October 2025 arXiv papers — page 203

Filippo Rinaldi, Aniello Panariello, Giacomo Salici, Fengyuan Liu

When a new release of a foundation model is published, practitioners typically need to repeat fine-tuning, even if the same task was already tackled in the previous version. A promising alternative is to reuse the parameter changes (i.e., task vectors) that capture how a model adapts to a specific task. However, these vectors often fail to transfer across di

Giorgia Maroni, Eva Cabrera San Millan, Beatrice Campanella, Massimo Onor

Aims. Resistance to targeted therapies remains a major challenge in EGFR-mutant non-small cell lung cancer (NSCLC). Here, we describe a novel metabolic adaptation in osimertinib-resistant cells characterized by elevated acetate levels and activation of an unconventional pyruvate-acetaldehyde-acetate (PAA) shunt. Methods. Integrated transcriptomic, exometabol

Marc Garreta Basora, Mehmet Oguz Mulayim

Anomaly detection in 12-lead electrocardiograms (ECGs) is critical for identifying deviations associated with cardiovascular disease. This work presents a comparative analysis of three autoencoder-based architectures: convolutional autoencoder (CAE), variational autoencoder with bidirectional long short-term memory (VAE-BiLSTM), and VAE-BiLSTM with multi-hea

Jakub Skowronski, Axel Boeltzig

The ${}^{\mathsf{12}}\mathsf{C}(\mathsf{p},\gamma)$ reaction cross section is currently under investigation in the low-background environment of the Laboratory for Underground Nuclear Astrophysics (LUNA). It is being studied using different types of solid targets, and employing two complementary detection techniques: HPGe spectroscopy and activation counting

Joshua Krauß, Enrico Stein, Axel Pelster

Photon condensation was first experimentally realized in 2010 within a dye-filled microcavity at room temperature. Since then, interest in the field has increased significantly, as a photon Bose-Einstein condensate (BEC) represents a prototypical driven-dissipative system. Here, we investigate how its inherent open nature influences the condensation process

Philippe Lamy, Yannick Boursier, Jean Loirat, Andrei Zhukov

We report on the characterization of a coronal mass ejection (CME) observed on 22 October 2003 by the LASCO-C2 and C3 coronagraphs over a time interval of 6 hours. This CME clearly appears as an asymmetric flux-rope in self-similar expansion and in spite of having a single vantage point, this relatively simple morphology and the geometry of the observations

Eduardo Camps-Moreno, Deblina Dey, Souvik Dey, Tai Huy Ha

We investigate the analytic spread of binomial edge ideals of finite simple graphs. We provide tight bounds for this invariant in general. For special families of graphs (e.g., closed graphs, pseudo-forests), we compute the exact value for the analytic spread of the corresponding binomial edge ideals via combinatorial and convex geometric means.

Vassilis G. Papanicolaou

We propose a discrete two-dimensional mathematical model for forest fires and we derive certain results describing its limiting behavior. We also pose a relevant open question.

Bruce Allen, Arian L. von Blanckenburg, Ken D. Olum

We use Legendre polynomials, previously employed in this context by Lee et al., van Haasteren and Levin, and Pitrou and Cusin, to model signals in pulsar timing arrays. These replace the (Fourier mode) basis of trigonometric functions normally used for data analysis. The Legendre basis makes it simpler to incorporate pulsar modeling effects, which remove con

S. Thatikonda, F. N. De Oliveira-Lopes, A. Mustonen, K. Pommois

We investigate the nonlinear evolution of the lower hybrid drift instability (LHDI) in reconnecting current sheets using a hybrid kinetic simulation model implemented in the Super Simple Vlasov (ssV) code. The model treats ions kinetically and electrons with a drift-kinetic approximation, solving self-consistent coupled electrostatic and electromagnetic fiel

Jannik Schestag

Phylogenetic trees represent certain species and their likely ancestors. In such a tree, present-day species are leaves and an edge from u to v indicates that u is an ancestor of v. Weights on these edges indicate the phylogenetic distance. The phylogenetic diversity (PD) of a set of species A is the total weight of edges that are on any path between the roo

F. Avitabile, F. Colangelo, M. Yu. Mikhailov, Z. Makhdoumi Kakhaki

The influence of the reactive DC sputtering parameters on the superconducting properties of NbReN ultrathin films was investigated. A detailed study of the current-voltage characteristics of the plasma was performed to optimize the superconducting critical temperature, Tc. The thickness dependence of Tc for the films deposited under different conditions was

Aksel Joonas Reedi, Corentin Léger, Julien Pourcel, Loris Gaven

Large Language Models (LLMs) optimized to output truthful answers often overfit, producing brittle reasoning that fails to generalize. While persuasion-based optimization has shown promise in debate settings, it has not been systematically compared against mainstream truth-based approaches. We introduce DebateQD, a minimal Quality-Diversity (QD) evolutionary

Lei Wang, Mingwei Ma, Jiangxu Li, Liucheng Chen

The interplay between electronic and lattice degrees of freedom is fundamental to charge density wave (CDW) formation, yet the microscopic origin often remains elusive. Here, we investigate the transient optical response of the intermetallic compound BaFe2Al9 using polarization-resolved ultrafast optical spectroscopy. We identify a discontinuous sign reversa

Lingfei Zeng, Fengdi Che, Xuhan Huang, Fei Ye

Formal verification is the next frontier for ensuring the correctness of code generated by Large Language Models (LLMs). While methods that co-generate code and formal specifications in formal languages, like Dafny, can, in principle, prove alignment with user intent, progress is bottlenecked by specification quality evaluation. Current benchmarks rely on ma

Dmitrii Radivonchik, Yakov Kuzin, Anton Chizhov, Dmitriy Shcheka

In this paper, we discuss a novel technique for processing correlated subqueries in SQL. The core idea is to isolate the non-correlated part of the predicate and use it to reduce the number of evaluations of the correlated part. We begin by providing an overview of several classes of queries that may benefit from this technique. For each class, we propose a

Matan Seidel

Consider the free group algebra $K\left[F\right]$, where $F$ is a free group and $K$ a field. A well-order $\prec$ on $F$ is called an exposure order if words are greater than their proper prefixes. We show that every one-sided ideal $I$ in $K\left[F\right]$ admits a Schreier transversal, a basis, and a Gr\"obner basis -- each minimal in a natural sense with

Jie Lu, Ji-Ze Han, Jie-Dong Huang, Yang Qian

Systematic Rabi-amplitude and detuning errors remain important sources of infidelity in high-fidelity quantum gates. We develop a robust pulse-engineering scheme for non-adiabatic holonomic quantum computing in a three-level $Λ$-type qutrit, combining inverse engineering with time-dependent perturbative analysis. Pulse shaping eliminates the leading second-o

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

We report the first measurement of the semileptonic decay $D^+_s \rightarrow K^0\mu^+\nu_{\mu}$, using a sample of $e^+e^-$ annihilation data corresponding to an integrated luminosity of $7.33~\mathrm{fb}^{-1}$ collected at center-of-mass energies between 4.128 to 4.226~GeV with the BESIII detector at the BEPCII collider. The branching fraction of the decay

Sebastian Höfer, Dorian Henning, Artemij Amiranashvili, Douglas Morrison

We present a novel large-scale dataset for defect detection in a logistics setting. Recent work on industrial anomaly detection has primarily focused on manufacturing scenarios with highly controlled poses and a limited number of object categories. Existing benchmarks like MVTec-AD [6] and VisA [33] have reached saturation, with state-of-the-art methods achi

Amalan Mahendran, Helen Thompson, James M. McGree

Subsampling is a computationally efficient and scalable method to draw inference in large data settings based on a subset of the data rather than needing to consider the whole dataset. When employing subsampling techniques, a crucial consideration is how to select an informative subset based on the queries posed by the data analyst. A recently proposed metho

Martin Benfeghoul, Teresa Delgado, Adnan Oomerjee, Haitham Bou Ammar

Transformers' quadratic computational complexity limits their scalability despite remarkable performance. While linear attention reduces this to linear complexity, pre-training such models from scratch remains, in most cases, prohibitively expensive. Recent post-training linearisation methods convert pre-trained Transformers to linear models efficiently, oft

Zhaoqilin Yang, Chanchan Li, Tianqi Liu, Hongxin Zhao

Inspired by the principle of self-regulating cooperation in collective institutions, we propose the Group Relative Policy Optimization with Global Cooperation Constraint (GRPO-GCC) framework. This work is the first to introduce GRPO into spatial public goods games, establishing a new deep reinforcement learning baseline for structured populations. GRPO-GCC i

Wenhao Li, Selvakumar Manickam, Yung-Wey Chong, Shankar Karuppayah

Phishing websites remain a persistent cybersecurity threat by mimicking legitimate sites to steal sensitive user information. Existing machine learning-based detection methods often rely on supervised learning with labeled data, which not only incurs substantial annotation costs but also limits adaptability to novel attack patterns. To address these challeng

Jiesi Hu, Yanwu Yang, Zhiyu Ye, Jinyan Zhou

Universal models for medical image segmentation, such as interactive and in-context learning (ICL) models, offer strong generalization but require extensive annotations. Interactive models need repeated user prompts for each image, while ICL relies on dense, pixel-level labels. To address this, we propose Weakly Supervised In-Context Learning (WS-ICL), a new

Jean-Pierre Magnot

We develop a framework for Poisson geometry on loop spaces of low regularity, extending Mokhov's classical constructions from smooth loops to weak Sobolev spaces $W^{s,p}(\mathbb{S^1},\mathbb{R}^m)$ with $o < s \frac{1}{2}$ and $1 < p < \infty.$ Within this setting we construct presymplectic and Poisson structures of hydrodynamic type, as well as their weakl

Sergi Julià-Farré, Antoine Michel, Christophe Domain, Joseph Mikael

We experimentally study the two-dimensional Fermi-Hubbard model using a Rydberg-based quantum processing unit in the analog mode. Our approach avoids encoding directly the original fermions into qubits and instead relies on reformulating the original model onto a system of fermions coupled to spins and then decoupling them in a self-consistent manner. We the

Mikkel Abrahamsen, Sujoy Bhore, Maike Buchin, Jacobus Conradi

A fundamental problem in shape matching and geometric similarity is computing the maximum area overlap between two polygons under translation. For general simple polygons, the best-known algorithm runs in $O((nm)^2 \log(nm))$ time [Mount, Silverman, Wu 96], where $n$ and $m$ are the complexities of the input polygons. In a recent breakthrough, Chan and Hair

Felipe Arenas-Uribe, T. Michael Seigler, Jesse B. Hoagg

Soft landing on small celestial bodies (SCBs) poses unique challenges, as gravitational models poorly characterize the higher-order gravitational effects of SCBs. Existing control approaches lack guarantees for safety under gravitational uncertainty. This paper proposes a three-stage control architecture that combines disturbance estimation, trajectory track

Jeremy C. Kirn, Lucas Meijer, Tillmann Miltzow, Hans L. Bodlaender

We investigate machine models similar to Turing machines that are augmented with the operations of a first-order structure $\mathcal{R}$, and we show that under weak conditions on $\mathcal{R}$, the complexity class $Σ_k \mathcal{R}$ may be characterized in four equivalent ways: (1) by polynomial-time algorithms implemented on $\mathcal{R}$-machines together

Jacob Fox, Janos Pach, Andrew Suk

A graph is said to contain $K_k$ (a clique of size $k$) as a weak immersion if it has $k$ vertices, pairwise connected by edge-disjoint paths. In 1989, Lescure and Meyniel made the following conjecture related to Hadwiger's conjecture: Every graph of chromatic number $k$ contains $K_k$ as a weak immersion. We prove this conjecture for graphs with at most $(1

Dennis Müller, Maurice Chiodo

This paper identifies several different interconnected challenges preventing the move towards more ethical and sustainable mathematics education: the entrenched belief in mathematical neutrality, the difficulty of simultaneously reforming mathematics and its pedagogy, the gap between academic theory and classroom practice, and the need for epistemic decoloni

Yanran Zhang, Bingyao Yu, Yu Zheng, Wenzhao Zheng

The emergence of visual autoregressive (AR) models has revolutionized image generation while presenting new challenges for synthetic image detection. Unlike previous GAN or diffusion-based methods, AR models generate images through discrete token prediction, exhibiting both marked improvements in image synthesis quality and unique characteristics in their ve

Srinivasan Arunachalam, Arkopal Dutt

We consider the task of learning a structured stabilizer decomposition of an arbitrary $n$-qubit quantum state $|\psi\rangle$: for $\epsilon > 0$, output a state $|\phi\rangle$ with stabilizer-rank $\textsf{poly}(1/\epsilon)$ such that $|\psi\rangle=|\phi\rangle+|\phi'\rangle$ where $|\phi'\rangle$ has stabilizer fidelity $< \epsilon$. We first show the exis

Ihsan Caha, Aqrab ul Ahmad, Francis Leonard Deepak

Integrating monolayers derived from 2D van der Waals (vdW) magnetic materials into next-generation technological applications remains a significant challenge due to their structural and magnetic instability issues. Template-assisted encapsulation is a potential route for the growth of stable 2D monolayers aimed at designing novel 1D heterostructures, opening

Johannes Seiffarth, Keitaro Kasahara, Michelle Bund, Benita Lückel

Live-cell imaging (LCI) technology enables the detailed spatio-temporal characterization of living cells at the single-cell level, which is critical for advancing research in the life sciences, from biomedical applications to bioprocessing. High-throughput setups with tens to hundreds of parallel cell cultivations offer the potential for robust and reproduci

Alexis Montoison, François Pacaud, Michael Saunders, Sungho Shin

We present a GPU implementation of Algorithm NCL, an augmented Lagrangian method for solving large-scale and degenerate nonlinear programs. Although interior-point methods and sequential quadratic programming are widely used for solving nonlinear programs, the augmented Lagrangian method is known to offer superior robustness against constraint degeneracies a

Ralf Kaiser, Andreas Tilgner

In MHD dynamo theory well-known necessary criteria for dynamo action are formulated in terms of lower bounds either on the maximum modulus of the velocity field (Childress-type) or the maximum strain of the velocity field (Backus-type). We generalize these criteria for spherical dynamos by introducing a radially varying weight $f(r)$. The corresponding {\em

Maria Chiara de Simone, Manuela Campanelli, Lorenzo Ennoggi, Carlos O. Lousto

We report the first three-dimensional general relativistic magnetohydrodynamic simulation to follow, self-consistently in a dynamical spacetime, the magnetized gas around a misaligned-spin supermassive binary black hole, from late inspiral through merger to the gravitational-wave recoil of the remnant. The equal-mass binary, in a $\textit{hang-up kick}$ conf

Rinesh T., H. Srinivasan, V. K. Sharma, S. Mitra

In this study, we investigate the microscopic diffusion dynamics of choline chloride (ChCl) based deep eutectic solvents (DESs) to elucidate the influence of hydrogen bond donor (HBD) identity on the mobility of cholinium ions. The DES systems examined include ethaline, glyceline, and reline, comprising ChCl mixed with ethylene glycol, glycerol, and urea, re

Ping-Yi Chen, Chih-Pin Tan, Yi-Hsuan Yang

We propose the Segmented Full-Song Model (SFS) for symbolic full-song generation. The model accepts a user-provided song structure and an optional short seed segment that anchors the main idea around which the song is developed. By factorizing a song into segments and generating each one through selective attention to related segments, the model achieves hig

M. Klasen

We review the series of specific nCTEQ analyses of nuclear parton distribution functions (PDFs) published since 2020 and present preliminary results of a new global analysis. Building on a modern proton baseline without nuclear data and extending the kinematic range, it combines and updates the previous separate analyses that focused on Jefferson Lab neutral

Julia Moska, Oleksii Furman, Kacper Kozaczko, Szymon Leszkiewicz

GeoAI is evolving rapidly, fueled by diverse geospatial datasets like traffic patterns, environmental data, and crowdsourced OpenStreetMap (OSM) information. While sophisticated AI models are being developed, existing benchmarks are often concentrated on single tasks and restricted to a single modality. As such, progress in GeoAI is limited by the lack of a

Darja Smite, Franz Zieris, Lars-Ola Damm

The COVID-19 pandemic has permanently altered workplace structures, normalizing remote work. However, critical evidence highlights challenges with fully remote arrangements, particularly for software teams. This study investigates employee resignation patterns at Ericsson, a global developer of software-intensive systems, before, during, and after the pandem

J. Castel, S. Cebrián, T. Dafni, D. Díez-Ibáñez

We report on the successful implementation of an $^{37}$Ar calibration source in the TREX-DM detector, a high-pressure time projection chamber designed for low-mass dark matter searches. The $^{37}$Ar source was produced through fast neutron activation of CaO powder at the HiSPANoS facility of Centro Nacional de Aceleradores (CNA) in Spain, yielding $O(1)$ k

Abhimanyu Choudhury, Meena Mahajan

Quantified Conflict Driven Clause Leaning (QCDCL) is one of the main approaches to solving Quantified Boolean Formulas (QBF). Cube-learning is employed in this approach to ensure that true formulas can be verified. Dependency Schemes help to detect spurious dependencies that are implied by the variable ordering in the quantifier prefix of QBFs but are not es

Jiahao Mei, Xuenan Xu, Zeyu Xie, Zihao Zheng

Recent advances in text-to-music models have enabled coherent music generation from text prompts, yet fine-grained emotional control remains unresolved. We introduce LARA-Gen, a framework for continuous emotion control that aligns the internal hidden states with an external music understanding model through Latent Affective Representation Alignment (LARA), e

Philipp Dahlinger, Tai Hoang, Denis Blessing, Niklas Freymuth

Accurately simulating physics is crucial across scientific domains, with applications spanning from robotics to materials science. While traditional mesh-based simulations are precise, they are often computationally expensive and require knowledge of physical parameters, such as material properties. In contrast, data-driven approaches like Graph Network Simu

Venla Koikkalainen, Emilia Kilpua, Simon Good, Adnane Osmane

In this paper we use statistical complexity and information theory metrics to study structure within solar wind time series. We explore this using entropy-complexity and information planes, where the measure for entropy is formed using either permutation entropy or the degree distribution of a horizontal visibility graph (HVG). The entropy is then compared t

Kiyoto Nakamura, Joachim Ankerhold

Within a numerically exact simulation technique, the dissipative dynamics of a two-qubit architecture is considered in which each qubit couples to its individual noise source (reservoir). The goal is to reveal the role of subtle qubit-reservoir correlations including non-Markovian processes as a prerequisite to guide further improvements of quantum computing

Josefa Lia Stoisser, Lawrence Phillips, Aditya Misra, Tom A. Lamb

Synthetic chain-of-thought (CoT) traces are widely used to train large reasoning models (LRMs), improving generalization by providing step-level supervision. Yet most approaches require ground-truth labels to seed or filter these traces - an expensive bottleneck in domains like biology where wet-lab data are scarce. We propose a label-free alternative: uncer

Wadim Gerner

We prove a homogeneous, quantitative version of Ehrling's inequality for the function spaces $H^1(\Omega)\subset\subset L^2(\partial\Omega)$, $H^1(\Omega)\hookrightarrow L^2(\Omega)$ which reflects geometric properties of a given $C^{1,1}$-domain $\Omega\subset\mathbb{R}^n$. We use this result to derive quantitative homogeneous versions of Gaffney's inequali

Kun Sun, Rong Wang

In a recent study, Lu, Song, and Zhang (2025) (LSZ) propose that large language models (LLMs), when prompted in different languages, display culturally specific tendencies. They report that the two models (i.e., GPT and ERNIE) respond in more interdependent and holistic ways when prompted in Chinese, and more independent and analytic ways when prompted in En

Vivekananda Bal, Jackie M. Wolfrum, Paul W. Barone, Stacy L. Springs

Physicochemical characterization of materials is central to the field of science and engineering and is essential to design new/engineered materials with specific properties. Assays available for small-molecules, e.g., XRD, NMR, LC-MS, can't be applied to macromolecules easily. Thus, it is extremely challenging to characterize complex materials such as adeno

T. de Ara, B. Olivera, C. Sabater, C. Untiedt

Two factors contribute to the electrical capacitance between two electrodes: a classical contribution, stemming from the electric field, and a quantum contribution, governed by the Pauli exclusion principle, which increases the difficulty of adding charge to the electrodes. In metals, the high electronic Density of States (DOS) at the Fermi energy allows the

Lorenzo Baraldi, Zifan Zeng, Chongzhe Zhang, Aradhana Nayak

The rapid progress in embodied artificial intelligence has highlighted the necessity for more advanced and integrated models that can perceive, interpret, and predict environmental dynamics. In this context, World Models (WMs) have been introduced to provide embodied agents with the abilities to anticipate future environmental states and fill in knowledge ga

Francesco Caravelli, Jean-Charles Delvenne

We develop a Koopman operator framework for studying the {computational properties} of dynamical systems. Specifically, we show that the resolvent of the Koopman operator provides a natural abstraction of halting, yielding a ``Koopman halting problem that is recursively enumerable in general. For symbolic systems, such as those defined on Cantor space, this

Zecheng Tang, Baibei Ji, Juntao Li, Lijun Wu

Long-context models (LCMs) have demonstrated great potential in processing long sequences, facilitating many real-world applications. The success of LCMs can be attributed to their ability to locate implicit critical information within the context for further prediction. However, recent research reveals that LCMs are often susceptible to contextual noise, i.

Bo-Yao Lian, Nelson G. Chen

The Wald-Wolfowitz runs test can assess the correctness of a regression curve fitted to a data set with one independent parameter. The assessment is performed through examination of the residuals, where the signs of the residuals would appear randomly if the regression curve were correct. We propose extending the test to the case where multiple data points w

Mahmoud Elkhodr, Ergun Gide

Systems analysis students increasingly use Generative AI, yet current pedagogy lacks systematic approaches for teaching responsible AI orchestration that fosters critical thinking whilst meeting educational outcomes. Students risk accepting AI suggestions blindly or uncritically without assessing alignment with user needs or contextual appropriateness. SAGE

Hans-Christian von Bothmer

We extend the computation of the invariant $\eta(\omega,C,a)$ defined in arXiv:2409.01751 to special points on the line at infinity and show that, as in the affine case, its value is determined purely by the geometry of the integral curve C. By incorporating points at infinity, the invariant $\eta$ yields effective geometric criteria that certify Darboux int

Xue-Yong Fu, Elena Khasanova, Md Tahmid Rahman Laskar, Harsh Saini

Large language models (LLMs) have achieved impressive performance in text summarization, yet their performance often falls short when applied to specialized domains that differ from their original pre-training distribution. While fine-tuning can improve summarization quality, it typically relies on costly and scarce high-quality labeled data. In this work, w

Saghar Garayemi, Reza Ali Akbari Khoei, Sarah Friedrich

Missing data is a common challenge in observational studies. Another challenge stems from the observational nature of the study itself. Here, propensity score analysis can be used as a technique to replicate conditions similar to those found in clinical trials. With regard to the missing data, a majority of studies only analyze the complete cases, but this h

Egor Surkov, Dmitry Osin, Evgeny Burnaev, Egor Shvetsov

This paper studies forecasting of the future distribution of events in human action sequences, a task essential in domains like retail, finance, healthcare, and recommendation systems where the precise temporal order is often less critical than the set of outcomes. We challenge the dominant autoregressive paradigm and investigate whether explicitly modeling

Dmitrij Ševaev, Andrei Nomerotski, Peter Švihra, Keshav Sishodia

We present a novel application of the Timepix3 optical camera (Tpx3Cam) for investigating ultrafast dynamics in substrate-free nanoparticles at the Extreme Light Infrastructure European Research Infrastructure Consortium (ELI ERIC). The camera, integrated into an ion imaging system based on a micro-channel plate (MCP) and a fast P47 scintillator, enables ind

Paolo Fittipaldi

The problem of scheduling in quantum networks amounts to choosing which entanglement swapping operations to perform to better serve user demand. The choice can be carried out following a variety of criteria (e.g. ensuring all users are served equally vs. prioritizing specific critical applications, adopting heuristic or optimization-based algorithms...), req

Weibo Mao, Tadashi Takayanagi

We model the Hayden--Preskill (HP) information recovery protocol in 2d CFTs via local joining quenches. Euclidean path integrals with slits prepare the HP subsystems: the message $M$, its reference $N$, the Page-time black hole $B$, the early radiation $E$, and the late radiation $R$; the remaining black hole after emitting $R$ is denoted as $B'$. The single

F. Marcadon, A. Prša

The existence of a deficit of brown dwarfs (BDs) in close orbit around main-sequence stars is one of the most intriguing questions in stellar physics. This so-called BD desert may result from the transition between two different dominant formation processes occurring for different mass regimes. While the BD mass derived from radial-velocity measurements help

Riccardo Fosco Gramaccioni, Christian Marinoni, Fabrizio Frezza, Aurelio Uncini

Accurate simulation of wave propagation in complex acoustic materials is crucial for applications in sound design, noise control, and material engineering. Traditional numerical solvers, such as finite element methods, are computationally expensive, especially when dealing with large-scale or real-time scenarios. In this work, we introduce a dataset of 31,00

Pranav Chandarana, Sebastián V. Romero, Alejandro Gomez Cadavid, Anton Simen

We introduce hybrid sequential quantum computing (HSQC), a paradigm for combinatorial optimization that systematically integrates classical and quantum methods within a structured, stage-wise workflow. HSQC may involve an arbitrary sequence of classical and quantum processes, as long as the global result outperforms the standalone components. Our testbed beg

Gefei Cai, Haoyu Liu, Baojun Wu, Zijie Zhuang

Recently, Ang--Cai--Sun--Wu (2024) determined the three-point connectivity constant for two-dimensional critical percolation, confirming a prediction of Delfino and Viti (2010). In this paper, we address the analogous problem for planar critical $q$-state Potts spin clusters. We introduce a continuum three-point connectivity constant and compute it explicitl

Adhithyan Kalaivanan, Zheng Zhao, Jens Sjölund, Fredrik Lindsten

Guiding pretrained flow-based generative models for conditional generation or to produce samples with desired target properties enables solving diverse tasks without retraining on paired data. We present ESS-Flow, a gradient-free method that leverages the typically Gaussian prior of the source distribution in flow-based models to perform Bayesian inference d

Roberto Civino, Valerio Fedele

We classify small binary bibraces, using the correspondence with alternating algebras over the field F2, up to dimension eight, also determining their isomorphism classes. These finite-dimensional algebras, defined by an alternating bilinear multiplication and nilpotency of class two, can be represented by subspaces of skew-symmetric matrices, with classific

Angelica Pia Di Feola, Michael Ruzicka

For a given bounded domain $\Omega \subset \mathbb R^3$, with $C^2$ boundary, and a given instant of time $T>0$, we prove the existence of a global weak solution on $(0,T)$, which satisfies a maximum principle, to a parabolic $p$-Laplacian system with convective term without divergence constraint for any $p\in (1,2)$.

Young D. Kwon, Abhinav Mehrotra, Malcolm Chadwick, Alberto Gil Ramos

High-resolution (4K) image-to-image synthesis has become increasingly important for mobile applications. Existing diffusion models for image editing face significant challenges, in terms of memory and image quality, when deployed on resource-constrained devices. In this paper, we present MobilePicasso, a novel system that enables efficient image editing at h

Maxence Lasbordes, Sinoué Gad

The landscape of Large Language Models remains predominantly English-centric, resulting in a significant performance gap for other major languages, such as French, especially in the context of Small Language Models (SLMs). Existing multilingual models demonstrate considerably lower performance in French compared to English, and research on efficient adaptati

Stergios Amarantidis, Duncan Farrah, Nick Seymour, Mark Lacy

Accretion rates in radio galaxies are typically estimated from optical and total radio flux measurements, incorporating emission from the core, jets, and lobes. These estimates can be used to investigate the link between observed Active Galactic Nuclei (AGN) emission properties and the underlying accretion physics of their Super-Massive Black Holes (SMBHs).

Lonni Besançon

In this essay, I argue that, while visualization research does not seem to be directly at risk of being corrupted by the current massive wave of polluted research, certain visualization concepts are being used in fraudulent fashions and fields close to ours are being targeted. Worse, the society publishing our work is overwhelmed by thousands of questionable

Josef Hanuš, Marco Delbo, Petr Pokorný, Franck Marchis

We report a successful observation of a stellar occultation by asteroid (16583) Oersted, enabling a detailed physical characterization of its shape, spin state, and surface properties. Our goal is to determine the physical parameters of Oersted by combining multi-chord occultation timing, sparse optical photometry, and thermal infrared observations. Such ast

Najmeh Mirian

The generation of high-power radiation in the terahertz (THz) regime using free-electron lasers (FELs) is challenging due to strong diffraction and pronounced slippage effects. These constraints often limit the achievable pulse duration and peak power in conventional single-pass THz FEL configurations. In this work, we investigate an unseeded optical klystro

Lucia A. Popa

We study the left-right symmetric extension of the Standard Model (LRSM), featuring a TeV-scale right-handed (RH) gauge boson $W_R$ and three RH neutrinos. This setup naturally realises the type-II seesaw mechanism for active neutrino masses. We identify the conditions that yield sufficient entropy dilution to reconcile the keV sterile neutrino dark matter e

Zhi Liu, Xuyuan Hu, Xiao Han, Zhehao Dai

Accurate travel time estimation (TTE) plays a crucial role in intelligent transportation systems. However, it remains challenging due to heterogeneous data sources and complex traffic dynamics. Moreover, traditional approaches typically convert trajectory data into fixed-length representations. This overlooks the inherent variability of real-world motion pat

Hengyang Zhou, Yiwei Wei, Jian Yang, Zhenyu Zhang

Multimodal Misinformation Recognition has become an urgent task with the emergence of huge multimodal fake content on social media platforms. Previous studies mainly focus on complex feature extraction and fusion to learn discriminative information from multimodal content. However, in real-world applications, multimedia news may naturally lose some informati

Katie Clinch, John Haslegrave, Tony Huynh, Anthony Nixon

NAC-colourings of graphs correspond to flexible quasi-injective realisations in $\mathbb {R} ^2$. A special class of NAC-colourings are those that arise from stable cuts. We give sharp thresholds for the random graph to have no stable cut and to have no NAC-colouring via exact hitting-time results: with high probability, the random graph process gains both p

Liang Chen, Xueting Han, Qizhou Wang, Bo Han

Balancing exploration and exploitation remains a central challenge in reinforcement learning with verifiable rewards (RLVR) for large language models (LLMs). Current RLVR methods often overemphasize exploitation, leading to entropy collapse, diminished exploratory capacity, and ultimately limited performance gains. Although techniques that increase policy st

Ruyang Liu, Shangkun Sun, Haoran Tang, Ge Li

Long-form video understanding has always been a challenging problem due to the significant redundancy in both temporal and spatial contents. This challenge is further exacerbated by the limited context length of Multimodal Large Language Models (MLLMs). To address this issue, many previous works have attempted to extract key video information, where the "key

Md Khalid Hossain, Farook Rahaman

Recently, we proposed a novel charged wormhole spacetime based on Yoshiaki Sofue's exponential dark matter density profile, referred to as the Charged Galactic Wormhole. Our previous work explored the deflection of light and massive chargeless particles in this spacetime. Building upon this foundation, we now extend our study to investigate the deflection of

Moinuddin Muhammad Imtiaz Bhuiyan, Kazi Ekramul Hoque, Rakibul Islam, Md. Mahbubur Rahman Tusher

This study addresses the challenge of detecting code smells in large-scale software systems using machine learning (ML). Traditional detection methods often suffer from low accuracy and poor generalization across different datasets. To overcome these issues, we propose a machine learning-based model that automatically and accurately identifies code smells, o

Tony Lindeberg

This paper presents a framework for time-causal wavelet analysis. It targets real-time processing of temporal signals, where data from the future are not available. The study builds upon temporal scale-space theory, originating from a complete classification of temporal smoothing kernels that guarantee non-creation of new structures from finer to coarser tem

Yejun Jang

The proliferation of high-fidelity synthetic media, coupled with exploitable hardware vulnerabilities in conventional imaging pipelines, has precipitated a crisis of trust in digital content. Existing countermeasures, from post-hoc classifiers to software-based signing, fail to address the fundamental challenge of establishing an unbreakable link to reality

B. Sankar, Devottama Sen, Dibakar Sen

Humans navigate and understand complex visual environments by subconsciously quantifying what they see, a process known as visual enumeration. However, traditional studies using flat screens fail to capture the cognitive dynamics of this process over the large visual fields of real-world scenes. To address this gap, we developed an immersive virtual reality

Kerem Semiz

Accurately determining resonance frequencies and quality factors (Q) is crucial in accelerator physics and radiofrequency engineering, as these factors have direct impacts on system design, operational stability, and research results. The methods currently employed to facilitate resonance analysis are mostly manual, requiring operators and physicists to esti

Iva Bačić, Michael T. Schaub, Jürgen Kurths, Dirk Witthaut

Higher-order interactions fundamentally shape collective dynamics in oscillator networks. The topological Kuramoto model captures these effects by extending synchronization models to include interactions between cells of arbitrary dimension within simplicial and cell complexes. We introduce the topological nonlinear Kirchhoff conditions to characterize all p

Johnnatan Messias, Ayae Ide

Decentralized Autonomous Organizations (DAOs) aim to enable participatory governance, but in practice face challenges of voter apathy, concentration of voting power, and misaligned delegation. Existing delegation mechanisms often reinforce visibility biases, where a small set of highly ranked delegates accumulate disproportionate influence regardless of thei

Cristian Meo, Varun Sarathchandran, Avijit Majhi, Shao Hung

Predicting precipitation maps is a highly complex spatiotemporal modeling task, critical for mitigating the impacts of extreme weather events. Short-term precipitation forecasting, or nowcasting, requires models that are not only accurate but also computationally efficient for real-time applications. Current methods, such as token-based autoregressive models

Riccardo Fosco Gramaccioni, Christian Marinoni, Eleonora Grassucci, Giordano Cicchetti

In this work, we present FoleyGRAM, a novel approach to video-to-audio generation that emphasizes semantic conditioning through the use of aligned multimodal encoders. Building on prior advancements in video-to-audio generation, FoleyGRAM leverages the Gramian Representation Alignment Measure (GRAM) to align embeddings across video, text, and audio modalitie

Christian Marinoni, Riccardo Fosco Gramaccioni, Kazuki Shimada, Takashi Shibuya

Although audio generation has been widely studied over recent years, video-aligned audio generation still remains a relatively unexplored frontier. To address this gap, we introduce StereoSync, a novel and efficient model designed to generate audio that is both temporally synchronized with a reference video and spatially aligned with its visual context. More

Haoran Zhang, Shuanghao Bai, Wanqi Zhou, Yuedi Zhang

Robotic grasping is one of the most fundamental tasks in robotic manipulation, and grasp detection/generation has long been the subject of extensive research. Recently, language-driven grasp generation has emerged as a promising direction due to its practical interaction capabilities. However, most existing approaches either lack sufficient reasoning and gen

Pubudu L. Indrasiri, Bipasha Kashyap, Pubudu N. Pathirana

Biomedical signals provide insights into various conditions affecting the human body. Beyond diagnostic capabilities, these signals offer a deeper understanding of how specific organs respond to an individual's emotions and feelings. For instance, ECG data can reveal changes in heart rate variability linked to emotional arousal, stress levels, and autonomic

Giorgio Giannone, Guangxuan Xu, Nikhil Shivakumar Nayak, Rohan Mahesh Awhad

Inference-Time Scaling (ITS) improves language models by allocating more computation at generation time. Particle Filtering (PF) has emerged as a strong ITS method for complex mathematical reasoning tasks, but it is vulnerable when guided by process reward models, which often assign overconfident scores early in the reasoning process. This causes PF to suffe