April 2026 arXiv papers — page 72

Davor Dragicevic, Yeor Hafouta

We prove quenched and annealed statistical stability, linear response, and differentiability of asymptotic moments for parametric families of partially hyperbolic skew products, with random hyperbolic maps on the fibers. The main novelty is that the base maps also depend on the parameter, which leads to different formulas in the linear response and the deriv

Deevashwer Rathee, Jean-Luc Watson, Zirui Neil Zhao, G. Edward Suh

Approximate nearest neighbor (ANN) search in AI systems increasingly handles sensitive data on third-party infrastructure. Trusted execution environments (TEEs) offer protection, but cost-efficient deployments must rely on external SSDs, which leaks user queries through disk access patterns to the host. Oblivious RAM (ORAM) can hide these access patterns but

Ling Li

Let $\tau(n)$ denote the classical divisor function. In this paper, we consider the hyperbolic fractional sum of the divisor function defined by $$ T(x) = \sum_{n_1 n_2 \leqslant x} \tau\left( \left[ \frac{x}{n_1 n_2} \right] \right) = \sum_{n \leqslant x} \tau\left( \left[ \frac{x}{n} \right] \right) \tau(n), $$ where $[t]$ denotes the integral part of the

Xiaorong Zou, Hyeon Suk Shin, Chang-Jong Kang, Baibiao Huang

The discovery of higher-order topological insulator (HOTI) has established a new paradigm for understanding symmetry-constrained boundary electronic states. Here, based on first-principles calculations, we demonstrate the emergence of HOTI phase in organic lattices of two-dimensional azulenoid-kekulene-type carbon allotropes, namely AKC-[3,3] and AKC-[6,0].

Juyong Jiang, Chenglin Cai, Chansung Park, Jiasi Shen

While Large Language Models (LLMs) excel at function-level code generation, project-level tasks such as generating functional and visually aesthetic multi-page websites remain highly challenging. Existing works are often limited to single-page static websites, while agentic frameworks typically rely on multi-turn execution with proprietary models, leading to

Hefei Wang, Jianwei Liu, Yinghui He, Guanding Yu

In recent years, WiFi sensing has been recognized as a promising technology to bring respiratory monitoring into everyday homes, thanks to its contactless nature and ubiquitous availability. However, existing WiFi-based respiratory monitoring systems still fall short of deployment-oriented performance: they suffer from restrained hardware scalability, limite

Haoyu Zhang, Jingyi Zhou, Peng Ye, Jiakang Yuan

With the development of deep learning, ViT-based stereo matching methods have made significant progress due to their remarkable robustness and zero-shot ability. However, due to the limitations of ViTs in handling resolution sensitivity and their relative neglect of local information, the ability of ViT-based methods to predict details and handle arbitrary-r

Nedyalko Prisadnikov, Danda Pani Paudel, Yuqian Fu, Luc Van Gool

Vision Transformers (ViTs) dominate self-supervised learning (SSL). While they have proven highly effective for large-scale pretraining, they are computationally inefficient and scale poorly with image size. Consequently, foundational models like DINO are constrained to low-resolution processing. A recent foveal-inspired transformer achieves resolution agnos

Chao Pan, Yu Wu, Xin Yao

Internal Safety Collapse (ISC) is a failure mode in which frontier LLMs, when executing legitimate professional tasks whose correct completion structurally requires harmful content, spontaneously generate that content with safety failure rates exceeding 95%. Existing input-level defenses achieve a 100% failure rate against ISC, and standard system prompt def

Francis Brown

Using results of Fayers on the structure of Specht modules, we prove two different formulae for the determinant of matrices which are obtained by amalgamating the entries of two smaller matrices. In particular, this gives formulae for multivariable Vandermonde determinants as a sum of completely factorising terms, each of which is a Vandermonde determinant i

Gustav Keppler, Ghada Elbez, Veit Hagenmeyer

The rapid evolution and use of Large Language Models (LLMs) in professional workflows require an evaluation of their domain-specific knowledge against industry standards. We introduceCyberCertBench, a new suite of Multiple Choice Question Answering (MCQA) benchmarks derived from industry recognized certifications. CyberCertBench evaluates LLM domain knowledg

Guojie Hu, Qingqing Wu, Lipeng Zhu, Wen Chen

The movable antenna (MA) technology enables flexible reconfiguration of wireless channels through adaptive antenna deployment, offering significant potential for enhancing communication performance. However, antenna movement requires a certain duration within which communication may be compromised due to factors such as channel fluctuation and Doppler effect

I. V. Voronchikhin, D. V. Kirpichnikov

In this work, we investigate the projected sensitivity of the Beam-Dump eXperiment at the International Linear Collider (ILC-BDX) to inelastic fermionic dark matter coupled to the Standard Model photon through an off-diagonal magnetic dipole operator. We compute the production rate of dark matter states in the bremsstrahlung like process $e^- N \to e^- N γ^*

Isabel Nha Minh Le, Roeland Wiersema, Christian B. Mendl

Optimizing tensor networks with standard first-order methods often leads to slow convergence and entrapment in local minima. Although second-order optimization offers enhanced robustness, explicitly constructing the full Hessian matrix is computationally prohibitive for large-scale systems. In this work, we bypass this bottleneck by introducing an analytical

Gang Li

This is a continuation of the research in [16]. Let $(\overline{M},g_{-1})$ be a closed geodesic $r_0$-ball in the hyperbolic space $(\mathbb{H}^n,g_{-1})$. Let $m\neq1$ be a positive constant. In this paper, we show that for $n\geq3$, starting from the metric $m g_{-1}$ on $\overline{M}$, with certain prescribed non-decreasing rotationally symmetric mean cu

Aishik Mandal, Hiba Arnaout, Clarissa W. Ong, Juliet Bockhorst

Rising demand for mental health support has increased interest in using Large Language Models (LLMs) for counseling, but adapting them to this safety-critical domain is hindered by limited real-world data due to privacy constraints. Synthetic datasets provide a promising alternative, but existing approaches often rely on unstructured or semi-structured text

Behrad Koohy, Jamie Bayne

Quality-Diversity (QD) algorithms excel at discovering diverse repertoires of skills, but are hindered by poor sample efficiency and often require tens of millions of environment steps to solve complex locomotion tasks. Recent advances in Reinforcement Learning (RL) have shown that high Update-to-Data (UTD) ratios accelerate Actor-Critic learning. While effe

Youngmok Park, Bumsu Park, Namyoon Lee

In frequency division duplex massive multiple-input multiple-output systems, downlink channel state information must be fed back within a limited uplink budget. While transform coding with Karhunen-Loeve transform and reverse water-filling is rate-distortion optimal for Gaussian channels, its performance is limited by basis mismatch between the user and base

Kartik N. Iyer, Parag H. Rughani

Memory analysis is a crucial technique in digital forensics that enables investigators to examine the runtime state of a system through physical memory dumps. While significant advances have been made in memory forensics, the detection and analysis of Thread Local Storage (TLS) callbacks remain challenging due to their dual nature as both legitimate Windows

Yi-Xiao Tao

In this letter, we focus on the application of the off-shell recursion method proposed in \cite{Tao:2025fch} in the Yang-Mills planar loop integrands, which starts with solving the classical equation of motion via the perturbiner method. Following the recursion steps, we point out that the pure gluon sector of the planar loop integrands can be written in mat

David Barral, Aitor Brazaola-Vicario, Diego Cifrián, Natalia Costas

QKD technology is being increasingly adopted inside the network core for protecting information transport against any form of computational attacks. However, the use of QKD for wide-area internetworking is still challenging and costly, due to its strong trust assumptions and the low achievable key rates in long QKD links. This paper presents a standards-driv

Gang Li

In this paper, we show that starting from a geodesic ball $\overline{B_{r_0}}(0)$ in $\mathbb{H}^n$, for $n\geq3$, with prescribed non-decreasing rotationally symmetric mean curvature and the fixed conformal class $[g_{\mathbb{S}^{n-1}}]$ on the boundary, the solution $g(t)$ to the normalized Ricci flow $(1.2)$ which is continuous up to the boundary, exists

Huaiyu Jia, Jiehshun You, Yizhi Luo, Jingyu Liu

Automated Market Makers (AMMs), as a core infrastructure of decentralized finance (DeFi), uniquely drive on-chain asset pricing through a deterministic reserve ratio mechanism. Unlike traditional markets, AMM price dynamics is triggered largely by on-chain events (e.g., swap) that change the reserve ratio, rather than by continuous responses to off-chain inf

Rodrigo Carmo Terin

We extend our gauge-covariant stochastic neural-field framework by promoting architecture-level parameters to slow stochastic variables evolving in function space. Our effective theory is formulated in terms of classical commuting fields and provides symmetry-constrained diagnostics of marginality and finite-width effects through the maximal Lyapunov exponen

Ramdhan Wibawa, Birendra Jha

We report the first systematic evidence of hallucination in AI models of fluid dynamics, demonstrated in the canonical problem of hydrodynamically unstable transport known as viscous fingering. AI-based modeling of flow with instabilities remains challenging because rapidly evolving, multiscale fingering patterns are difficult to resolve accurately. We ident

Chao Pan, Xin Yao

Fast Adversarial Training (FastAT) seeks to achieve adversarial robustness at a fraction of the computational cost incurred by standard multi-step methods such as PGD-AT. Although numerous FastAT techniques have been proposed in recent years, fair comparison among them remains elusive. Existing benchmarks and public leaderboards typically permit diverse mode

R. Grimaudo, A. S. M. De Castro, G. Falci, A. Messina

A two-qutrit extension of the quantum Rabi model is studied. Despite its increased complexity, the model results to be integrable under specific, physically relevant conditions. This feature allows for the emergence of analytically tractable subdynamics. In this framework, the ground-state phase diagram can be derived, and the analysis reveals critical pheno

Ruihan Zhou, Zishi Zhang, Jinhui Han, Yijie Peng

Forecasting the life-cycle trajectory of a newly launched product is important for launch planning, resource allocation, and early risk assessment. This task is especially difficult in the pre-launch and early post-launch phases, when product-specific outcome history is limited or unavailable, creating a cold-start problem. In these phases, firms must make d

Eray Unsal Atay, Venkat Chandrasekaran, Victoria Kostina

We study the rate-cost tradeoff in rate-limited control of general stochastic control systems, including nonlinear systems, over a finite horizon. At each time step, an encoder observes the state and transmits a description to a controller, which then selects the control action. For an average control-cost threshold $D$, we characterize the minimum achievabl

Zuo Chen, Jiancheng Guan, Dongmei Li

This paper investigates the equivalence reduction for several classes of multivariate polynomial matrices and their Smith forms, establishing some criteria for such reduction. In particular, we employ algebra isomorphisms as a key tool to study this equivalence problem. We then leverage the Quillen-Suslin and Lin-Bose theorems to extend these results to non-

Zhe Feng, Sen Lian, Changwei Wang, Muyang Zhang

The quadratic complexity of softmax attention presents a major obstacle for scaling Transformers to high-resolution vision tasks. Existing linear attention variants often replace the softmax with Gaussian kernels to reduce complexity, but such approximations lack theoretical grounding and tend to oversuppress mid-range token interactions. We propose Laplacia

Zhengchao Ji, Yong Luo

In this paper, we establish Brezin-Li-Yau type lower bounds for averaged sums of Dirichlet eigenvalues of the Laplacian and poly-Laplacian on bounded domains in Euclidean spaces. By deriving expansions of two binary polynomials which may be of independent interest, we improve several existing lower bounds of this kind in the literature. Furthermore, our lowe

Xingyu Zhu, Junfeng Fang, Shuo Wang, Beier Zhu

Large Vision-Language Models (LVLMs) exhibit powerful generative capabilities but frequently produce hallucinations that compromise output reliability. Fine-tuning on annotated data devoid of hallucinations offers the most direct solution, while its high computational cost motivates recent representation-based methods, which focus on mitigating hallucinatory

Kevin Godin-Dubois, Anil Yaman, Anna V. Kononova

While Central Pattern Generators (CPGs) and Multi-Layer Perceptrons (MLP) are widely used paradigms in robot control, few systematic studies have been performed on the relative merits of large parameter spaces in highly constrained settings. As opposed to traditional Machine Learning contexts, our input and output spaces are small and performance is bounded

Guojie Hu, Qingqing Wu, Lipeng Zhu, Kui Xu

Through adaptive antenna repositioning, the movable antenna (MA) technology enables on-demand reconfiguration of wireless channels, thereby creating an additional spatial degree of freedom in improving communication performance. This paper investigates a multiuser uplink communication system aided by MAs, where a base station (BS) equipped with multiple MAs

Roberto Grimaudo, Sagnik Chakraborty, Rosario Lo Franco, Giuseppe Falci

The present work focuses on the strong/weak interaction of many-body spin-systems with a cavity mode. It introduces the necessity of redefining the physical conditions determining the strong/weak coupling regime in those systems. In more complex systems, the effective coupling emerging from the collective dynamics may differ indeed from the actual coupling o

Zhiqiu Lin, Chancharik Mitra, Siyuan Cen, Isaac Li

Video-language models (VLMs) learn to reason about the dynamic visual world through natural language. We introduce a suite of open datasets, benchmarks, and recipes for scalable oversight that enable precise video captioning. First, we define a structured specification for describing subjects, scenes, motion, spatial, and camera dynamics, grounded by hundred

Jie Gu

We derive spectral fluctuation--dissipation--response inequalities for finite-state Markov jump processes. By comparing the causal susceptibility to its passive equilibrium reference, we establish frequency-resolved and frequency-integrated inequalities that bound their mismatch in terms of the steady-state entropy production rate, probe variance, short-time

Rong Quan, Yantao Lai, Dong Liang, Jie Qin

Object Referring-guided Scanpath Prediction (ORSP) aims to predict the human attention scanpath when they search for a specific target object in a visual scene according to a linguistic description describing the object. Multimodal information fusion is a key point of ORSP. Therefore, we propose a novel model, ScanVLA, to first exploit a Vision-Language Mode

Harshit Bajpai, Ankik Kumar Giri, Tim Jahn, Abhinav Jha

Solving inverse problems requires appropriate regularization techniques to ensure well-posedness and stability. In recent years, denoiser-driven methods have emerged as effective regularization strategies, achieving state-of-the-art performance in various imaging applications. However, their stability and convergence within iterative regularization framework

Sergio Albeverio, Suji Kawasaki, Yumi Yahagi, Minoru W. Yoshida

This paper introduces partial results, in the current situation, of ongoing considerations corresponding to the above title. A construction on exact relativistic quantum field model with the space time dimension $d \in {\mathbb N}$, including the case where $d \geq 4$, is going to be discussed. Firstly, Hermitian scalar quantum fields $<{\cal H}, U, \psi, D>

Zixu Li, Yupeng Hu, Zhiwei Chen, Mingyu Zhang

The Composed Image Retrieval (CIR) task provides a flexible retrieval paradigm via a reference image and modification text, but it heavily relies on expensive and error-prone triplet annotations. This paper systematically investigates the Noisy Triplet Correspondence (NTC) problem introduced by annotations. We find that NTC noise, particularly ``hard noise''

Kuanwei Chen, Tingyi Lin

Sign-language datasets are difficult to preprocess consistently because they vary in annotation schema, clip timing, signer framing, and privacy constraints. Existing work usually reports downstream models, while the preprocessing pipeline that converts raw video into training-ready pose or video artifacts remains fragmented, backend-specific, and weakly doc

Yu Cao, Xukun Feng, Yiming Guo, Huiying Liu

Third-order nonlinear Hall effects (THE) have recently attracted considerable experimental interest as powerful probes for quantum geometric properties in emergent quantum materials, encompassing quadrupole moments of quantum metric and Berry curvature. Here, we report a fundamentally new THE in room-temperature van der Waals ferromagnet Fe3GaTe2 from second

Luka Benić, Dino Novko, Ivor Lončarić

The exact microscopic origin, symmetry, and thermal melting mechanism of the charge density wave (CDW) phase in TiSe$_{2}$ remain a subject of intense debate, particularly regarding the presence of chiral structural order and a multi-step phase transition. Here, we resolve the finite-temperature structural dynamics of the monolayer TiSe$_{2}$ using large-sca

Federico Betti, Lorenzo Baraldi, Lorenzo Baraldi, Rita Cucchiara

Text-to-Image generation has seen significant advancements in output realism with the advent of diffusion models. However, diffusion models encounter difficulties when tasked with generating multiple objects, frequently resulting in hallucinations where certain entities are omitted. While existing solutions typically focus on optimizing latent representation

George Brumpton, Aiman Khan, Helia Hooshmand, Samanta Piano

We show that the construction of the linear interferometer in the Supplemental Material of arXiv:1909.09581 is flawed, leading to a generally suboptimal solution. We then provide the correct derivation of the optimal interferometric configuration that achieves the quantum Fisher information limit for imaging N weak incoherent emitters.

Evgeny Staritsin

Spin-up of a mass gaining component in a binary system is considered taking into account the mass loss from the system during the mass transfer between components in the Hertzsprung gap. The angular momentum that the accreting component gains during mass transfer depends on the increase in the mass of the component at this stage. The increase in the mass was

Gui Wang, Zehao Zhong, YongSong Zhou, Yudong Li

Despite significant progress in Multi-modal Large Language Models (MLLMs), their clinical reasoning capacity for multi-modal diagnosis remains largely unexamined. Current benchmarks, mostly single-modality data, can't evaluate progressive reasoning and cross-modal integration essential for clinical practice. We introduce the Cross-Modality Progressive Clinic

Muhammad Ammad, Albrecht Michler, Paul Schwarzbach, Jonas Ninnemann

This article introduces the HYMN (HYbrid Multi-technology Navigation) dataset: a multi-system, and time synchronized dataset for localization research based on opportunistic signals collected in an indoor-outdoor scenario. HYMN comprises measurement data collected in an industrial hall setting for five different positioning systems including Ultra-Wideband (

Yuelin Zhang, Qingpeng Ding, Longxiang Tang, Chengyu Fang

Ultrasound (US)-guided needle insertion is a critical yet challenging procedure due to dynamic imaging conditions and difficulties in needle visualization. Many methods have been proposed for automated needle insertion, but they often rely on hand-crafted pipelines with modular controllers, whose performance degrades in challenging cases. In this paper, a Vi

Junyu Ren, Wensheng Gan, Philip S Yu

Fault diagnosis under unseen operating conditions remains highly challenging when labeled data are scarce. Semi-supervised domain generalization fault diagnosis (SSDGFD) provides a practical solution by jointly exploiting labeled and unlabeled source domains. However, existing methods still suffer from two coupled limitations. First, pseudo-labels for unlabe

Sylvie Boldo, François Clément, Vincent Martin, Micaela Mayero

Formalization of mathematics is a major topic, that includes in particular numerical analysis, towards proofs of scientific computing programs. The present study is about the finite element method, a popular method to numerically solve partial differential equations. In the long-term goal of proving its correctness, we focus here on the formal definition of

Maarten Baes

The core-S\'ersic model is the standard tool for describing partially depleted stellar cores in massive early-type galaxies, yet its physical admissibility has rarely been examined. Using numerical deprojections, we show that many formally allowed parameter combinations cannot represent realistic stellar systems: sharp transitions between the inner power-law

Yong Luo

In this paper, motivated by study on universal inequalities for eigenvalues of the Dirichlet Laplacian, we prove some new inequalities for eigenvalues of the Dirichlet Laplacian on the hyperbolic space. In particular, we verify Cheng's conjecture (Adv. Lect. Math. 37, 2017) up to loss of $\epsilon$ for two special kinds of bounded domains in the hyperbolic s

Katerina Ioannidou, Marios D. Dikaiakos, Athena Stassopoulou

This paper presents e112, a context-aware mobile emergency response application designed to strengthen communication between citizens and authorities during disasters. Building on the ubiquity of smartphones, the system provides SOS requests, incident reporting, customized alerts, evacuation guidance, and moderated community interaction, supported by a cloud

Andreas Morr, Maya Ben-Yami, Brian Groenke, Christof Schötz

Ditlevsen and Ditlevsen [Nature Communications, 2023] (DD23 hereafter) propose a statistical framework to estimate the timing of a potential collapse of the Atlantic Meridional Overturning Circulation (AMOC) based on extrapolating information from observed sea-surface temperature (SST) variability. By fitting a stochastic one-dimensional fold-bifurcation mod

Teppei Kitahara, Manas Kumar Mohapatra, Kota Sasaki

We derive a robust sum rule among the branching fractions of $\Lambda_b \to \Lambda \nu \bar\nu$ and $B \to K^{(\ast)} \nu\bar\nu$, assuming that right-handed neutrinos are decoupled. Despite the presence of 18 independent Wilson coefficients in the effective Hamiltonian, this relation remains exact. Remarkably, it is found that the coefficients of this bary

Piermarco Cannarsa, Valerio Lucarini, Patrick Martinez, Cristina Urbani

We study a two-layer one-dimensional energy balance model, which allows for vertical energy exchanges between a surface layer and the atmosphere, as well as meridional energy transport across latitudes via a diffusion law. The evolution equations of the surface temperature and the atmospheric temperature are coupled by exchange of infrared radiation as well

Álvaro Troyano Olivas, Andrés Agustí Casado, Hans H. Brunner, Chi-Hang Fred Fung

Efficient resource allocation and optical switching promise high key rates, network adaptability, and cost reduction in repeaterless quantum communication networks. However, identifying optimal switching configurations remains a significant challenge due to the combinatorial complexity. We introduce a novel graph formulation to model the physical and logical

M. Biswas, K. Bhattacharya, K. M. Ranjith, S. M. Hossain

Despite recent progress in identifying the exotic random singlet (RS) state in disordered frustrated magnets as a distinct correlated phase, three-dimensional (3D) realizations remain scarce. Sr$_3$CuNb$_2$O$_9$ was proposed to be one of such 3D frustrated systems with magnetic site disorder hosting an RS ground state. Here, we report a detailed microscopic

Jiahao Xu, Xiaohan Yuan, Xingchen Wu, Chongyang Xu

Co-manipulation requires multiple humans to synchronize their motions with a shared object while ensuring reasonable interactions, maintaining natural poses, and preserving stable states. However, most existing motion generation approaches are designed for single-character scenarios or fail to account for payload-induced dynamics. In this work, we propose a

Dariusz Chruściński, Farrukh Mukhamedov

We study a class of quantum dynamical maps for d-level systems that interpolate between positive, Schwarz, and completely positive evolutions. Our approach is based on a geometric analysis of the parameter space, which reveals the structure of regions corresponding to different positivity classes and their boundaries. We show that dynamical trajectories natu

Antoine Heranval, Olivier Lopez, Didier Ngatcha, Daniel Nkameni

According to the United Nations Office for Disaster Risk Reduction (2025), the average annual cost of natural catastrophes increased from 70--80 billion USD between 1970 and 2000 to 180--200 billion USD between 2001 and 2020. Reports from organizations such as the IFOA and the WWF highlight the need for the insurance sector to adapt to this rapidly evolving

Hyeokmin Lee, Youngkyu Kim, Byounghyun Yoo

The advent of NMT has expanded the scope of translation beyond isolated sentences, enabling context to be preserved across paragraphs and documents. However, current evaluation metrics largely remain restricted to the sentence level and typically depend on reference translations. Without references, existing metrics cannot provide a clear basis for their qua

Akira Tamamori

High-capacity associative memories based on Kernel Logistic Regression (KLR) achieve strong retrieval performance but typically require substantial computational resources. This paper investigates the compressibility of KLR Hopfield networks to clarify the geometric principles underlying their robust representations. We present a geometric interpretation bas

Stéphane Fischler, Tanguy Rivoal

Let $\xi$ be a value, at an algebraic point, of a Siegel $E$-function. As a special case of a very general interpolation result, we prove that there exists an $E$-function $f$ such that $f(1)=\xi$, and such that 1 is not a singularity of the minimal differential equation satisfied by $f$. We prove that the same property does not hold at the point $0$, when $

Changho Han, Songsoo Kim, Dong Won Kim, Leo Anthony Celi

Large language models (LLMs), trained on vast datasets, encode extensive real-world knowledge within their parameters, yet their black-box nature obscures the mechanisms and extent of this encoding. Surrogate modeling, which uses simplified models to approximate complex systems, can offer a path toward better interpretability of black-box models. We propose

Athanasios Beslikas

We study composition operators acting on the weighted Bergman spaces on the bidisc, i.e. $C_{\Phi}:A^2_{\beta}(\mathbb{D}^2)\to A^2_{\beta}(\mathbb{D}^2)$ where $\Phi$ is induced by rational inner functions (RIFs) or a RIF and a smooth function (mixed case). Our approach is geometric. Our main result is a uniform criterion for all $\beta\in(-1,0]$ that can b

Tristan Guillaume

Let $X_t = B_t + \mu t$, $t \geq 0$, be planar Brownian motion with nonzero drift, and let $K_t^r = \{x \in \mathbb{R}^2 : {\rm dist}(x, X[0,t]) \leq r\}$ be the radius-$r$ Wiener sausage up to time $t$. For a bounded Borel function $\psi$ supported in a compact interval $[r_0, r_1] \subset (0,\infty)$, consider the smoothed Betti-curve functional $\Phi_\psi

L. Roth, K. D. Retherford, J. Saur, D. F. Strobel

An image of Lyman-$\alpha$ (Ly$\alpha$) emission from Europa obtained with the Hubble Space Telescope Space Telescope Imaging Spectrograph (HST/STIS) has previously provided the first evidence of localized water vapor (H$_2$O) aurora, potentially originating from outgassing. Subsequent STIS observations have revealed the presence of a global atomic hydrogen

Benjamin Jourdain, Stéphane Menozzi

We emphasize that for a stochastic differential equation with isotropic stable additive noise and non Lipschitz drift, when considering an appropriate discretization scheme and the associated weak error, it is somehow natural to consider a test function having the same spatial regularity as the drift involved. We will in particular focus on drifts belonging

Yui Tomo, Shinto Eguchi, Daisuke Yoneoka

The zero-inflated logistic regression model accommodates binary responses with excess zeros, which often arise from a latent mixture of susceptible and insusceptible subpopulations or asymmetric misclassification of the response. The model has two components: regression for the binary response and a latent binary indicator for the zero-inflation state. In ap

Alessia Ciacco, Luigi Di Puglia Pugliese, Francesca Guerriero

The Traveling Salesman Problem is a classical NP-hard combinatorial optimization problem that has been extensively studied in operations research. A major challenge in Traveling Salesman Problem formulations is the large number of subtour elimination constraints required to ensure a valid tour. To address this issue, we adopt an iterative approach grounded i

Lauri Oksanen, Miika Sarkkinen

We show that two non-isometric, smooth, globally hyperbolic Lorentzian metrics can have the same hyperbolic Dirichlet-to-Neumann map on an infinite cylinder with timelike boundary.

Gui Wang, YongSong Zhou, Kaijun Deng, Wooi Ping Cheah

Fine-grained spatiotemporal reasoning on surgical videos is critical, yet the capabilities of Multi-modal Large Language Models (MLLMs) in this domain remain largely unexplored. To bridge this gap, we introduce SurgCoT, a unified benchmark for evaluating chain-of-thought (CoT) reasoning in MLLMs across 7 surgical specialties and 35 diverse procedures. SurgCo

Jan Pennekamp, Johannes Lohmöller, David Schütte, Joscha Loos

Preprints are essential for the timely and open dissemination of research. arXiv, the most widely used preprint service, takes the idea of open science one step further by not only publishing the actual preprints but also LaTeX sources and other files used to create them. As known from other contexts, such as GitHub repositories, and anecdotally exemplified

Tristan Guillaume

Barrier derivatives depend on extrema and first-passage events and are therefore highly sensitive to volatility dynamics -- especially to the instantaneous return-volatility correlation $\rho$, often called ``leverage''. This sensitivity makes accurate and fast pricing under realistic stochastic-volatility specifications difficult: two-dimensional PDE solver

Xuan Cui, Yunfei Zhao, Bo Liu, Wei Duan

GAN-based facial attribute editing is widely used in virtual avatars and social media but often suffers from attribute entanglement, where modifying one face attribute unintentionally alters others. While supervised disentangled representation learning can address this, it relies heavily on labeled data, incurring high annotation costs. To address these chal

Yousouf Taghzouti, Tao Jiang, Camille Juigné, Benjamin Navet

The evaluation of Question Answering (QA) systems over Knowledge Graphs has historically suffered from fragmentation, inconsistency, and limited reproducibility. While significant progress has been made in semantic parsing and SPARQL query generation, evaluation methodologies remain diverse, ad hoc, and often incomparable across studies. Existing benchmarks

Gernot Stroth

We consider saturated fusion systems $\mathcal F$ on a Sylow $2$-subgroup of $\Omega^+_8(2)$ with $O_2(\mathcal F) = 1$. Examples for this are the $2$-fusion systems of $\Omega^+_8(2)$, $\Omega^+_8(2):3$, $P\Omega^+_8(3)$ and $P\Omega^+_8(3):3$

Xiang Shi, Shuaizhi Cheng, Mingwei Li

This technical note provides a first-order formalisation of the logit shift and fact-margin change induced by Low-Rank Adaptation (LoRA). Using a first-order Fr\'echet approximation around the base model trajectory, we show that the multi-layer LoRA effect can be decomposed into a linear summation of layerwise contributions and a higher-order remainder term

Pei-Hao Fu, Jun-Feng Liu, Luca Chirolli, Jorge Cayao

We consider a superconducting altermagnet heterostructure and demonstrate that the interplay between altermagnetism and a selective filter of transverse momentum channels enables perfect nonreciprocal spin-polarized currents. We demonstrate that this nonreciprocity manifests in both local and nonlocal spin currents, signalling the emergence of directionally

Dali Wang, Yunyao Zhang, Junqing Yu, Yi-Ping Phoebe Chen

Micro-video popularity prediction (MVPP) aims to forecast the future popularity of videos on online media, which is essential for applications such as content recommendation and traffic allocation. In real-world scenarios, it is critical for MVPP approaches to understand both the temporal dynamics of a given video (temporal) and its historical relevance to o

Yuki Harada, Manuel Aleixandre, Manabu Okumura, Takamichi Nakamoto

The application of large language models (LLMs) to OdorSpace analysis attracts growing interest. Recent studies have explored the comparison of sensory evaluation spaces derived from LLMs with odor character profiles in the Dravnieks' dataset. In this study, we calculated pairwise distances of odor descriptors using three distance measures and statistically

Steffen Staeck, Can Yildirim, Raquel Rodriguez-Lamas, Thomas Dufrane

We introduce the use of a crossed pair of Multilayer Laue Lenses (MLLs) as an objective in Dark-Field X-ray Microscopy (DFXM). In a demonstration experiment at the ID03 beamline at ESRF, two flat Mo-Si MLLs were used, with a physical aperture of 50 x 50 $\mathrm{\mu m^2}$ and a focal length of 14.25 mm at 19 keV. Applying a 10 % criterion to the Modulation T

Serap Kırbız

In this paper, a deep learning framework is proposed for automatic facial emotion based on deep convolutional networks. In order to increase the generalization ability and the robustness of the method, the dataset size is increased by merging three publicly available facial emotion datasets: CK+, FER+ and KDEF. Despite the increase in dataset size, the minor

Zibo Xu, Qiang Li, Ke Lu, Jin Wang

Medical Visual Question Answering (MedVQA) aims to generate clinically reliable answers conditioned on complex medical images and questions. However, existing methods often overfit to superficial cross-modal correlations, neglecting the intrinsic biases embedded in multimodal medical data. Consequently, models become vulnerable to cross-modal confounding eff

Kui Wu, Hao Chen, Jinzhu Han, Haijun Liu

Realizing active visual tracking with a single unified model across diverse robots is challenging, as the physical constraints and motion dynamics vary drastically from one platform to another. Existing approaches typically train separate models for each embodiment, leading to poor scalability and limited generalization. To address this, we propose AdaTracke

Ryo Tamura, Haruhiko Morito, Yuna Oikawa, Guillaume Deffrennes

Constructing phase diagrams for multicomponent alloys requires extensive experimental measurements and is a time-consuming task. Here we investigate whether large language models (LLMs) can guide experimental planning for phase diagram construction. In our framework, a general-purpose LLM serves as the experimental planner, suggesting compositions for measur

Paolo Solinas, Beatrice Donelli, Stefano Gherardini

We introduce an operational criterion to identify Wigner function (WF) negativity for an arbitrary quantum state within the framework of quantum non-demolition measurements. This criterion corresponds to experimentally accessible schemes that enable a direct measurement of the WF, and establishes the coherent-state basis as a privileged basis for determining

Anjie Qiu, Donglin Wang, Zexin Fang, Sanket Partani

Cloud-hosted LLM inference for autonomous driving adds round-trip delay and depends on stable connectivity, while purely local edge models struggle under occlusion. We present SwarmDrive, a semantic Vehicle-to-Vehicle (V2V) coordination framework in which nearby vehicles run local Small Language Models (SLMs), share compact intent distributions only when unc

Rania Islambouli, Laura Geiger, Daniela Wurhofer, Devender Kumar

Monitoring exercise intensity is critical for safe and effective physical activity, particularly for individuals with cardiovascular disease, where overexertion can pose serious risks. Although physiological measures such as heart rate are widely used for avoiding overexertion, they can be unreliable in certain cases, such as when affected by medication or w

Francesca Romana Crucinio, Sahani Pathiraja

We consider the problem of sampling from a probability distribution $\pi$. It is well known that this can be written as an optimisation problem over the space of probability distributions in which we aim to minimise the Kullback--Leibler divergence from $\pi$. We consider the effect of replacing $\pi$ with a sequence of moving targets $(\pi_t)_{t\ge0}$ defin

Yingjie Gu, Wenjian Xiong, Liqiang Wang, Pengcheng Ren

For LLM agents, memory management critically impacts efficiency, quality, and security. While much research focuses on retention, selective forgetting--inspired by human cognitive processes (hippocampal indexing/consolidation theory and Ebbinghaus forgetting curve)--remains underexplored. We argue that in resource-constrained environments, a well-designed fo

Zechao Jiang, Zhaoyu Ding, Shaohua Yang, Ye Xu

Surface creasing in swelling polymer gels is commonly attributed to compressive strain or interlayer mismatch, yet its general control remains unclear. Here we show that solvent polymerization degree $N_{\rm s}$ provides an independent control parameter for crease onset in surface-bound polydimethylsiloxane gels swollen by silicone oils. Despite nearly ident

Kun Zhang, Yuanyang Zhou

In this paper, with suitable assumptions, we generalize the work of K\"ulshammer and Puig on extensions of nilpotent blocks to inertial blocks.

Yahong Guo, Chilin Zhang

We focus on the classification of positive solutions to $(-\Delta)^s u=\frac{x_n^{\alpha}}{u^\gamma}$ in the half space with $\gamma>0$, subject to the Dirichlet condition. We show that when $-2s<\alpha<(\gamma-1)s$, all positive solutions exhibit one-dimensional symmetry and are monotone increasing in $x_n$. Moreover, we provide a complete classification of

Yang Xu, Wenbin Lu, Rui Song

Survival analysis is a widely used statistical framework for modeling time-to-event data under censoring. Classical methods, such as the Cox proportional hazards (Cox PH) model, offer a semiparametric approach to estimating the effects of covariates on the hazard function. Despite its importance, survival analysis has been largely unexplored in online settin

Zhe Xu, Feiyu Zhao, Xiyan Huang, Chenxi Xiao

Tactile sensors are increasingly integrated into dexterous robotic manipulators to enhance contact perception. However, learning manipulation policies that rely on tactile sensing remains challenging, primarily due to the trade-off between fidelity and computational cost of soft-body simulations. To address this, we present ETac, a tactile simulation framewo