expand by several times its volume, thus forming a highly soft and porous hydrogel. A stress applied on the soft hydrogel surface deforms it and forces the absorbed solvent to move by flowing through the network of pores. This coupled phenomenon sets the fr

Hangkong Wu, Yuze Zhu, Yajun Zhu, Kun Xu

The gas-kinetic scheme (GKS) provides high computational efficiency and accuracy for continuum flow simulations but is unable to reliably capture rarefaction effects. In contrast, although the discrete velocity method (DVM) is better suited for rarefied flows, it exhibits reduced accuracy and slow convergence when applied to continuum regimes. To overcome th

Yuxuan Han, Yuanxing Zhang, Yushuo Wang, Yichao Jin

Structured information extraction from long, multilingual scanned financial documents is a core requirement in industrial KYC and compliance workflows. These documents are typically non machine readable, noisy, and visually heterogeneous. They usually span dozens of pages while containing only sparse task relevant information. Although recent vision-language

Sebastián Gallardo, Hui-Yin Wu, Dorian Mazauric, Pierre Kornprobst

Understanding how diverse audiences engage with structured media is critical to ensure a consistent quality of experience. In this context, we quantify the behavioral and performance cost of manual navigation (e.g., pinch and zoom) versus direct structural access in layout-based digital documents. We specifically investigate newspaper reading when visual acc

Ryan Rae-Cheng Wee, Josef Bruzzese

We develop a geometric-phase framework for time-bin photonic qudits and propose a practical calibration and feed-forward algorithm for separating and compensating geometric (Pancharatnam-Berry), dynamical, and technical phase contributions. Working directly in the time-bin basis, we use a parallel-transport gauge so that geometric phases appear as experiment

Lingjie Zeng, Hailun Zhang, Xiwen Wang, Qijun Zhao

Temporal modeling remains a fundamental challenge in video understanding, particularly as sequence lengths scale. Traditional video models relying on dense spatiotemporal attention suffer from quadratic computational costs for long videos. To circumvent these costs, recent approaches adapt image models for videos via Parameter-Efficient Fine-Tuning (PEFT) me

Yash Ganpat Sawant

Stylistic personalization - making LLMs write in a specific individual's style, rather than merely adapting to task preferences - lacks evaluation grounded in authorship science. We show that grounding evaluation in authorship verification theory transforms what benchmarks can measure. Drawing on three measurement traditions - LUAR (a trained authorship

Jian Yang, Bohang Wang, Lina Wang, Jiacheng Chen

The optimization of front-end crude oil scheduling is a critical determinant of refinery profitability and operational stability. However, the coupling of discrete logistics events (e.g., vessel berthing) with continuous material flows (e.g., pipeline transfers) renders this problem an NP-hard Mixed-Integer Linear Programming (MILP) challenge, often intracta

Martin Boniol, Julien Brunel, Jean-Baptiste Chaudron, Christophe Garion

The Airborne Collision Avoidance System Xu (ACAS-Xu) relies on large certified Look-Up Tables (LUTs) that encode the exact decision logic used in operation. Neural-network-based approximations have been proposed to reduce memory requirements, but they inherently introduce approximation errors and complicate formal verification. This paper presents a symbolic

Jessica Crosse, Romina Gaburro

We address Calder\'on's problem of stably determining the anisotropic complex admittivity $\sigma$ in a domain $\Omega\subset\mathbb{R}^n$, with $n\geq3$, representing a conducting medium, in terms of a Dirichlet-to-Neumann map locally prescribed on a non-empty portion $\Sigma$ of the boundary of $\Omega$, $\partial\Omega$. $\sigma$ is assumed to be of type

Yasusada Murata, Ryo Nakajima

We identify a causal effect of top inventor inflows on the patent productivity of local inventors by combining the idea-generating process described by Marshall (1890) with the Bartik (1991) instruments involving the state taxes and commuting zone characteristics of the United States. We find that local productivity gains go beyond organizational boundaries

Akhil Rajeev P, Annarao Kulkarni

The digitisation of classical Sanskrit literature is impeded by a scarcity of annotated resources, particularly for Named Entity Recognition. While recent methodologies utilise generic Large Language Models (LLMs) for data augmentation, these approaches remain prone to error and often lack the reasoning depth required for classical grammar. In this work, we

Picchiotti Flavio, Thiago Alves Lima, Girard Antoine

In this paper we first study the fixed-time stabilizability of discrete-time switched linear control systems. Using a geometric approach, we derive conditions under which such systems can be stabilized within a prescribed number of steps, independently of the switching sequence. We address both the mode-dependent case, where the controller has access to the

Gongshu Wang, Zhirui Wang, Kan Yang

Monocular depth estimation (MDE) is a fundamental yet inherently ill-posed task. Recent vision foundation models (VFMs), particularly DINO-based transformers, have significantly improved accuracy and generalization for dense prediction. Prior works generally follow a unified paradigm: sampling a fixed set of intermediate transformer layers at uniform interva

Wasim Ahmad, Wei Zhang, Xuerui Mao

Audio-visual deepfakes have reached a level of realism that makes perceptual detection unreliable, threatening media integrity and biometric security. While multimodal detection has shown promise, most approaches are binary classification tasks that often latch onto dataset-specific artifacts rather than genuine generative traces. We argue that a detector in

Ofer Neiman, Alon Spector

Let $G=(V,E)$ be a weighted undirected graph, with $n$ vertices. A distance oracle is a data structure that can quickly answer distance queries, with some stretch factor. A seminal work of \cite{TZ01}, given an integer $k\ge 1$, provides such an oracle with stretch $2k-1$, query time $O(k)$, and size $O(k\cdot n^{1+1/k})$. Furthermore, this oracle can also r

Junfeng Cheng, Xiao-Song Yang

We establish a criterion for the existence of a topological horseshoe in a class of planar systems generated by periodic switching between two subsystems, each admitting a family of closed orbits, where the mechanism for chaos arises from the non-isochronicity of each subsystem. Exploiting the relationship between the period function of a Hamiltonian system

Jizhou Huang, Brendan Juba

We study three problems that involve identifying homogeneous halfspaces under Gaussian distributions: agnostic learning, one-sided reliable learning, and fairness auditing. In each of these problems, we are given labeled examples $(\mathbf{x}, \mathrm{y})$ drawn from an unknown distribution on $\mathbb{R}^d\times\{-1, +1\}$, whose marginal distribution on $\

Aleksander Tankman

We prove that any continuous function f from [0,1]^n to R representable by a finite computation tree with N internal nodes and compositional sparsity s = O(1) admits a deep Kolmogorov-Arnold Network (KAN) representation. Each internal node is realised by a primitive KAN block with controlled block depth and Lipschitz product. The layer-wise Lipschitz product

Gilberto Sussumu Hida, Danilo Monteiro Ribeiro, Erika Yahata

Context: Study screening in systematic literature reviews is costly, inconsistency-prone, and risk-asymmetric, since false negatives can compromise validity. Despite rapid uptake of Large Language Models (LLMs), there is limited evidence on how such models behave during the study screening phase, particularly regarding the choice of specific LLMs and their c

Maria Chiara Paolozzi, Annalisa D Arco, Ilaria Martinelli, Lorenzo Mosesso

Optical anisotropy in crystalline solids enables direction-dependent light-matter interactions and underpins a variety of advanced photonic functionalities. In this context, Vanadium dioxide (VO2) represents a prototypical material that undergoes a reversible MIT near 67{\deg}C, accompanied by pronounced electronic, structural, and optical modifications. The

Ziwei Ou

PSR J0437-4715 is a gamma-ray millisecond pulsar, which has been detected by Fermi-LAT. For understanding the nature, we analyze the GeV gamma-ray data obtained with Fermi-LAT around the pulsar region. Based on the pulsar timing ephemeris, we derived the gamma-ray pulse profile and defined on-pulse and off-pulse phase intervals. A binned likelihood analysis

Shaoliang Yang, Jun Wang, Yunsheng Wang

Large 3D SIMP studies require repeated elasticity solves for density-dependent operators whose finest matrices are expensive to assemble and whose conditioning degrades under high contrast. We study this linear-solver layer rather than claiming end-to-end optimization acceleration. The solver builds a matrix-free Galerkin geometric multigrid (GMG) hierarchy

Ivan Méndez-Cruz, Faisal Amlani

Motivated by existing blend-to-zero techniques, a formal framework is developed for defining and constructing blend-to-zero operators on closed intervals for the generation of sufficiently smooth transitions between functions. Such transitions are first formulated as a two-point Hermite-type interpolation that is not necessarily polynomial. It is shown that,

Marcelino Agundez, Jose Cernicharo

In recent years, the obsessive interest in the observation of TMC-1 has brought a boost in our knowledge of the chemistry of cold dark clouds. The number of molecules detected in this particular cloud has been more than doubled. Two observational programmes, GOTHAM and QUIJOTE, are responsible for this spectacular achievement. Here we provide an overall view

Aman Swaraj, Arnav Agarwal, Hitendra Singh Bhadouria, Sandeep Kumar

Purpose: Rapid and reliable diagnostic tools are crucial for managing respiratory diseases like COVID-19, where chest X-ray analysis coupled with artificial intelligence techniques has proven invaluable. However, most existing works on X-ray images have not considered lung segmentation, raising concerns about their reliability. Additionally, some have employ

Narimene Benarbia, Rabah Labbas, Tewfik Mahdjoub, Alexandre Thorel

In this work, we develop a new biological transmission model for Chagas disease. This model, set in two juxtaposed habitats with skew Brownian motion conditions at the interface, is composed of two reaction--diffusion equations and takes into account the sylvatic transmission. We write it as an abstract perturbed Cauchy problem using operator theory. Then, w

Garvit Kumar Mittal, Sahil Tomar, Sandeep Kumar

The rapid advancement of object detection architectures has positioned single stage detectors as the dominant solution for real-time visual perception. A primary source of computational overhead in these models lies in the deep backbone stages, where C2f bottleneck modules at high stride levels accumulate a disproportionate share of parameters due to quadrat

Yu-Ming Bai, Ming-Han Ding, Yu-Xuan Liu, Jun-Lin Li

We propose Geometric-Configuration Modulation (GM), a novel AO-free FSO paradigm utilizing multi-source geometric configuration encoding and active correlative decoding. GM demonstrates exceptional resistance to strong atmospheric turbulence ($D/r_{0}\sim 5$) over a 1.2 m link in preliminary experiments.

Alexander D. Kolesnik

We consider the symmetric Markov random flight $\bold X(t), \; t>0,$ in the Euclidean space $\Bbb R^m, \; m\ge 3$, performed by a particle that moves in $\Bbb R^m$ with constant finite speed and changes its directions at Poisson-distributed random time instants by choosing the initial and each new direction at random according to the uniform distribution on

Yan-Hong Qin, Jin-Peng Yang, Li-Chen Zhao

We investigate topological vector potentials underlying the phases of nonlinear waves by performing Dirac's magnetic monopole theory in an extended complex plane, taking into account self-steepening effects while ignoring the usual cubic nonlinearities. We uncover that the simple poles and third-order poles of the density function constitute virtual monopole

Ejaz Ahmed, Boshuai Ye, Syed Hamza Shah, Muhammad Azeem Akbar

Ensuring the integrity of quantum circuits is a significant challenge in the Noisy Intermediate-Scale Quantum (NISQ) era, where circuits are subject to compilation transformations, hardware constraints, and potential adversarial modifications. Existing validation approaches typically rely on either structural analysis or behavioral evaluation, leading to inc

Nico Yannik Merkt

This master's thesis investigates the thermal and photochemical dehydrogenation of ethylbenzene (EB) to styrene on the rutile TiO$_{2}$(110) surface. A dual-methodological quantum chemical approach is used for this investigation. While industrial styrene production is energy-intensive, photocatalysis on semiconductor materials offers a promising alternative

Yibiao Wei, Jie Zou, Pengfei Zhang, Xiao Ao

Generative recommendation frameworks typically represent items as discrete Semantic IDs (SIDs). While existing studies have sought to enhance SID construction by incorporating multimodal content, collaborative signals, or more advanced quantization techniques, learning high-quality SIDs still faces two key challenges: (1) The two-stage generative recommendat

Tong Hu, Zitao Lin, Sharon X. Wang, Mu-Tian Wang

TOI-4600b and c, originally identified by the Transiting Exoplanet Survey Satellite (TESS) and reported by I. Mireles et al. (2023), are a rare pair of transiting long-period giant planets ($\rm P_b=82.7$ days, $\rm P_c=482.8$ days) orbiting an early K dwarf. In this work, we refine the orbital parameters of the TOI-4600 system by combining new TESS photomet

Jie Liu

We prove that a non-projective compact K\"ahler contact manifold is of the form $\mathbb{P} T_Y$, where $Y$ is a compact K\"ahler manifold.

Lorenzo Zapparoli, Paul Fäth, Blazhe Gjorgiev, Giovanni Sansavini

As the penetration of distributed energy resources (DERs) increases, harnessing their flexibility becomes critical for power system operations. Virtual power plants (VPPs) offer a promising solution. However, most existing scheduling tools rely on simplified DER or grid models and largely overlook local flexibility procurement mechanisms such as dynamic netw

J. A. Montanez-Barrera, Kristel Michielsen

Recent advances in quantum computing have enabled the development of quantum processors with hundreds of qubits. However, noise continues to limit the amount of useful information that can be extracted from these systems, making it essential to identify the regime in which experimental outputs remain reliable. In this work, we benchmark Quantinuum Helios-1,

Yongliang Ding, Qigong Bi, Peng Pu

Accurate end-to-end tail-latency forecasting is critical for proactive SLO management in microservice systems. However, modeling long-range dependency propagation and non-stationary, bursty workloads while maintaining inference efficiency at scale remains challenging. We present STLGT (Scalable Trace-based Linear Graph Transformer), a per-API predictor that

Chandramouli Chowdhury, Song He, Yong-Xiang Su, Dongyu Yang

Motivated by recent evidence that equal-time correlators can be simpler than the corresponding wavefunction coefficients, we study de Sitter correlators in conformally coupled $\phi^3$ theory directly. By inverting the momentum-space dressing rules, we derive a time integral representation for generic graphs and show that its natural building blocks are flat

Zepeng Wang, Juan Peypouquet

We analyze the convergence rate of an accelerated backward forward method for solving convex composite optimization problems. The method was developed by Taylor, Hendrickx and Glineur, and is different from the FISTA algorithm in its placement of the proximal operator. When the smooth part of the objective function is convex, we establish a fast convergence

Junru Song, Yimeng Hu, Yijing Chen, Huining Li

Large Vision-Language Models (VLMs) have achieved remarkable multimodal performance yet remain prone to factual hallucinations, particularly in long-tail or specialized domains. Moreover, current models exhibit a weak capacity to refuse queries that exceed their parametric knowledge. In this paper, we propose a systematic framework to enhance the refusal cap

Yasuyuki Hatsuda, Tadashi Okazaki

We study supersymmetric quarter-indices for corner configurations in 4d $\mathcal{N}=4$ super Yang-Mills theory with orthogonal and symplectic gauge groups. For the basic Y-junctions, we obtain exact closed-form expressions for the indices by making use of the Gustafson type integral formula and the Higgsing method. We demonstrate the equality of the quarter

Shuhao Xu, Yifan Hu, Jingjing Wu, Zhihao Du

Emotion perception and adaptive expression are fundamental capabilities in human-agent interaction. While recent advances in speech emotion captioning (SEC) have improved fine-grained emotional modeling, existing systems remain limited to static, single-emotion characterization within isolated sentences, neglecting dynamic emotional transitions at the discou

Falk Dettinger, Matthias Weiß, Baran Can Gül, Sruthi Mangala Suresh

Software Defined Vehicles face an increasing computational gap as advanced algorithms and frequent software updates demand more processing power while onboard hardware remains static throughout a vehicle's 10+ year lifespan. This mismatch threatens the performance of safety-critical functions including advanced driver-assistance systems and real-time percept

Feihu Liu

Given a numerical semigroup $S$ and a positive integer $p$, the quotient $\frac{S}{p}=\{x\in \mathbb{N} \mid px\in S\}$ also forms a numerical semigroup. In this paper, we first characterize the Ap\'ery set for a class of quotients of numerical semigroups. Under certain conditions, we then derive half-closed form formulas for their Frobenius number and genus

Samitha Gunarathne, Eslam Eldeeb, Nurul Huda Mahmood, Italo Atzeni

Interference alignment (IA) is a widely recognized approach for mitigating inter-cell interference in multi-user multiple-input multiple-output (MIMO) networks. Despite its effectiveness, practical deployment remains constrained by two major challenges, i.e., the need for global channel state information (CSI) at each transmitter and the complexity of derivi

Sahil Tomar, Sandeep Kumar

This paper presents Quantum Gatekeeper, a context-bound image steganography framework where successful payload recovery depends on both cryptographic decryption and the reconstruction of a precise extraction path. The system integrates lossless least significant bit (LSB) embedding with a deterministic variational quantum circuit (VQC)-derived gate key, mult

Tianyu Liu, Yuhao Shen, Xinyi Hu, Baolin Zhang

Speculative decoding accelerates LLM inference, but SOTA hidden-state-based drafters suffer from long-range decay: draft accuracy degrades as the speculative step increases. Existing work attributes this decay to train-inference mismatch and proposes test-time training (TTT) as a remedy, yet we observe that long-range decay persists even in TTT-trained draft

Mathieu Dario, Florent Chenevier, Kévin Delmas, Joris Guerin

Runtime monitoring is essential to ensure the safety of ML applications in safety-critical domains. However, current research is fragmented, with independent methods emerging from different communities. In this paper, we propose a unified framework categorising runtime monitoring approaches into three distinct types: Operational Design Domain (ODD) monitorin

Ahyoung Oh, Wonseok Shin, Songkuk Kim

Sparse Autoencoders (SAEs) have demonstrated significant success in interpreting Large Language Models (LLMs) by decomposing dense representations into sparse, semantic components. However, their potential for analyzing Vision Transformers (ViTs) remains largely under-explored. In this work, we present the first application of SAEs to the ViT [CLS] token for

Talha Rahman, Murat Uysal

Terahertz (THz) communication has emerged as a key enabler for sixth-generation (6G) networks, offering ultrawide bandwidths to support data-intensive applications such as holographic telepresence and immersive extended reality. Recent advances have enabled both electronics-based and photonics-based THz front-ends, each with distinct advantages and hardware

Dilip Kr. Maity, Sandip Dighe, Nilamani Sahoo, Tadd Truscott

Capillary interfaces subjected to impulsive forcing arise in many natural and technological systems, yet the pathway by which rapid substrate motion is converted into droplet detachment remains unclear. Here we study this process in a controlled setting: a liquid droplet resting on a taut wire that is plucked and suddenly released. The resulting transverse w

Pietro Colangelo, Fulvia De Fazio, Carlo la Torre, Giuseppe Roselli

The semileptonic decays of $B_q$ mesons ($q=u,d,s$) to $J^P=2^+$ charmed mesons are investigated. The form factors parametrising the hadronic matrix elements of the weak vector and axial-vector quark currents are evaluated using light-cone QCD sum rules with external $B_q$ state, including the 3-particle contributions. The form factors of pseudoscalar and te

Narahari N. Moudhgalya

This work presents the design and analysis of a sixth-order triple-coupled transformer-based tank, enabling third-harmonic expansion for mmWave VCOs. Unlike conventional fourth-order tanks, the proposed tank inherently supports three resonance modes, enabling wideband third-harmonic expansion without additional low-Q switched-capacitor tuning elements. In co

Hari Prasanth S. M., Nilusha Jayawickrama, Risto Ojala

Industrial object detection systems typically rely on large annotated datasets, which are expensive to collect and challenging to maintain in industrial scenarios where the inventory of objects changes frequently. This work addresses the challenge of few-shot object detection in such industrial scenarios, where only a limited number of labeled samples are av

Fei Xie, Nan Lu, Yajuan Sun

In this paper, we propose a quadratic reformulation theory for rational-like functions. Based on this theory, we develop the Quadratic Conservation Elevation (QCE) method, which combines the Scalar Auxiliary Variable (SAV) method with the implicit midpoint rule. We apply this approach to the Cahn-Hilliard (CH) equation with rational-like free-energy terms, o

R. G. Bullis, W. L. Tavis, M. R. Weiss, J. Orellana Cisneros

We present absolute frequency measurements of 2S_{1/2}-nS_{1/2} two-photon transitions with n = 8, 9, and 10 in a cryogenic beam of atomic hydrogen. Each transition has been measured with a fractional uncertainty of approximately 2.6*10^(-12). Combining the results from this work and the 1S_{1/2}-2S_{1/2} transition frequency, we extract a root-mean-square p

Shi-Qi Liu, Kai Li, Xiao-Dian Chen, Li-Heng Wang

Eclipsing binaries are crucial astrophysical laboratories for studying stellar parameters and evolutionary processes. In this study, we constructed a machine-learning-based model for systematic phenomenological classification of eclipsing binaries. We first extracted eclipsing binaries from the ASAS-SN variable star catalog and cross-matched them with TESS t

Charul Rajput, B. Sundar Rajan, Ragnar Freij-Hollanti, Camilla Hollanti

Function-correcting codes with data protection simultaneously protect both the data and a function of the data at distinct error-correction levels. When the function receives strictly stronger protection than the data, such a code is called a strict function-correcting code with data protection. While prior work showed that perfect and MDS codes cannot serve

Zhaorui Dong, Fang Han, Jianfeng Yao

We study random matrices whose entries are obtained by applying consistent rank correlations, such as Hoeffding's $D$, pairwise to a high-dimensional random vector with mutually independent components. Prior work has shown that, in the proportional high-dimensional regime, the empirical spectral distributions of large Kendall's tau and Spearman's rho matrice

C. X. Liu, T. F. Feng, J. M. Dong

Millisecond magnetars are widely suggested as the central engines powering hydrogen-poor superluminous supernovae (SLSNe). These magnetars primarily lose huge rotational energy through gravitational wave radiation (GWR) and magnetic dipole radiation (MDR), with MDR serving as an energy source for SLSNe. We study the evolution of the magnetar spin, magnetic i

Yair Meidan, Omri Haller, Yulia Moshan, Shahaf David

Recent advances in large language models and agentic frameworks have enabled virtual customer assistants (VCAs) for complex support. We present SecMate, a multi-agent VCA for cybersecurity troubleshooting that integrates device, user, and service specificity from conversational and device-level signals. Device specificity is provided by a lightweight local d

Yiheng Liu, Xinyu Li

Ultra-faint dwarf galaxies serve as powerful testing grounds for wave dark matter models through dynamical stellar heating. Previous simulation-based work derived a lower bound on the fuzzy dark matter particle mass using a diffusion approximation valid only when the de Broglie wavelength is much smaller than the galaxy's half-light radius. We simulate the d

Akhil Kumar Awasthi, Mrinmoy Samanta, Sudipta Mondal, Ayan Patra

Imaginarity, stemming from the complex structure of quantum mechanics, has recently emerged as a fundamental resource, yet its dynamical generation remains largely unexplored. In this work, we introduce the notion of imaginarity-generating power (IGP) of unitary dynamics, which quantifies the ability of unitary operations to produce imaginarity from initiall

Zhou Li, Xiang Zhang, Jiguang He, Giuseppe Caire

We study the fundamental limits of multi-server secure aggregation over a two-hop network where multiple servers, each connected to a disjoint subset of users, jointly compute the sum of all users' inputs. The goal is to ensure that no server can infer any information about prescribed subsets of inputs beyond the desired aggregate, even when colluding with a

Peter Müllner, Dominik Kowald, Markus Schedl, Elisabeth Lex

Balancing differential privacy (DP) with recommendation accuracy is a key challenge in privacy-preserving recommender systems, since DP-noise degrades accuracy. We address this trade-off at both the data and model levels. At the data level, we apply DP only to the most stereotypical user data likely to reveal sensitive attributes, such as gender or age, to r

Yimeng Shan, Zhaorui Zhang, Sheng Di, Yu Liu

Federated Split Learning has been identified as an efficient approach to address the computational resource constraints of clients in classical federated learning, while guaranteeing data privacy for distributed model training across data owners. However, it faces some critical challenges when such a training strategy meets large language models (LLMs) for f

Hengfeng Liu, Chunming Tang, Cuiling Fan, Zhengchun Zhou

The Gram matrix is a classical object formed from the pairwise inner products of a collection of vectors, with fundamental roles in functional analysis, statistics, combinatorics, and coding theory. In the realm of sequence design, maximum-length sequences (m-sequences) are among the most fundamental classes of sequences, traditionally characterized by their

Hongzhang Chen, Jianxi Li, Yongtao Li

Brualdi and Hoffman proposed a well-known problem of determining the graph with maximum adjacency spectral radius among all graphs with given size $m$. Early work by Friedland and Stanley addressed some specific cases. This problem was later completely solved by Rowlinson and recently revisited by Cheng and Weng. Pioneering work on the distance matrix was ca

Om Parkash, Jannik Bauer, Vincent Schmitt, Thomas Greiner

Increasing complexity of modern enterprise systems and the demand for automation and interoperability require consistent and semantically validated models in Model-Based Systems Engineering (MBSE). The Object Constraint Language (OCL) supports formal definition of such constraint validations. However, MBSE models and OCL constraints are typically managed in

Saurabh K. Singh, Sachin Raj

Most enterprise document AI today is a pipeline. Parse, index, retrieve, generate. Each of those stages has been studied to death on its own -- what's still hard is evaluating the system as a whole. We built EnterpriseDocBench to take a swing at it: parsing fidelity, indexing efficiency, retrieval relevance, and generation groundedness, all on the same corpu

Dechao Li, Yutao Yao, Jingyao Duan

The transitivity of fuzzy relations plays an important role in fuzzy set theory, artificial intelligence, clustering and decision-making. However, it is often difficult for fuzzy relations to satisfy the transitivity property in many practical applications. This has motivated researchers to investigate the degree to which a fuzzy relation is transitive. Ther

Alessandro Barone, Ahmed Elgaziari, Shoji Hashimoto, Zhi Hu

We discuss the calculation of the inclusive semileptonic decay for the process $B_s \to X_c \, l \nu_l$ using lattice QCD. This calculation could be decisive in understanding the long-standing tension between inclusive and exclusive determinations of the CKM matrix element, $|V_{cb}|$. In this talk, we investigate the main sources of systematic uncertainty i

Tong Lu, Ke Xu, Zimo Zhang, Zitong Zhao

Reliable seizure detection in mouse models is essential for preclinical epilepsy research, yet manual review of synchronized video-EEG recordings is labor-intensive and single-modality systems fail for complementary reasons: video-based methods are easily confounded by benign behaviors, whereas EEG-based methods are vulnerable to ictal motion artifacts. We p

Zhe Ding, Su Pan, Duowei Pan

Post-training quantization (PTQ) has become an important technique for reducing the inference cost of Large Language Models (LLMs). While recent mixed-precision methods improve ultra-low bit quantization by preserving critical subspaces in high precision, they typically construct these subspaces relying solely on activation statistics. This ignores the funda

Dan Gluck, Yotam Mimran, Andrey Karenskih, Talya Vaknin

Solving large, sparse linear systems is a fundamental workload in scientific computing and engineering simulations, often dominating runtime and energy consumption in high-performance computing (HPC) applications. In this work, we explore an alternative computing paradigm based on analog optical processing, implemented through the Laser Processing Unit (LPU)

Caroline E. P. Robin, Martin J. Savage

Advances in quantum information science (QIS) are providing transformative insights into the complexity of quantum many-body systems, potentially defining new frontiers in nuclear and high-energy physics. This review explores how QIS-derived techniques are fostering new analytic frameworks and algorithms - both classical and quantum - to tackle (some of the)

Gabriel Stefan, Sergiu Nisioi

We describe our system for SemEval-2026 Task 6 (CLARITY: Unmasking Political Question Evasions), which classifies English political interview responses by coarse-grained clarity (3-way) and fine-grained evasion strategy (9-way). Since responses frequently exceed the 512-token limit of standard Transformer encoders, we apply an overlapping sliding-window chun

Karthik Soma, Mohamed S. Talamali, Genki Miyauchi, Giovanni Beltrame

In multi-agent systems, should limited resources be concentrated into a few capable agents or distributed among many simpler ones? This work formulates the split over $n$ resource sharing problem where a group of $n$ agents equally shares a common resource (e.g., monetary budget, computational resources, physical size). We present a case study in multi-agent

Guo Xuan Chan, Wangwei Lan, Tenghui Wang, Xizheng Ma

Fluxonium qubits combine long coherence times with strong anharmonicity, making them a promising platform for scalable superconducting quantum processors. Recent experiments have demonstrated high-fidelity operations in multi-qubit processors while suppressing stray qubit interactions using fluxonium-transmon-fluxonium (FTF) architectures. However, scaling s

Tushar K. Ghosh, Elvar Ö. Jónsson, Stephan Steinhauer, Panagiotis Grammatikopoulos

Polaron-mediated charge transport in α-Fe2O3 plays a central role in its performance as a gas-sensing material, yet the atomistic interaction between surface adsorbates and polarons remains insufficiently understood. Here, density functional theory with Hubbard-U correction (DFT+U) combined with nudged elastic band calculations is used to investigate polaron