July 2025 arXiv papers — page 4

Samah Kansab

The rapid advancement of software development practices has introduced challenges in ensuring quality and efficiency across the software engineering (SE) lifecycle. As SE systems grow in complexity, traditional approaches often fail to scale, resulting in longer debugging times, inefficient defect detection, and resource-heavy development cycles. Machine Lea

Gerhard Buchalla, Florian Pandler

We investigate the production of (longitudinal) $Z$-boson pairs in gluon fusion as a probe of anomalous Higgs couplings. Of particular interest is the kinematic region of large center-of-mass energy, where the Higgs-boson is highly off-shell. We employ the electroweak chiral Lagrangian with a light Higgs, which is the most natural effective field theory (EFT

Yang Gao, Po-Chien Luan, Kaouther Messaoud, Lan Feng

While large-scale pre-training has advanced human trajectory prediction, a critical challenge remains: zero-shot transfer to unseen dataset with varying temporal dynamics. State-of-the-art pre-trained models often require fine-tuning to adapt to new datasets with different frame rates or observation horizons, limiting their scalability and practical utility.

Shenghao Hua

Let $f$ be a primitive holomorphic newform of weight at least $2$ and arbitrary level. We consider the representations obtained from its symmetric powers by taking tensor products, symmetric powers, and isobaric sums. Classical $\mathrm{GL}(2)$ representation theory decomposes each such expression into symmetric powers with determinant twists. This gives an

Jian Ren, F. S. Liu, Nan Li, Qi Song

We present a systematic study of merging galaxies among Lyman-alpha emitters (LAEs) using JWST/NIRCam high-resolution imaging data. From a large sample of 817 spectroscopically confirmed LAEs at $3<z<7$ in the GOODS-S field, we identify late-stage mergers and interacting systems with fractions of $39.4\%\pm2.5\%$ and $60.6\%\pm6.3\%$, respectively. These fra

Mustapha El Moussaoui

In an era of exponential technological advancement, artificial intelligence (AI) has emerged as a transformative force in architecture, reshaping traditional design and construction practices. This article explores the multifaceted roles of AI in the architectural process, emphasizing its potential to enhance creativity and efficiency while addressing its li

Kunpeng Qiu, Zhiying Zhou, Yongxin Guo

Medical image annotation is constrained by privacy concerns and labor-intensive labeling, significantly limiting the performance and generalization of segmentation models. While mask-controllable diffusion models excel in synthesis, they struggle with precise lesion-mask alignment. We propose \textbf{Adaptively Distilled ControlNet}, a task-agnostic framewor

Ashwini Malviya

As an extension to our previous work [1], a comprehensive theoretical study for Na-like Krypton and Xenon is carried out. Using MCDHF (Multiconfiguration Dirac-Hartee-Fock) along with RDW (Relativistic distorted wave) theory we calculate key atomic properties, electron-impact excitation (EIE), rate coefficients, and collision strength for these ions. We use

Dang Duc Trong, Nguyen Dang Minh, Luu Xuan Thang, Luu Dang Khoa

Let $X$ and $Y$ be Hilbert spaces, and $\mathbf{K}: \text{dom} \mathbf{K} \subset X \to Y$ a bounded linear operator. This paper addresses the inverse problem $\mathbf{K}x = y$, where exact data $y$ is replaced by noisy data $y^\delta$ satisfying $\|y^\delta - y\|_Y \leq \delta$. Due to the ill-posedness of such problems, we employ regularization methods to

Yakir Aharonov, Daniel Collins, Sandu Popescu

The existence of electromagnetic radiation - radio-waves, microwaves, light, x-rays and so on - is one of the most important physical phenomena, and our ability to manipulate them is one of the most significant technological achievement of humankind. Underlying this ability is our understanding of how radiation is produced: whenever an electric charge is acc

Qing Zhang, Karin M. Rabe, Xiaohui Liu

Could electrons stabilize ferroelectric polarization in unpolarized system? Basically, electron doping was thought to be contrary to polarization due to the well-known picture that the screening effect on Coulomb interaction diminishes ferroelectric polarization. However, in this paper, we propose a novel mechanism of stabilizing highly-polar supertetragonal

Louise Guillon, Soheib Biga, Yendoube E. Kantchire, Mouhamadou Lamine Sane

Malaria remains a major global health challenge, particularly in low-resource settings where access to expert microscopy may be limited. Deep learning-based computer-aided diagnosis (CAD) systems have been developed and demonstrate promising performance on thin blood smear images. However, their clinical deployment may be hindered by limited generalization a

Rasmus S. Nielsen, Axel G. Medaille, Arnau Torrens, Oriol Segura-Blanch

Selenium is experiencing renewed interest as a elemental semiconductor for a range of optoelectronic and energy applications due to its irresistibly simple composition and favorable wide bandgap. However, its high volatility and low radiative efficiency make it challenging to assess structural and optoelectronic quality, calling for advanced, non-destructive

Jaehyung Choi

We develop the information geometry of L\'evy processes. Deriving $\alpha$-divergences directly in terms of the L\'evy triplets of the L\'evy processes, we identify Fisher information matrix and $\alpha$-connection on the statistical manifold. In addition, we discuss statistical implications of this information geometry, including bias reduction estimation a

Geng Chen, Cooper Faile, Sam G. Krupa

We consider hyperbolic systems of conservation laws in one spatial dimension. For any limit of front tracking solutions $v$, and for a general weak solution $u\in L^\infty$ with no BV assumption, we prove the following H\"older-type stability estimate in $L^2$: $$||u(\cdot,\tau)-v(\cdot,\tau)||_{L^2} \leq K \sqrt{||u( \cdot,0)-v( \cdot,0)||_{L^2}}$$ for all

Changqing Xu, Ziqiang Yang, Yi Liu, Xinfang Liao

Spiking Neural Networks (SNNs) offer a biologically plausible framework for energy-efficient neuromorphic computing. However, it is a challenge to train SNNs due to their non-differentiability, efficiently. Existing gradient approximation approaches frequently sacrifice accuracy and face deployment limitations on edge devices due to the substantial computati

Dustin Carrión-Ojeda, Stefan Roth, Simone Schaub-Meyer

Few-shot classification and segmentation (FS-CS) focuses on jointly performing multi-label classification and multi-class segmentation using few annotated examples. Although the current state of the art (SOTA) achieves high accuracy in both tasks, it struggles with small objects. To overcome this, we propose the Efficient Masked Attention Transformer (EMAT),

Chloe Li, Mary Phuong, Noah Y. Siegel

Trustworthy evaluations of dangerous capabilities are increasingly crucial for determining whether an AI system is safe to deploy. One empirically demonstrated threat is sandbagging - the strategic underperformance on evaluations by AI models or their developers. A promising defense is to monitor a model's chain-of-thought (CoT) reasoning, as this could reve

Michael Schaller

In this paper we introduce a rank $2$ lattice over a polynomial ring arising from the public key of the BIKE cryptosystem. The secret key is a sparse vector in this lattice. We study properties of this lattice and generalize the recovery of weak keys from "Weak keys for the quasi-cyclic MDPC public key encryption scheme". In particular, we show that they imp

Samah Kansab, Mohammed Sayagh, Francis Bordeleau, Ali Tizghadam

Code review (CR) is essential to software development, helping ensure that new code is properly integrated. However, the CR process often involves significant effort, including code adjustments, responses to reviewers, and continued implementation. While past studies have examined CR delays and iteration counts, few have investigated the effort based on the

Juntao Sun, Shuai Yao, He Zhang

We study normalized solutions for the nonlinear Schrodinger (NLS) equation with potential and Sobolev critical nonlinearity. By establishing suitable assumptions on the potential, together with new techniques, we find a mountain-pass type solution for N>=6, which solves an open problem presented in a recent paper [Verzini and Yu, arXiv:2505.05357v1]. Moreove

Le Chen, Jingyu Huang, Wenxuan Tao

We consider the stochastic heat equation (SHE) on the torus $\mathbb{T}=[0,1]$, driven by space-time white noise $\dot W$, with an initial condition $u_0$ that is nonnegative and not identically zero: \begin{equation*} \frac{\partial u}{\partial t} = \tfrac{1}{2}\frac{\partial^2 u}{\partial x^2} + b(u) + \sigma(u)\dot{W}. \end{equation*} The drift $b$ and di

Abby Barlow, Ben Adams

The release of Wolbachia-infected mosquitoes into Aedes aegypti infested areas is a promising strategy for localised eradication of dengue infection. Ae aegypti mosquitoes favour urban environments as breeding habitats, so are often found in and around houses. Therefore, it is likely that they will infect members of the households that they reside around. Si

Shouhong Qiao, Ning Su, Binzhou Xia, Zhishuo Zhang

A perfect code in a graph $\Gamma=(V, E)$ is a subset $C$ of $V$ such that no two vertices in $C$ are adjacent and every vertex in $V \setminus C$ is adjacent to exactly one vertex in $C$. A subgroup $H$ of a group $G$ is called a subgroup perfect code of $G$ if it is a perfect code in some Cayley graph of $G$. In this paper, we undertake a systematic study

Peter West

I give an account of the discovery of supergravity and the first six years of its development which lead to the most general coupling of supergravity to matter. I restrict the discussion to theories with only one supersymmetry that are in four dimensions. As well as describing the contents of the papers I will also discuss the ideas and techniques they used.

Qian Zhao, Zhuo Sun, Bin Guo, Zhiwen Yu

Agent-assisted memory recall is one critical research problem in the field of human-computer interaction. In conventional methods, the agent can retrieve information from its equipped memory module to help the person recall incomplete or vague memories. The limited size of memory module hinders the acquisition of complete memories and impacts the memory reca

Khaled Mnaymneh

Quantum mechanics is widely regarded as a complete theory, yet we argue it is a tractable projection of a deeper, computationally-inaccessible classical variational structure. By analyzing the coupled partial differential equations of the Hamilton type 1 principal function, we show that classical action-based dynamics are generally undecidable, paralleling s

Gabriel Mongaras, Eric C. Larson

Since its introduction, softmax attention has become the backbone of modern transformer architectures due to its expressiveness and scalability across a wide range of tasks. However, the main drawback of softmax attention is the quadratic memory requirement and computational complexity with respect to the sequence length. By replacing the softmax nonlinearit

Marion Mallweger, Natalia Kuk, Vinay Shankar, Robin Thomm

State-dependent conformational changes play a central role in molecular dynamics, yet they are often difficult to observe or simulate due to their complexity and ultrafast nature. One alternative approach is to emulate such phenomena using quantum simulations with cold, trapped ions. In their electronic ground state, these ions form long-lived Wigner crystal

Dominick S. Scaletta, Ngoc Thanh Mai Tran, Marta Musso, Valery Ortiz Jimenez

This work elaborates on how one may develop high-resistance quantized Hall array resistance standards (QHARS) by using star-mesh transformations for element count minimization. Refinements are made on a recently developed mathematical framework optimizing QHARS device designs based on full, symmetric recursion by reconciling approximate device values with ex

Yewei Huang, John McConnell, Xi Lin, Brendan Englot

We present DRACo-SLAM2, a distributed SLAM framework for underwater robot teams equipped with multibeam imaging sonar. This framework improves upon the original DRACo-SLAM by introducing a novel representation of sonar maps as object graphs and utilizing object graph matching to achieve time-efficient inter-robot loop closure detection without relying on pri

Matéo Spriet

We define the Kirkwood-Dirac quasiprobability representation of quantum mechanics associated with the Fourier transform over second countable locally compact abelian groups. We discuss its link with the Kohn-Nirenberg quantization of the phase space $G\times \widehat{G}$. We use it to argue that in this abstract setting the Wigner-Weyl quantization, when it

Eric James Faust, Michael Tait

Let $F_h(n)$ denote the minimum cardinality of an additive {\em $h$-fold basis} of $\{1,2,\cdots,n\}$: a set $S$ such that any integer in $\{1,2,\cdots, n\}$ can be written as a sum of at most $h$ elements from $S$. While the trivial bounds $h!n \; \lesssim \; F_h(n)^h \; \lesssim \; h^h n$ are well-known, comparatively little has been established for $h>2$.

I. Babich, I. Reznikov, I. Begichev, A. E. Kazantsev

The electronic quality of graphene has improved significantly over the past two decades, revealing novel phenomena. However, even state-of-the-art devices exhibit substantial spatial charge fluctuations originating from charged defects inside the encapsulating crystals, limiting their performance. Here, we overcome this issue by assembling devices in which g

Dominick S. Scaletta, Ngoc Thanh Mai Tran, Marta Musso, Dean G. Jarrett

This work introduces a pseudofractal analysis for optimizing high-resistance graphene-based quantized Hall array resistance standards (QHARS). The development of resistance standard device designs through star-mesh transformations is detailed, aimed at minimizing element count. Building on a recent mathematical framework, the approach presented herein refine

Michelle Delcourt, Cicely, Henderson, Thomas Lesgourgues

In 1847, Kirkman proved that there exists a Steiner triple system on $n$ vertices (equivalently a triangle decomposition of the edges of $K_n$) whenever $n$ satisfies the necessary divisibility conditions (namely $n\equiv 1,3 \mod 6$). In 1970, Nash-Williams conjectured that every graph $G$ on $n$ vertices with minimum degree at least $3n/4$ (for $n$ large e

Guillaume Valette

These notes constitute a survey on the geometric properties of globally subanalytic sets. We start with their definition and some fundamental results such as Gabrielov's Complement Theorem or existence of cell decompositions. We then give the main basic tools of subanalytic geometry, such as Curve Selection Lemma, Lojasiewicz's inequalities, existence of tub

Robbe De Prins, Guy Van der Sande, Peter Bienstman, Thomas Van Vaerenbergh

Ising machines (IMs) are specialized devices designed to efficiently solve combinatorial optimization problems. Among such problems, Boolean Satisfiability (SAT) is particularly relevant in industrial applications. To solve SAT problems using IMs, it is crucial to incorporate higher-order interactions. However, in analog IMs, interactions of different orders

Ullika Scholz, Julian Koellermeier

Reduced models for free-surface flows are required due to the high dimensionality of the underlying incompressible Navier-Stokes equations, which need to fully resolve the flow in vertical direction to compute the surface height. On the other hand, standard reduced models, such as the classical Shallow Water Equations (SWE), which assume a small depth-to-len

Yucheng Xie, Fu Feng, Ruixiao Shi, Jing Wang

Diffusion models have advanced from text-to-image (T2I) to image-to-image (I2I) generation by incorporating structured inputs such as depth maps, enabling fine-grained spatial control. However, existing methods either train separate models for each condition or rely on unified architectures with entangled representations, resulting in poor generalization and

Grzegorz M. Koczan, Piotr Stachura

The article presents, in an elementary way, but with mathematical precision and without harm to the intuition, the path from the integral representation to the Dirac delta, starting with Schwartz's functional approach. Next, the considered representation is presented in a more intuitive sequential approach, formulated by Mikusi\'nski and Sikorski. Finally, w

Ignas Gasparavičius, Andrius Grigutis, Juozas Petkelis

Let ${\pmb b}=\{b_0,\,b_1,\,\ldots\}$ be the known sequence of numbers such that $b_0\neq0$. In this work, we develop methods to find another sequence ${\pmb a}=\{a_0,\,a_1,\,\ldots\}$ that is related to ${\pmb b}$ as follows: $a_n=a_0\,b_{n+m}+a_1\,b_{n+m-1}+\ldots+a_{n+m}\,b_0$, $n\in\mathbb{N}\cup\{0\}$, $m\in\mathbb{N}$. We show the connection of $\lim_{

Xinyi Guo, Geguang Miao, Shinichi Nishizawa, Hiromitsu Awano

Conventional quantum error correction (QEC) decoders such as Minimum-Weight Perfect Matching (MWPM) and Union-Find (UF) offer high thresholds and fast decoding, respectively, but both suffer from high topological complexity. In contrast, Ising model-based decoders reduce topological complexity but demand considerable decoding time. We propose the Symmetric O

Sana Boughdachi, Benedikt Heizenreder, Ananya Sitaram, Erik Dierikx

We demonstrate a quasi-continuous sub-$\mu$K strontium source achieved without the use of a high-finesse cavity-locked laser. Our frequency reference is based on a dispersion-optimized, fiber-based frequency comb that enables sub-kHz linewidths. The long-term stability of the comb is defined by an external RF reference: either a 10 MHz RF signal from the Dut

Giulia Janzen, Euan D. Mackay, Rastko Sknepnek, D. A. Matoz-Fernandez

Curvature plays a central organizational role in active polymer dynamics. Using large-scale Langevin-dynamics simulations, we study active semiflexible filaments confined to smooth curved surfaces and map how curvature, bending rigidity, and activity interact. We find geodesic alignment, curvature lensing, and curvature-induced trapping. In particular, regio

Cole Jeznach

In this article, we investigate unique continuation principles for solutions $u$ of uniformly elliptic equations of the form $-\mathrm{div}(A \nabla u) = 0$ when $A$ is less regular than Lipschitz. For general matrices $A$, we prove that strong unique continuation holds provided that $A$ has modulus of continuity $\omega$ satisfying the Osgood condition $\in

Martin Lafréchoux

Over the last twenty years, smartphones gradually replaced many earlier digital tools such as PDAs, cameras and music players. Today these objects are regarded as obsolete: they may hold some esthetic or nostalgic appeal but they do not fit in a modern, zero-friction, cloud-first workflow. Yet these devices still have desirable qualities that smartphones lac

Daniel Appelö, Francis Appiah, Jeffrey W. Banks, Cassandra Carrick

We develop and analyze a new approach for simultaneously computing multiple solutions to the Helmholtz equation for different frequencies and different forcing functions. The new Multi-Frequency WaveHoltz (MFWH) algorithm is an extension of the original WaveHoltz method and both are based on time-filtering solutions to an associated wave equation. With MFWH,

Sayan Bhowmik, Andrew J. Medford, Phanish Suryanarayana

We present an accurate and efficient framework for real-space Hubbard-corrected density functional theory. In particular, we obtain expressions for the energy, atomic forces, and stress tensor suitable for real-space finite-difference discretization, and develop a large-scale parallel implementation. We verify the accuracy of the formalism through comparison

Stephen Cusack

Large variations of European storm activity at decadal and longer timescales have been found to be driven by major tropical volcanic eruptions, internal climate variability and anthropogenic aerosols (AA). The insurance industry have the ability to align with these slow fluctuations in windstorm risk, yet have not done so, due to uncertainty in how the clima

Estelle Ruellan, Eric Clay, Nicholas Ascoli

Infostealers exfiltrate credentials, session cookies, and sensitive data from infected systems. With over 29 million stealer logs reported in 2024, manual analysis and mitigation at scale are virtually unfeasible/unpractical. While most research focuses on proactive malware detection, a significant gap remains in leveraging reactive analysis of stealer logs

Monika Robotkova

Jets are multiscale objects that connect partons to hadrons, making jet substructure measurements crucial for probing both perturbative and non-perturbative processes in QCD. At STAR, a variety of jet substructure observables, such as SoftDrop groomed splittings and N-Point Energy Correlators (ENC), provide insights into parton evolution and hadronization me

Halid Ziya Yerebakan, Gerardo Hermosillo Valadez

This study demonstrates that incorporating a consistency heuristic into the point-matching algorithm \cite{yerebakan2023hierarchical} improves robustness in matching anatomical locations across pairs of medical images. We validated our approach on diverse longitudinal internal and public datasets spanning CT and MRI modalities. Notably, it surpasses state-of

Linmin Pei, Granger Sutton, Michael Rutherford, Ulrike Wagner

The de-identification (deID) of protected health information (PHI) and personally identifiable information (PII) is a fundamental requirement for sharing medical images, particularly through public repositories, to ensure compliance with patient privacy laws. In addition, preservation of non-PHI metadata to inform and enable downstream development of imaging

Tien Huu Do, Antoine Masquelier, Nae Eoun Lee, Jonathan Crowther

Clinical trials are a systematic endeavor to assess the safety and efficacy of new drugs or treatments. Conducting such trials typically demands significant financial investment and meticulous planning, highlighting the need for accurate predictions of trial outcomes. Accurately predicting patient enrollment, a key factor in trial success, is one of the prim

Andrea Loi, Roberto Mossa, Fabio Zuddas

We prove a universal embedding theorem for flag manifolds: every flag manifold admits a holomorphic isometric embedding into an irreducible classical flag manifold. This result generalizes the classical celebrated embedding theorems of Takeuchi [30] and Nakagawa-Takagi [27]. Using this embedding, we establish new rigidity phenomena for holomorphic isometries

Yuansheng Lu, Wanlou Wu

In this paper, we proved that for every $C^1$ star vector fields on three-dimensional manifolds, every ergodic hyperbolic invariant measure which is not supported on singularities can be approximated by periodic measures, and the Lyapunov exponents of the ergodic hyperbolic invariant measure can also be approximated by the Lyapunov exponents of those periodi

Andoni Rodriguez, Irfansha Shaik, Davide Corsi, Roy Fox

Safe Reinforcement Learning focuses on developing optimal policies while ensuring safety. A popular method to address such task is shielding, in which a correct-by-construction safety component is synthesized from logical specifications. Recently, shield synthesis has been extended to infinite-state domains, such as continuous environments. This makes shield

Moaad Khamlich, Francesco Romor, Gianluigi Rozza

Semi-discrete optimal transport (SOT), which maps a continuous probability measure to a discrete one, is a fundamental problem with wide-ranging applications. Entropic regularization is often employed to solve the SOT problem, leading to a regularized (RSOT) formulation that can be solved efficiently via its convex dual. However, a significant computational

Xin Li, Keren Fu, Qijun Zhao

Existing video camouflaged object detection (VCOD) methods primarily rely on spatial appearances for motion perception. However, the high foreground-background similarity in VCOD limits the discriminability of such features (e.g. color and texture). Recent studies demonstrate that frequency features can not only compensate for appearance limitations, but als

Yu-Tang Chang, Shih-Fang Chen

Signal unmixing analysis decomposes data into basic patterns and is widely applied in chemical and biological research. Multivariate curve resolution (MCR), a branch of signal unmixing, separates mixed signals into components (base patterns) and their concentrations (intensity), playing a key role in understanding composition. Classical MCR is typically fram

Yuchen Zhou, Yan Luo, Xiaogang Wang, Xingjian Gu

Efficient and high-accuracy 3D occupancy prediction is vital for the performance of autonomous driving systems. However, existing methods struggle to balance precision and efficiency: high-accuracy approaches are often hindered by heavy computational overhead, leading to slow inference speeds, while others leverage pure bird's-eye-view (BEV) representations

David Stewart, Joern Putschke

Recent research in machine learning has employed neural networks to learn mappings between function spaces on bounded domains termed ``neural operators''. As such, these operators can provide alternatives to standard numerical methods for partial differential equation (PDE) solutions. In particular, the Fourier Neural Operator (FNO) has been shown to map sol

Zijian Dong, Longteng Duan, Jie Song, Michael J. Black

We present MoGA, a novel method to reconstruct high-fidelity 3D Gaussian avatars from a single-view image. The main challenge lies in inferring unseen appearance and geometric details while ensuring 3D consistency and realism. Most previous methods rely on 2D diffusion models to synthesize unseen views; however, these generated views are sparse and inconsist

Dmitrii Stoliarov, Sergey Sergeyev, Hani Kbashi, Fan Wu

Synchronization is ubiquitous across a wide range of fields. Subharmonic entrainment (SHE) is a nonlinear synchronization phenomenon that results in a locking oscillator at a frequency of an external periodic forcing signal with a fraction of the oscillator frequency. Beyond the fundamentals of nonlinear dynamics, SHE has a range of practical applications fr

Yaoye Zhu, Zhe Wang, Yan Wang

As cooperative systems that leverage roadside cameras to assist autonomous vehicle perception become increasingly widespread, large-scale precise calibration of infrastructure cameras has become a critical issue. Traditional manual calibration methods are often time-consuming, labor-intensive, and may require road closures. This paper proposes MamV2XCalib, t

Sebastian Pögel, Toni Teschke, Xing Wang, Stefan Weinzierl

We compute the three-loop banana integral with four unequal masses in dimensional regularisation. This integral is associated to a family of K3 surfaces, thus representing an example for Feynman integrals with geometries beyond elliptic curves. We evaluate the integral by deriving an $\varepsilon$-factorised differential equation, for which we rely on the al

Hayun Park, Hunpyo Lee

We developed a graph-based block-diagonalization (GBBD) method for the full configuration interaction Hamiltonian of molecular systems to efficiently calculate the exact eigenvalues of low-energy states. In this approach, the non-zero matrix elements of the Hamiltonian are represented as edges on a graph, which naturally decomposes into disconnected clusters

Hassan Ugail, Hamad Mansour Alawar, AbdulNasser Abbas Zehi, Ahmed Mohammad Alkendi

Face recognition systems experience severe performance degradation when processing low-quality forensic evidence imagery. This paper presents an evaluation of latent diffusion-based enhancement for improving face recognition under forensically relevant degradations. Using a dataset of 3,000 individuals from LFW with 24,000 recognition attempts, we implement

Bogoljub Terzin, E. Javier Olucha, Amritam Das, Siep Weiland

The Linear Parameter-Varying (LPV) framework is a powerful tool for controlling nonlinear and complex systems, but the conversion of nonlinear models into LPV forms often results in high-dimensional and overly conservative LPV models. To be able to apply control strategies, there is often a need for model reduction in order to reduce computational needs. Thi

Jack Collins, Adrian Buzea, Chris Collier, Alejandro Ballesta Rosen

Individuals regularly experience Hearing Difficulty Moments in everyday conversation. Identifying these moments of hearing difficulty has particular significance in the field of hearing assistive technology where timely interventions are key for realtime hearing assistance. In this paper, we propose and compare machine learning solutions for continuously det

Kai Goebel, Patrik Zips

Recent advancements in Large Language Models have sparked interest in their potential for robotic task planning. While these models demonstrate strong generative capabilities, their effectiveness in producing structured and executable plans remains uncertain. This paper presents a systematic evaluation of a broad spectrum of current state of the art language

Alexandre Misrahi, Nadezhda Chirkova, Maxime Louis, Vassilina Nikoulina

Differential Transformer has recently been proposed to improve performance in Transformer models by canceling out noise through a denoiser attention mechanism. In this work, we introduce DiffLoRA, a parameter-efficient adaptation of the differential attention mechanism, with low-rank adapters on both positive and negative attention terms. This approach retai

Darij Grinberg

This is an introduction to rings and fields, written for a quarter-long undergraduate course. It includes the basic properties of ideals, modules, algebras and polynomials, the constructions of ring extensions and finite fields, some number-theoretical applications (such as a proof of quadratic reciprocity and Jacobsthal's formulas for $p = x^2 + y^2$), and

Shuying Li, Hong Shen, Jinniu Hu

The Thomas-Fermi approximation is a powerful method that has been widely used to describe atomic structures, finite nuclei, and nonuniform matter in supernovae and neutron-star crusts. Nonuniform nuclear matter at subnuclear density is assumed to be composed of a lattice of heavy nuclei surrounded by dripped nucleons, and the Wigner-Seitz cell is commonly in

Wietse M. Boon, Johannes Kraus, Tomáš Luber, Maria Lymbery

We use the practical framework for abstract perturbed saddle point problems recently introduced by Hong et al. to analyze the mixed formulation of the Hodge Laplace problem. We compose two parameter-dependent norms in which the uniform continuity and stability of the problem follow. This not only guarantees the well-posedness of the corresponding variational

Sophia Liu, Shm Garanganao Almeda

Today's algorithm-driven interfaces, from recommendation feeds to GenAI tools, often prioritize engagement and efficiency at the expense of user agency. As systems take on more decision-making, users have less control over what they see and how meaning or relationships between content are constructed. This paper introduces "Hypertextual Friction," a conceptu

Sebastian Boldt, Peter Stollmann, Felix Wirth

We define the speed measure $\nu$ for mappings $\gamma:I\to X$ from an interval to a metric space that are locally of bounded variation. We characterize continuity and absolute continuity of $\gamma$ in terms of $\nu$ and identify the Radon-Nikod\'ym derivative of $\nu$ with respect to Lebesgue measure as the metric speed of $\gamma$. In doing so we prove an

Yue-Zhi Zhang, Leong-Chuan Kwek, Wei Nie

Topological manipulation of light provides a versatile toolbox for photonic technologies. Here, we show that a topological atom array can induce photon localization in a waveguide via symmetry-protected light-matter interaction. Long-lived photon-atom entanglement reveals the existence of a novel topological quasi-bound state in the continuum (quasi-BIC). Th

Chuanyue Yu, Kuo Zhao, Yuhan Li, Heng Chang

Graph Retrieval-Augmented Generation (GraphRAG) has shown great effectiveness in enhancing the reasoning abilities of LLMs by leveraging graph structures for knowledge representation and modeling complex real-world relationships. However, existing GraphRAG methods still face significant bottlenecks when handling complex problems that require multi-hop reason

Bradley D. Keister, Saeed Najafi, Joan-Emma Shea, Krastan B. Blagoev

Absence of Ostwald ripening has been observed in living cells, which operate out of equilibrium. Using molecular dynamics we study the behaviour of liquid droplets away from equilibrium in a system of particles interacting with each other via several central potential. The system is driven out of equilibrium either by the particles randomly transitioning bet

Chiara Lambranzi, Giulia Oberti, Christian Di Natali, Darwin G. Caldwell

Anchor point placement is a crucial yet often overlooked aspect of exosuit design since it determines how forces interact with the human body. This work analyzes the impact of different anchor point positions on gait kinematics, muscular activation and energetic consumption. A total of six experiments were conducted with 11 subjects wearing the XoSoft exosui

Min-Qi Li, Xin Liu, Zhi-Tian Zou, Ying Li

Motivated by the idea of fragmented scalar glueball, we investigate the decays $B^0 \to \eta_c f_0$ within the improved perturbative QCD (iPQCD) framework by including the known next-to-leading order corrections. Here, $B^0$ and $f_0$ denote the neutral $B_{d,s}^0$ mesons and the light scalar mesons $f_0(500, 980, 1370, 1500)$ under the $q\bar q$ assignment.

Alva West, Luodan Zhang, Liuliu Zhang, Minjun Zhu

Large language models (LLMs) have shown the capability to generate fluent and logical content, presenting significant challenges to machine-generated text detection, particularly text polished by adversarial perturbations such as paraphrasing. Current zero-shot detectors often employ Gaussian distributions as statistical measure for computing detection thres

Michael L. Li, Dingyu Shen, Jesus A. del Alamo, Martin Z. Bazant

Three-terminal electrochemical ionic synapses (EIoS) have recently attracted interest for in-memory computing applications. These devices utilize electrochemical ion intercalation to modulate the ion concentration in the channel material. The electrical conductance, which is concentration dependent, can be read separately and mapped to a non-volatile memory

Sobhan Asasi, Mohamed Ilyas Lakhal, Ozge Mercanoglu Sincan, Richard Bowden

Sign Language Translation (SLT) is a challenging task that requires bridging the modality gap between visual and linguistic information while capturing subtle variations in hand shapes and movements. To address these challenges, we introduce \textbf{BeyondGloss}, a novel gloss-free SLT framework that leverages the spatio-temporal reasoning capabilities of Vi

Khushi Mahajan, Chamkor Singh

We consider pattern formation in a sheared dense mixture of cohesive and non-cohesive grains. Our findings show that cohesive grains, which would typically form distributed agglomerates, instead segregate into percolating stripes or layers when the cohesive grain concentration ($c_o$) and cohesion strength ($C$) increase -- in a way that the average agglomer

Yuzhou Zhu

Dynamic streams from news feeds, social media, sensor networks, and financial markets challenge static RAG frameworks. Full-scale indices incur high memory costs; periodic rebuilds introduce latency that undermines data freshness; naive sampling sacrifices semantic coverage. We present Streaming RAG, a unified pipeline that combines multi-vector cosine scree

Frédéric Rousset, Changzhen Sun

We prove the linear and nonlinear asymptotic stability of small amplitude one-dimensional solitary waves submitted to small localized irrotational perturbations in the three dimensional Euler-Poisson system describing the dynamics of ions. In particular, in this regime, we obtain the existence of global smooth solutions and describe their asymptotic behavior

Nhut Truong, Uri Hasson

Topographic convolutional neural networks (TCNNs) are computational models that can simulate aspects of the brain's spatial and functional organization. However, it is unclear whether and how different types of topographic regularization shape robustness, representational structure, and functional organization during end-to-end training. We address this ques

Felix Wald, Amir Sajadi, Barry Mather, Giovanni De Carne

This paper presents an integration study for a power electronic-based fast-frequency response technology, an asynchronous grid connection operating as an aggregator for behindthe-meter resources and distributed generators. Both technical feasibility and techno-economic viability studies are presented. The dynamic performance of the fast-frequency response en

Maxime Pietrantoni, Gabriela Csurka, Torsten Sattler

Visual localization is the task of estimating a camera pose in a known environment. In this paper, we utilize 3D Gaussian Splatting (3DGS)-based representations for accurate and privacy-preserving visual localization. We propose Gaussian Splatting Feature Fields (GSFFs), a scene representation for visual localization that combines an explicit geometry model

Lars Torbjørn Stutzer

Stochastic thermodynamics is the field of study relating fluctuations in stochastic systems to thermodynamic quantities. The total entropy production (EP), is central to the thermodynamic classification of systems. Non-equilibrium systems manifestly all have non-zero EP and therefore impose an "arrow of time". Thermodynamic inequalities are lower bounds on t

Fernando Martínez-García, Álvaro Rubio-García, Samuel Fernández-Lorenzo, Juan José García-Ripoll

We introduce SA-FDR, a novel algorithm for $\ell_0$-norm feature selection that considers this task as a combinatorial optimisation problem and solves it by using simulated annealing to perform a global search over the space of feature subsets. The optimisation is guided by the Fisher discriminant ratio, which we use as a computationally efficient proxy for

Yung-Hsu Yang, Luigi Piccinelli, Mattia Segu, Siyuan Li

Monocular 3D object detection is valuable for various applications such as robotics and AR/VR. Existing methods are confined to closed-set settings, where the training and testing sets consist of the same scenes and/or object categories. However, real-world applications often introduce new environments and novel object categories, posing a challenge to these

Marián Kolesár, Jaroslav Říha

Using a variety of experimental results and lattice QCD calculations of $\pi\pi$ scattering lengths, while employing dispersive representations of the amplitude based on Roy equations, we compute the subthreshold parameters of this process. We use Monte Carlo sampling to numerically model the probability distribution of the results based on all uncertainties

Botao Zhu, Xianbin Wang, Dusit Niyato

The effective completion of tasks in collaborative systems hinges on task-specific trust evaluations of potential devices for distributed collaboration. Due to independent operation of devices involved, dynamic evolution of their mutual relationships, and complex situation-related impact on trust evaluation, effectively assessing devices' trust for collabora

Putu Brahmanda Sudarsana, Jagmohan Singh, Anchal Sareen

This study investigates the effect of surface dimples on the unsteady aerodynamics of a National Advisory Committee for Aeronautics airfoil (NACA0012) at a chord-based Reynolds numbers of $Re_c = 5300$ and $10{,}000$ using direct numerical simulations. Dimples were placed on the suction side at non-dimensional chordwise locations of $l_D/c = 0.035$ and $0.35

T. C. Vijayaraghavan

In this monograph, we study complexity classes that are defined using $O(\log n)$-space bounded non-deterministic Turing machines. We prove salient results of Computational Complexity in this topic such as the Immerman-Szelepcsenyi Theorem, the Isolating Lemma, theorems of Meena Mahajan and V. Vinay on the determinant and many consequences of these very impo

Sirine Arfa, Bernhard Vogginger, Christian Mayr

Spiking Neural Networks (SNNs) promise orders-of-magnitude lower power consumption and low-latency inference on neuromorphic hardware for a wide range of robotic tasks. In this work, we present an energy-efficient implementation of a reinforcement learning (RL) algorithm using quantized SNNs to solve two classical control tasks. The network is trained using