March 2025 arXiv papers — page 60

Tim Gräfnitz

A conjecture by Corti, Filip and Petracci, inspired by mirror symmetry, states that smoothing types of affine Gorenstein toric 3-folds correspond to zero mutable Laurent polynomials. We propose a method to prove this conjecture via log crepant log resolutions constructed from compatible collections of divisorial extractions. For affine cones over weighted pr

Nikolaos Galatos, Simon Santschi

We provide an axiomatization for the variety generated by the $n$-periodic l-pregroup $\mathbf{F}_n(\mathbb{Z})$, for every $n \in \mathbb{Z}^+$, as well as for all possible joins of such varieties; the finite joins form an ideal in the subvariety lattice of l-pregroups and we describe fully its lattice structure. On the way, we characterize all finitely sub

Ting Li, Bin Wang

This article is concerned with a new filtered two-step variational integrator for solving the charged-particle dynamics in a mildly non-uniform moderate or strong magnetic field with a dimensionless parameter $\varepsilon$ inversely proportional to the strength of the magnetic field. In the case of a moderate magnetic field ($\varepsilon=1$), second-order er

Christopher Ummerle, Antonio Giganti, Sara Mandelli, Paolo Bestagini

Remote sensing plays a crucial role in monitoring Earth's ecosystems, yet satellite-derived data often suffer from limited spatial resolution, restricting their applicability in atmospheric modeling and climate research. In this work, we propose a deep learning-based Super-Resolution (SR) framework that leverages land cover information to enhance the spatial

Zi-Han Chen, Ming-Cheng Chen, Chao-Yang Lu, Jian-Wei Pan

Preparing high-fidelity logical magic states is crucial for fault-tolerant quantum computation. Among prior attempts to reduce the substantial cost of magic state preparation, magic state cultivation (MSC), a recently proposed protocol for preparing $\mathrm{T}$ states without magic state distillation, achieves state-of-the-art efficiency. Inspired by this w

Ye Feng, Jianfeng Lu

We study the solution theory of the whole-space static (elliptic) Hamilton-Jacobi-Bellman (HJB) equation in spectral Barron spaces. We prove that under the assumption that the coefficients involved are spectral Barron functions and the discount factor is sufficiently large, there exists a sequence of uniformly bounded spectral Barron functions that converges

Leonie Spitz, Takuya Nomoto, Shunsuke Kitou, Hironori Nakao

Configurational entropy can impact crystallization processes, tipping the scales between structures of nearly equal internal energy. Using alloyed single crystals of Gd2PdSi3 in the AlB2-type structure, we explore the formation of complex layer sequences made from alternating, two-dimensional triangular and honeycomb slabs. A four-period and an eight-period

Wen-Chen Chang, Marco Meyer-Conde, Jen-Chieh Peng, Stephane Platchkov

We consider the beam-charge asymmetry of the $J/\psi$ production cross sections in $\pi^-$- versus $\pi^+$-induced reactions on proton or nuclear targets. We show that the $J/\psi$ production cross section difference between $\pi^-$ and $\pi^+$ beams impinging on a proton target has a positive sign with a magnitude proportional to the product of pion's valen

Tong Chen, Yu Gao, Shijie Liu, Ying-nan Mao

This study investigates the constraints on ALPs parameters through the photon-ALP oscillation model, based on the high-energy photon propagation characteristics of the gamma-ray burst GRB 221009A. We briefly describe the Primakoff process and use it to derive the oscillation probability. Numerical simulations incorporate the GMF, IGMF, and EBL, utilizing the

Yaoyao Yun, Jianwen Xu

In recent years, sparse sampling techniques based on regression analysis have witnessed extensive applications in face recognition research. Presently, numerous sparse sampling models based on regression analysis have been explored by various researchers. Nevertheless, the recognition rates of the majority of these models would be significantly decreased whe

Gong-Yu Yao, Can-Min Deng

Fast Radio Bursts (FRBs) are intense, millisecond-duration radio transients that have recently been proposed to arise from coherent radiation mechanisms within the magnetosphere of neutron stars. Observations of repeating FRBs, including periodic activity and large variations in Faraday rotation measures, suggest that these bursts may have binary system orig

Jaime Cuadros Valle, Joe Lope Vicente

We study the local moduli space of Sasaki-Einstein metrics on links of invertible polynomials defining rational homology 7 -spheres. All these polynomials are either of cycle type or are given as Thom Sebastiani sums of a cycle block and another atomic block. We found that for polynomials of cycle type, the local moduli spaces of Sasaki-Einstein metrics are

Jin-Tao Jin, Yi Zhou

We develop a comprehensive Ginzburg-Landau theory describing triple-Q magnetic orders on hexagonal lattices, focusing on $O(N)$ models with $N=2$ and $N=3$. Through systematic analysis of symmetry-allowed terms in the free energy, we establish complete phase diagrams governed by competing interaction parameters. Our theory reveals distinct magnetic configura

Muzi Hong, Kyohei Mukaida, Tsutomu T. Yanagida

It is very much intriguing if the Planck scale $M_{\rm{Pl}}$ is not a fundamental parameter. The Brans-Dicke gravity is nothing but the theory where the Planck scale $M_{\rm{Pl}}$ is indeed an illusional parameter. The theory predicts a massless scalar boson whose exchanges between matters induce unwanted long range forces. We solve this problem imposing the

T. Z. Luan, Cheng Shang, H. Yi, J. L. Li

Quantum routers are essential elements of quantum networks, enabling coherent information transfer between distant nodes. While their behavior has been extensively studied under Markovian approximations, investigations in non-Markovian regimes remain limited. In this paper, we study a nonreciprocal quantum router embedded in non-Markovian environments, enabl

Zhen-Song Chen, Hong-Wei Ding, Xian-Jia Wang, Witold Pedrycz

Neural architecture search (NAS) provides a systematic framework for automating the design of neural network architectures, yet its widespread adoption is hindered by prohibitive computational requirements. Existing zero-cost proxy methods, while reducing search overhead, demonstrate inadequate performance in architecture ranking tasks, particularly for Tran

Pierre Bousseyroux, Tomas Espana, Matteo Smerlak

Bandeira et al. (2017) show that the eigenvalues of the Kendall correlation matrix of $n$ i.i.d. random vectors in $\mathbb{R}^p$ are asymptotically distributed like $1/3 + (2/3)Y_q$, where $Y_q$ has a Mar\v{c}enko-Pastur law with parameter $q=\lim(p/n)$ if $p, n\to\infty$ proportionately to one another. Here we show that another Mar\v{c}enko-Pastur law emer

D. V. Fursaev, E. A. Davydov, V. A. Tainov

When a gravitational shockwave hits a magnetar it creates perturbations of the magnetar magnetic field in a form of a transition radiation. We argue that this radiation can be a novel candidate to explain the origin of fast radio bursts (FRB). A unique feature of the transition radiation on the shockwaves is that normal components of its Maxwell strength `re

Jérôme Poineau

Let $X$ be an algebraic variety over $\mathbf{C}$. We define a canonical compactification $X^{\!\urcorner}$ of the complex analytic space $X(\mathbf{C})$ by adding a Berkovich space over a trivially valued field at the boundary. The construction is functorial with respect to proper morphisms and preserves many properties, such as normality, regularity, etc.

Taejin Jeong, Joohyeok Kim, Jaehoon Joo, Seong Jae Hwang

Glaucoma is a major cause of irreversible blindness, with significant diagnostic subjectivity. This inherent uncertainty, combined with the overconfidence of models optimized solely for accuracy can lead to fatal issues such as overdiagnosis or missing critical diseases. To ensure clinical trust, model calibration is essential for reliable predictions, yet s

Xingxing Zou, Wen Zhang, Nanxuan Zhao

This survey provides a comprehensive overview of the advancements in Artificial Intelligence in Graphic Design (AIGD), focusing on integrating AI techniques to support design interpretation and enhance the creative process. We categorize the field into two primary directions: perception tasks, which involve understanding and analyzing design elements, and ge

Haoran Wang, Jingwei Huang, Lu Yang, Tianchen Deng

3D Gaussian Splatting has shown remarkable capabilities in novel view rendering tasks and exhibits significant potential for multi-view optimization.However, the original 3D Gaussian Splatting lacks color representation for inputs in low-light environments. Simply using enhanced images as inputs would lead to issues with multi-view consistency, and current s

Florian Gebhard, Kevin Bauerbach, Örs Legeza

We provide solid evidence for the long-standing presumption that model Hamiltonians with short-range interactions faithfully reproduce the physics of the long-range Coulomb interaction in real materials. For this aim, we address a generic Hubbard model that captures the quantum phase transitions between metal, Mott insulator, and charge-density-wave insulato

Sankalp Jena, Gabriel D. Weymouth, Artur K. Lidtke, Andrea Coraddu

Surrogate models are essential for fast and accurate surface pressure and friction predictions during design optimization of complex lifting surfaces. This study focuses on predicting pressure distribution over two-dimensional airfoils using graph neural networks (GNNs), leveraging their ability to process non-parametric geometries. We introduce boundary gra

Jessica Szczuka, Lisa Mühl, Paula Ebner, Simon Dubé

Large language models (LLMs), like ChatGPT, are capable of computing affectionately nuanced text that therefore can shape online interactions, including dating. This study explores how individuals experience closeness and romantic interest in dating profiles, depending on whether they believe the profiles are human- or AI-generated. In a matchmaking scenario

Nina Shvetsova, Arsha Nagrani, Bernt Schiele, Hilde Kuehne

We propose a new "Unbiased through Textual Description (UTD)" video benchmark based on unbiased subsets of existing video classification and retrieval datasets to enable a more robust assessment of video understanding capabilities. Namely, we tackle the problem that current video benchmarks may suffer from different representation biases, e.g., object bias o

V. V. Braguta, M. N. Chernodub, A. A. Roenko

We study the effect of finite spin quark density on the chiral and deconfinement thermal crossovers using numerical simulations of lattice QCD with two dynamical light quarks. The finite spin density is introduced by the quark spin potential in the canonical formulation of the spin operator. We show that both chiral and deconfinement temperatures are decreas

Peter Arzt, Sebastian Kreutzer, Tim Jammer, Christian Bischof

Teaching performance engineering in high-performance computing (HPC) requires example codes that demonstrate bottlenecks and enable hands-on optimization. However, existing HPC applications and proxy apps often lack the balance of simplicity, transparency, and optimization potential needed for effective teaching. To address this, we developed cfdSCOPE, a com

Hui Li, Congcong Bian, Zeyang Zhang, Xiaoning Song

Image fusion is a crucial technique in the field of computer vision, and its goal is to generate high-quality fused images and improve the performance of downstream tasks. However, existing fusion methods struggle to balance these two factors. Achieving high quality in fused images may result in lower performance in downstream visual tasks, and vice versa. T

Sebastián A. Cajas Ordóñez, Jaydeep Samanta, Andrés L. Suárez-Cetrulo, Ricardo Simón Carbajo

The Internet of Things is an example domain where data is perpetually generated in ever-increasing quantities, reflecting the proliferation of connected devices and the formation of continuous data streams over time. Consequently, the demand for ad-hoc, cost-effective machine learning solutions must adapt to this evolving data influx. This study tackles the

Abdolreza Amiri

This study investigates the efficiency and reliability of the modified Shardlow's (M-Shardlow) method for dissipative particle dynamics (DPD). We show that the M-Shardlow method in which for its construction, the second order velocity Verlet method in the Shardlows method to integrate the Hamiltonian part has been replaced by a symplectic fourth order method

Max Hirschberger, Satoru Hayami, Yoshinori Tokura

Skyrmion formation in centrosymmetric magnets without Dzyaloshinskii-Moriya interactions was originally predicted from unbiased numerical techniques. However, no attempt has yet been made, by comparison to a real material, to determine the salient interaction terms and model parameters driving spin-vortex formation. We identify a Hamiltonian with anisotropic

Kunyang Li, Ming Hou

Lane detection is critical for autonomous driving and ad-vanced driver assistance systems (ADAS). While recent methods like CLRNet achieve strong performance, they struggle under adverse con-ditions such as extreme weather, illumination changes, occlusions, and complex curves. We propose a Wavelet-Enhanced Feature Pyramid Net-work (WE-FPN) to address these c

Alexander Betz

In this article, we introduce the notion of a based action of a fusion category on an algebra. We will build some general theory to motivate our interest in based actions, and then apply this theory to understand based actions of fusion categories on path algebras. Our results demonstrate that a separable idempotent split based action of a fusion category $C

Arne Grobrügge, Niklas Kühl, Gerhard Satzger, Philipp Spitzer

Concept-based eXplainable AI (C-XAI) aims to overcome the limitations of traditional saliency maps by converting pixels into human-understandable concepts that are consistent across an entire dataset. A crucial aspect of C-XAI is completeness, which measures how well a set of concepts explains a model's decisions. Among C-XAI methods, Multi-Dimensional Conce

Yu-Ji Shi, Jun Zeng

We study the weak decays of the charmed baryon $\Omega_c^0$ to the $\Omega^-$ baryon within the framework of QCD sum rules. A three-point correlation function is defined for calculating eight form factors governing the $\Omega_c^0 \to \Omega^-$ transition. The cutting rules are employed to extract the double imaginary parts of the correlation functions, enab

Bing Cao, Baoshuo Cai, Changqing Zhang, Qinghua Hu

Image fusion integrates complementary information from multi-source images to generate more informative results. Recently, the diffusion model, which demonstrates unprecedented generative potential, has been explored in image fusion. However, these approaches typically incorporate predefined multimodal guidance into diffusion, failing to capture the dynamica

Junqiao Fan, Yunjiao Zhou, Min Chang Jordan Ren, Jianfei Yang

In this paper, we address the problem of generative dataset distillation that utilizes generative models to synthesize images. The generator may produce any number of images under a preserved evaluation time. In this work, we leverage the popular diffusion model as the generator to compute a surrogate dataset, boosted by a min-max loss to control the dataset

Xiaoping Li, Shiyang Sun, Qunying Liao, Xiang-Gen Xia

Recently, a multi-channel self-reset analog-to-digital converter (ADC) system with complex-valued moduli has been proposed. This system enables the recovery of high dynamic range complex-valued bandlimited signals at low sampling rates via the Chinese remainder theorem (CRT). In this paper, we investigate complex-valued CRT (C-CRT) with erroneous remainders,

Fu Chen, Qinglin Zhao, Li Feng, Longfei Tang

Self-attention has revolutionized classical machine learning, yet existing quantum self-attention models underutilize quantum states' potential due to oversimplified or incomplete mechanisms. To address this limitation, we introduce the Quantum Complex-Valued Self-Attention Model (QCSAM), the first framework to leverage complex-valued similarities, which cap

Noriaki Kawaguchi

For continuous self-maps of compact metric spaces, we explore the relationship among the shadowable points, sensitive points, and entropy points. Specifically, we show that (1) if the set of shadowable points is dense in the phase space, then a point located in the interior of the set of sensitive points is an entropy point; and (2) if the topological entrop

Deepayan Das, Davide Talon, Yiming Wang, Massimiliano Mancini

Vision Language Models (VLMs) have lead to major improvements in multimodal reasoning, yet they still struggle to understand user-specific concepts. Existing personalization methods address this limitation but heavily rely on training procedures, that can be either costly or unpleasant to individual users. We depart from existing work, and for the first time

Leon Bollmann

We consider a regularised Fermi projection of the Hamiltonian of the massless Dirac equation at Fermi energy zero. The matrix-valued symbol of the resulting operator is discontinuous in the origin. For this operator, we prove Szeg\H{o}-type asymptotics with the spatial cut-off domains given by $d$-dimensional cubes. For analytic test functions, we obtain a $

V. Bartolini, D. Dallacasa, J. L. Gómez, M. Giroletti

Relativistic jets originating at the center of AGN are embedded in extreme environments with strong magnetic fields and high particle densities, which makes them a fundamental tool for studying the physics of magnetized plasmas. We aim to investigate the magnetic field structure and the pc/sub-pc properties of the relativistic jet in the radio galaxy 3C111.

BESIII Collaboration, M. Ablikim, M. N. Achasov, P. Adlarson

Using a dataset of $(27.12\pm 0.14)\times 10^{8}$ $\psi(3686)$ events collected by the BESIII detector operating at the BEPCII collider, we report the first observation of the decay $\psi(3686)\to\Sigma^{0}\bar{\Sigma}^{0}\omega$ with a statistical significance of 8.9$\sigma$. The measured branching fraction is $(1.24 \pm 0.16_{\textrm{stat}} \pm 0.11_{\text

Miles H. Currie, John Debes, Yasuhiro Hasegawa, Isabel Rebollido

In addition to planets and other small bodies, stellar systems will likely also host exozodiacal dust, or exozodi. This warm dust primarily resides in or near the habitable zone of a star, and scatters stellar light in visible to NIR wavelengths, possibly acting as a spatially inhomogeneous fog that can impede our ability to detect and characterize Earth-lik

Benjamin Knopp, Daniel Auras, Alexander C. Schütz, Dominik Endres

We investigated gaze direction during movement observation. The eye movement data were collected during an experiment, in which different models of movement production (based on movement primitives, MPs) were compared in a two alternatives forced choice task (2AFC). Participants observed side-by-side presentation of two naturalistic 3D-rendered human movemen

Zijun Jia, Jinsong Yu, Hongyu Long, Diyin Tang

Road rage, often triggered by emotional suppression and sudden outbursts, significantly threatens road safety by causing collisions and aggressive behavior. Speech emotion recognition technologies can mitigate this risk by identifying negative emotions early and issuing timely alerts. However, current SER methods, such as those based on hidden markov models

Tomasz Różański, Yuan-Sen Ting

Neural network-based emulators for the inference of stellar parameters and elemental abundances represent an increasingly popular methodology in modern spectroscopic surveys. However, these approaches are often constrained by their emulation precision and domain transfer capabilities. Greater generalizability has previously been achieved only with significan

Diego Dall'Alba, Michał Naskręt, Sabina Kaminska, Przemysław Korzeniowski

Robotic surgery is a rapidly developing field that can greatly benefit from the automation of surgical tasks. However, training techniques such as Reinforcement Learning (RL) require a high number of task repetitions, which are generally unsafe and impractical to perform on real surgical systems. This stresses the need for simulated surgical environments, wh

Michał Pawlikowski, Piotr Szewczak, Lyubomyr Zdomskyy

We consider products of sets of reals with a combinatorial structure based on scales parameterized by filters. This kind of sets were intensively investigated in products of spaces with combinatorial covering properties as Hurewicz, Scheepers, Menger and Rothberger. We will complete this picture with focusing on properties from the second row of the Scheeper

Y. Lin, P. Ossona de Mendez

In this work, we relate girth and path-degeneracy in classes with sub-exponential expansion, with explicit bounds for classes with polynomial expansion and proper minor-closed classes that are tight up to a constant factor (and tight up to second order terms if a classical conjecture on existence of $g$-cages is verified). As an application, we derive bounds

R. Kale, A. Botteon, D. Eckert, R. Santra

Diffuse synchrotron radio sources associated with the intra-cluster medium of galaxy clusters are of special interest at high redshifts to understand the magnetization and particle acceleration mechanisms. El Gordo (EG) is the most massive galaxy cluster at high redshift (0.87), hosts a radio halo and a double radio relic system. We aim to understand the rol

Yongshuai Liu, Xin Liu

Recent developments in deep reinforcement learning have been very successful in learning complex, previously intractable problems. Sample efficiency and local optimality, however, remain significant challenges. To address these challenges, novelty-driven exploration strategies have emerged and shown promising potential. Unfortunately, no single algorithm out

Duncan Adamson, Pamela Fleischmann, Annika Huch, Tore Koß

A subsequence of a word $w$ is a word $u$ such that $u = w[i_1] w[i_2] \cdots w[i_k]$, for some set of indices $1 \leq i_1 < i_2 < \dots < i_k \leq \vert w \vert$. A word $w$ is \emph{$k$-subsequence universal} over an alphabet $\Sigma$ if every word over $\Sigma$ up to length $k$ appears in $w$ as a subsequence. In this paper, we revisit the problem $k$-ESU

Jiawei Yao, Yijie Mao, Mingzhe Chen

Reconfigurable intelligent surface (RIS) has been recognized as a promising solution for enhancing localization accuracy. Traditional RIS-based localization methods typically rely on prior channel knowledge, beam scanning, and pilot-based assistance. These approaches often result in substantial energy and computational overhead, and require real-time coordin

Toby St Clere Smithe, Marco Perin

We introduce a new compositional framework for generalized variational inference, clarifying the different parts of a model, how they interact, and how they compose. We explain that both exact Bayesian inference and the loss functions typical of variational inference (such as variational free energy and its generalizations) satisfy chain rules akin to that o

Fan Zhang, Molin Li, Xiaoyu Chang, Kexue Fu

The use of motion capture in live dance performances has created an emerging discipline enabling dancers to play different avatars on the digital stage. Unlike classical workflows, avatars enable performers to act as different characters in customized narratives, but research has yet to address how movement, improvisation, and perception change when dancers

Liya Huang, Georgios Tzounas

This paper focuses on multirate time-domain simulations of power system models. It proposes a matrix pencil-based approach to evaluate the spurious numerical deformation introduced into power system dynamics by a given multirate integration scheme. Moreover, it considers the problem of multirate partitioning and discusses a strategy for allocating state and

Nimrod Bratspiess, Leo R. M. Maas, Eyal Heifetz

Fluids, subject to symmetry breaking by stratification support propagation of anisotropic internal waves - IWs. In the vertical plane, rays representing energy paths obey a non-specular reflection law, as their inclination is solely dictated by their frequency. Although satisfying the linear Poincare equation, in basins having sloping walls, ray dynamics exh

Hui Peng, Yu Yu

Fast radio bursts (FRBs), millisecond-duration radio transient events, possess the potential to serve as excellent cosmological probes. The FRB redshift distribution contains information about the FRB sources, providing key constraints on the types of engines. However, it is quite challenging to obtain the FRB redshifts due to the poor localization and the f

Jong Myoung Kim, Young-Jun Lee, Ho-Jin Choi, Sangkeun Jung

While Large Language Models have gained attention, many service developers still rely on embedding-based models due to practical constraints. In such cases, the quality of fine-tuning data directly impacts performance, and English datasets are often used as seed data for training non-English models. In this study, we propose LANGALIGN, which enhances target

A. Costa, G. Bodo, F. Tavecchio, P. Rossi

Recollimation is a phenomenon of particular importance in the dynamic evolution of jets and in the emission of high-energy radiation. Additionally, the full comprehension of this phenomenon provides insights into fundamental properties of jets in the vicinity of the Active Galactic Nucleus (AGN). Three-dimensional (magneto-)hydrodynamic simulations revealed

Hyelin Choi, Woocheol Choi

In this paper, we analyze the convergence rate of the Jacobi-Proximal Alternating Direction Method of Multipliers (ADMM) initially introduced by Deng et al. for the block-structured optimization problem with linear constraint. The algorithm is well-suited for parallel implementation and widely used for large-scale multi-block optimization problems. While the

Linda Fabiani, Sebastian J. Schlecht, Isabel Haasler, Filip Elvander

Separating sources is a common challenge in applications such as speech enhancement and telecommunications, where distinguishing between overlapping sounds helps reduce interference and improve signal quality. Additionally, in multichannel systems, correct calibration and synchronization are essential to separate and locate source signals accurately. This wo

Minsu Kim, Seongmin Hong, RyeoWook Ko, Soongyu Choi

Modern Large Language Model serving system batches multiple requests to achieve high throughput, while batching attention operations is challenging, rendering memory bandwidth a critical bottleneck. The community relies on high-end GPUs with multiple high-bandwidth memory channels. Unfortunately, HBM's high bandwidth often comes at the expense of limited mem

P. Skokowski, K. Synoradzki, M. Werwiński, A. Bajorek

A transformation between the magnetically ordered CeCoGe$_3$ and heavy fermion CeFeGe$_3$ is isostructural but not isoelectronic, therefore the characterization of the electronic structure of the CeCo$_{1-x}$Fe$_x$Ge$_3$ series is of special importance. We report both the experimental investigation by the X-ray photoelectron spectroscopy (XPS) measurements a

Michael Pradel

As software is evolving, code changes can introduce regression bugs or affect the behavior in other unintended ways. Traditional regression test generation is impractical for detecting unintended behavioral changes, because it reports all behavioral differences as potential regressions. However, most code changes are intended to change the behavior in some w

Yihan Wang, Peiyu Liu, Xin Yang

Schema linking is a critical bottleneck in applying existing Text-to-SQL models to real-world, large-scale, multi-database environments. Through error analysis, we identify two major challenges in schema linking: (1) Database Retrieval: accurately selecting the target database from a large schema pool, while effectively filtering out irrelevant ones; and (2)

Chengxiang Huang, Yake Wei, Zequn Yang, Di Hu

Sensory training during the early ages is vital for human development. Inspired by this cognitive phenomenon, we observe that the early training stage is also important for the multimodal learning process, where dataset information is rapidly acquired. We refer to this stage as the prime learning window. However, based on our observation, this prime learning

Guillem García Subies, Álvaro Barbero Jiménez, Paloma Martínez Fernández

We present a novel contribution to Spanish clinical natural language processing by introducing the largest publicly available clinical corpus, ClinText-SP, along with a state-of-the-art clinical encoder language model, RigoBERTa Clinical. Our corpus was meticulously curated from diverse open sources, including clinical cases from medical journals and annotat

Xu-Da Zhou, Si-Hong Zhou

Motivated by recent experimental advances in three-body hadronic $D$ decays from BESIII, we present a systematic analysis of $D_{(s)} \to P_1 (V \to) P_2 P_3 $ decay processes, where $V$ denotes vector resonances ($\rho, K^*, \omega$, $\phi$) and $P_{1,2,3}$ are light pseudoscalar mesons ($\pi,K, \eta^{(\prime)}$). Using the factorization-assisted topologica

Maria Panagiotou, Knut Stroemmen, Lorenzo Brigato, Bastiaan E. de Galan

The growing worldwide incidence of diabetes requires more effective approaches for managing blood glucose levels. Insulin delivery systems have advanced significantly, with artificial intelligence (AI) playing a key role in improving their precision and adaptability. AI algorithms, particularly those based on reinforcement learning, allow for personalised in

Zhong-Lv Huang, Xiao-Gang He

We investigate phenomenological implications of vector bosons $V$ transforming as (1, 2, -3/2) under the standard model (SM) product gauge group $SU(3)_C$, $SU(2)_L$ and $U(1)_Y$. These vector bosons can couple to two SM leptons at tree-level forming dimension-4 operators. These operators dictate $V$ to have two units of global lepton number, $\Delta L = 2$.

Luan Vinícius Fiorio, Bruno Defraene, Johan David, Alex Young

We propose a speaker selection mechanism (SSM) for the training of an end-to-end beamforming neural network, based on recent findings that a listener usually looks to the target speaker with a certain undershot angle. The mechanism allows the neural network model to learn toward which speaker to focus, during training, in a multi-speaker scenario, based on t

Guillem Capellera, Antonio Rubio, Luis Ferraz, Antonio Agudo

Multi-agent trajectory modeling has primarily focused on forecasting future states, often overlooking broader tasks like trajectory completion, which are crucial for real-world applications such as correcting tracking data. Existing methods also generally predict agents' states without offering any state-wise measure of uncertainty. Moreover, popular multi-m

Kangwei Liu, Junwu Liu, Yun Cao, Jinlin Guo

Recent advances in talking face generation have significantly improved facial animation synthesis. However, existing approaches face fundamental limitations: 3DMM-based methods maintain temporal consistency but lack fine-grained regional control, while Stable Diffusion-based methods enable spatial manipulation but suffer from temporal inconsistencies. The in

Neda Darvishi, Apostolos Pilaftsis

We present a new form of CP violation (CPV) that can be realised in Two-Higgs Doublet Models (2HDMs) and was studied recently in [1]. By examining the vacuum manifold of a generic (convex) 2HDM potential, we identify scenarios that exhibit Mixed Spontaneous and Explicit CP Violation (MCPV), in which at least two non-degenerate CP-violating local minima coexi

M. O. Toropov, S. A. Tyul'bashev, V. S. Beskin

An interpulse search was carried out in a sample of 96 pulsars observed on the Large Phased Array (LPA) radio telescope in the Pushchino Multibeams Pulsar Search (PUMPS). The pulsar sample is complete for pulsars having a signal-to-noise ratio (S/N) in the main pulse ($MP$) greater than 40. To search for weak interpulses ($IP$), the addition of average profi

Pierre Le Doussal, Gregory Schehr

We consider the classical Coulomb gas in two dimensions at the inverse temperature $\beta=2$, confined within a droplet of radius $R$ by a rotationally invariant potential $U(r)$. For $U(r)\sim r^2$ this describes the eigenvalues of the complex Ginibre ensemble of random matrices. We study linear statistics of the form ${\cal L}_N = \sum_{i=1}^N f(|{\bf x}_i

Reggie C. Pantig, Ali Övgün

This study explores novel static, neutral black hole solutions within Kalb-Ramond (KR) gravity in asymptotically (anti-)de Sitter [(A)dS] spacetimes, incorporating spontaneous Lorentz symmetry breaking (LSB) via an antisymmetric tensor field. Focusing on two metric configurations, we derive general analytical expressions for the horizon radius, photon sphere

Nilesh Kumar Sahu, Snehil Gupta, Haroon R Lone

Anxiety-provoking activities, such as public speaking, can trigger heightened anxiety responses in individuals with anxiety disorders. Recent research suggests that physiological signals, including electrocardiogram (ECG) and electrodermal activity (EDA), collected via wearable devices, can be used to detect anxiety in such contexts through machine learning

Zhiwei Shi, Chengxi Zhu, Fan Yang, Jun Yan

This paper presents a data driven universal ball trajectory prediction method integrated with physics equations. Existing methods are designed for specific ball types and struggle to generalize. This challenge arises from three key factors. First, learning-based models require large datasets but suffer from accuracy drops in unseen scenarios. Second, physics

Alexander Holmberg, Nils Mechtel, Wei Ouyang

We present a domain adaptation of video diffusion models to generate highly realistic time-lapse microscopy videos of cell division in HeLa cells. Although state-of-the-art generative video models have advanced significantly for natural videos, they remain underexplored in microscopy domains. To address this gap, we fine-tune a pretrained video diffusion mod

Victor H. Jorge-Pérez, Paulo Martins

Let $(R,\mathfrak{m},k)$ be a commutative Noetherian local ring. It is well-known that if $M$ is a finitely generated $R$-module of finite quasi-injective dimension, then $\operatorname{qid}_RM = \operatorname{depth} R$. In this paper, we demonstrate that under the weaker condition that $M$ is $\operatorname{Ext}$-finite and has finite quasi-injective dimens

Geunsu Choi, Helena del Río, Audrey Fovelle, Mingu Jung

We introduce a new class of bounded linear operators, called range strongly exposing (RSE) operators, which form a natural intermediate class: weaker than Bourgain's absolutely strongly exposing operators, yet stronger than both uniquely quasi norm-attaining and classical norm-attaining operators. Several foundational results on norm-attaining operators are

Talal Ahmed Chowdhury, Kwangmin Yu, Raza Sabbir Sufian

Quantum computers are expected to be vital for exploring complex dynamics in many-body quantum systems. Thus, validating established results on current quantum computers is essential for evaluating their future utility. Hence, we investigate the entanglement entropy of the Sachdev-Ye-Kitaev (SYK) model, a paradigmatic model of quantum chaos, many-body physic

Luan Vinícius Fiorio, Bruno Defraene, Johan David, Frans Widdershoven

We propose an unsupervised variational acoustic clustering model for clustering audio data in the time-frequency domain. The model leverages variational inference, extended to an autoencoder framework, with a Gaussian mixture model as a prior for the latent space. Specifically designed for audio applications, we introduce a convolutional-recurrent variationa

Stefano Pantaleone, Giulia De Gasperis, Marta Corno, Albert Rimola

The prebiotic history of phosphorus is a matter of debate in the scientific community: its origin, how it landed on Earth, the selective speciation of the phosphate, and its inclusion into the organic matrix are the main unsolved issues. In this regard, Schreibersite ((Fe,Ni)3P), a mineral present in iron meteorites, can play a fundamental role as a carrier

Tianyu Chen, Xingcheng Fu, Yisen Gao, Haodong Qian

Modern vision-language models (VLMs) develop patch embedding and convolution backbone within vector space, especially Euclidean ones, at the very founding. When expanding VLMs to a galaxy scale for understanding astronomical phenomena, the integration of spherical space for planetary orbits and hyperbolic spaces for black holes raises two formidable challeng

Peter Gracar, Marilyn Korfhage

We study the Poisson Boolean model with convex bodies which are rotation-invariant distributed. We assume that the convex bodies have regularly varying diameters with indices $-\alpha_1\geq \dots\geq-\alpha_d$ where $\alpha_k >0$ for all $k\in\{1,\dots,d\}.$ It is known that a sufficient condition for the robustness of the model, i.e. the union of the convex

Etienne Wamba, Jeremie Bai, A. Serge Tchakoutio Nguetcho

We investigate the dynamical instabilities of an ultracold Bose-Bose mixture with long-range dipole-dipole interactions, trapped in deep optical lattices and subject to periodically varying contact interaction. The effect of beyond-mean-field corrections due to quantum fluctuations is considered. In the tight-binding regime, we employ Wannier functions to de

Stanislav Semenov

Cantor's diagonal method is traditionally used to prove the uncountability of the set of all infinite binary sequences. This paper analyzes the expressive limits of this method. It is shown that under any constructive application -- including generalizations with computable permutations and infinite hierarchies of diagonal extensions -- the resulting set rem

Dazhao Tang

Let $\overline{B}_{s,t}(n)$ denote the number of overpartitions of $n$ where no part is divisible by $s$ or $t$, with $s$ and $t$ being coprime. By establishing the exact generating functions of a family of arithmetic progressions in $\overline{B}_{4,3}(n)$, we prove that for any $k\geq1$ and $n\geq1$, \begin{align*} \overline{B}_{4,3}\big(2^{k+3}n\big)\equi

Mikhail Bershtein

In these lecture notes, we give an introduction to cluster integrable systems. The topics include relativistic Toda systems, moduli spaces of framed local systems, Goncharov-Kenyon integrable systems, and quantization.

Prathyush Sambaturu, Bernardo Gutierrez, Moritz U. G. Kraemer

Understanding human mobility is essential for applications ranging from urban planning to public health. Traditional mobility models such as flow networks and colocation matrices capture only pairwise interactions between discrete locations, overlooking higher-order relationships among locations (i.e., mobility flow among two or more locations). To address t

Abhijith M S, Sandra S

The study proposes a data-driven model which combines the Dynamic Mode Decomposition with multi-linear interpolation to predict the thermal fields of nanofluid flows at unseen Reynolds numbers (Re) and particle volume concentrations ($\epsilon$). The flow, considered for the study, is laminar and incompressible. The study employs an in-house Fortran-based so

Tilahun Yeshambel, Moncef Garouani, Serge Molina, Josiane Mothe

This paper reports some difficulties and some results when using dense retrievers on Amharic, one of the low-resource languages spoken by 120 millions populations. The efforts put and difficulties faced by University Addis Ababa toward Amharic Information Retrieval will be developed during the presentation.

Hadi Mohammadi, Ehsan Nazerfard, Mostafa Haghir Chehreghani

Imbalanced data represent a distribution with more frequencies of one class (majority) than the other (minority). This phenomenon occurs across various domains, such as security, medical care and human activity. In imbalanced learning, classification algorithms are typically inclined to classify the majority class accurately, resulting in artificially high a

Mario J. Rincón, Martino Reclari, Xiang I. A. Yang, Mahdi Abkar

The integration of interpretability and generalisability in data-driven turbulence modelling remains a fundamental challenge for computational fluid dynamics applications. This study yields a generalisable advancement of the $k$-$\omega$ Shear Stress Transport (SST) model through a progressive data-augmented framework, combining Bayesian optimisation with ph