February 2025 arXiv papers — page 32

Milan Vojnovic, Se-Young Yun

In this note, we examine the aggregation of preferences achieved by the Group Policy Optimisation (GRPO) algorithm, a reinforcement learning method used to train advanced artificial intelligence models such as DeepSeek-R1-Zero and DeepSeekMath. The GRPO algorithm trains a policy using a reward preference model, which is computed by sampling a set of outputs

Ching-Chun Chang, Isao Echizen

Steganography is the art and science of covert writing, with a broad range of applications interwoven within the realm of cybersecurity. As artificial intelligence continues to evolve, its ability to synthesise realistic content emerges as a threat in the hands of cybercriminals who seek to manipulate and misrepresent the truth. Such synthetic content introd

Jianhao Yan, Yun Luo, Yue Zhang

In the multi-turn interaction schema, large language models (LLMs) can leverage user feedback to enhance the quality and relevance of their responses. However, evaluating an LLM's ability to incorporate user refutation feedback is crucial yet challenging. In this study, we introduce RefuteBench 2.0, which significantly extends the original RefuteBench by inc

Matteo Capoferri, Dmitri Vassiliev

The notion of eta invariant is traditionally defined by means of analytic continuation. We prove, by examining the particular case of the operator curl, that the eta invariant can equivalently be obtained as the trace of the difference of positive and negative spectral projections, appropriately regularised. Our construction is direct, in the sense that it d

Frederik G. Doktor, Niels M. Mikkelsen, Signe Kyrkjebø, Prashant Srivastava

We present a study the initial stages of ice growth on pristine and oxygen-functionalized highly oriented pyrolytic graphite (O-HOPG), combining low-temperature scanning tunneling microscopy (LT-STM) and machine-learning structural searches. LT-STM images show that oxygen atoms act as nucleation sites for ice growth, and that the size, structure and porosity

Adolfo Ruiz-Sanmartín, Vicent Ribas, David Suñol, Luis Chiscano-Camón

Background: The search for new biomarkers that allow an early diagnosis in sepsis has become a necessity in medicine. The objective of this study is to identify potential protein biomarkers of differential expression between sepsis and non-infectious systemic inflammatory response syndrome (NISIRS). Methods: Prospective observational study of a cohort of sep

Oscar W. Kennedy, Jared H. Cole, Connor D. Shelly

Building more powerful quantum computers requires manufacturing processes with tight tolerances. To improve the tolerances on Josephson junctions, techniques to fine tune their properties after fabrication have been developed. Understanding how tuning techniques may physically modify the tunnel barrier of a Josephson junction is important and will enable the

David Soler, Carlos Dafonte, Manuel Fernández-Veiga, Ana Fernández Vilas

Messaging Layer Security (MLS) and its underlying Continuous Group Key Agreement (CGKA) protocol allows a group of users to share a cryptographic secret in a dynamic manner, such that the secret is modified in member insertions and deletions. One of the most relevant contributions of MLS is its efficiency, as its communication cost scales logarithmically wit

Pengzhi Li, Pengfei Yu, Zide Liu, Wei He

In this paper, we introduce LDGen, a novel method for integrating large language models (LLMs) into existing text-to-image diffusion models while minimizing computational demands. Traditional text encoders, such as CLIP and T5, exhibit limitations in multilingual processing, hindering image generation across diverse languages. We address these challenges by

Xuechun Li, Susu Xu

Interferometric Synthetic Aperture Radar (InSAR) technology uses satellite radar to detect surface deformation patterns and monitor earthquake impacts on buildings. While vital for emergency response planning, extracting multi-class building damage classifications from InSAR data faces challenges: overlapping damage signatures with environmental noise, compu

Michael Hartz, Maximilian Tornes

A weighted composition operator on a reproducing kernel Hilbert space is given by a composition, followed by a multiplication. We study unitary and co-isometric weighted composition operators on unitarily invariant spaces on the Euclidean unit ball $\mathbb B_d$. We establish a dichotomy between the spaces $\mathcal{H}_\gamma$ with reproducing kernel $(1 - \

Wenlong Chen, Bolian Li, Ruqi Zhang, Yingzhen Li

Bayesian methods have shown success in deep learning applications. For example, in predictive tasks, Bayesian neural networks leverage Bayesian reasoning of model uncertainty to improve the reliability and uncertainty awareness of deep neural networks. In generative modeling domain, many widely used deep generative models, such as deep latent variable models

D. A. Kukusta, L. V. Bekenov, V. N. Antonov

We have investigated the electronic structure of Ba3InIr2O9 within the density-functional theory (DFT) using the generalized gradient approximation while considering strong Coulomb correlations (GGA+$U$) in the framework of the fully relativistic spin-polarized Dirac linear muffin-tin orbital band-structure method. We have investigated resonant inelastic x-r

Taha Ahmadi Pargo, Mohsen Akbarpour Shirazi, Dawud Fadai

Regarding problems like reduced precipitation and an increase in population, water resource scarcity has become one of the most critical problems in modern-day societies, as a consequence, there is a shortage of available water resources for irrigation in arid and semi-arid countries. On the other hand, it is possible to utilize modern technologies to contro

Zeju Li, Changran Xu, Zhengyuan Shi, Zedong Peng

This paper introduces DeepCircuitX, a comprehensive repository-level dataset designed to advance RTL (Register Transfer Level) code understanding, generation, and power-performance-area (PPA) analysis. Unlike existing datasets that are limited to either file-level RTL code or physical layout data, DeepCircuitX provides a holistic, multilevel resource that sp

James C. A. Main, Mickael Randour

We consider multi-dimensional payoff functions in partially observable Markov decision processes. We study the structure of the set of expected payoff vectors of all strategies (policies) and study what kind are needed to achieve a given expected payoff vector. In general, pure strategies (i.e., not resorting to randomisation) do not suffice for this problem

Chiara Esposito, Ryszard Nest, Jonas Schnitzer, Boris Tsygan

In this note, we provide a proof of the existence and complete classification of $G$-invariant star products with quantum momentum maps on Poisson manifolds by means of an equivariant version of the formality theorem.

Wenfeng Yang, Haozhi Sha, Jizhe Cui, Rong Yu

Size effects are ubiquitous in the structural, mechanical, and physical properties of materials, making it highly desirable to study the intrinsic properties of thick objects through high-resolution structural analysis in transmission electron microscopy. Although deep-sub-angstrom resolution has been achieved with multislice electron ptychography, the sampl

Taneesh Gupta, Rahul Madhavan, Xuchao Zhang, Chetan Bansal

Multi-preference optimization enriches language-model alignment beyond pairwise preferences by contrasting entire sets of helpful and undesired responses, thereby enabling richer training signals for large language models. During self-play alignment, these models often produce numerous candidate answers per query, rendering it computationally infeasible to i

Nuo Xu, Pinghui Wang, Zi Liang, Junzhou Zhao

Legal case retrieval (LCR) aims to automatically scour for comparable legal cases based on a given query, which is crucial for offering relevant precedents to support the judgment in intelligent legal systems. Due to similar goals, it is often associated with a similar case matching (LCM) task. To address them, a daunting challenge is assessing the uniquely

Zenghui Chang, Yiqiao Zhang, Hong Cai Chen

Graph similarity learning, crucial for tasks such as graph classification and similarity search, focuses on measuring the similarity between two graph-structured entities. The core challenge in this field is effectively managing the interactions between graphs. Traditional methods often entail separate, redundant computations for each graph pair, leading to

Zhaoyi Liu, Huan Zhang

Self-supervised learning (SSL) vision encoders learn high-quality image representations and thus have become a vital part of developing vision modality of large vision language models (LVLMs). Due to the high cost of training such encoders, pre-trained encoders are widely shared and deployed into many LVLMs, which are security-critical or bear societal signi

Natalia P. Bondarenko

We consider a class of self-adjoint Sturm-Liouville problems with rational functions of the spectral parameter in the boundary conditions. The uniform stability for direct and inverse spectral problems is proved for the first time for Sturm-Liouville operator pencils with boundary conditions depending on the eigenparameter. Furthermore, we obtain stability e

Zheming Ye, Xiaodong Qi, Zhao Zhang, Cheqing Jin

With the widespread adoption of Zero-Knowledge Proof systems, particularly ZK-SNARK, the efficiency of proof generation, encompassing both the witness generation and proof computation phases, has become a significant concern. While substantial efforts have successfully accelerated proof computation, progress in optimizing witness generation remains limited,

D. Bazeia, M. A. Marques, R. Menezes

We study a class of scalar field models coupled to impurities in arbitrary spacetime dimensions. The system admits the introduction of a second-order tensor that can be forced to obey an equality, if a first-order differential equation is satisfied, compatible with the equation of motion when the potential engenders a very specific form. In the case of stati

Rossella Attanasi, Marta Zoppello, Gaetano Napoli

This study investigates the dynamics and controllability of a Purcell three-link microswimmer equipped with passive elastic torsional coils at its joints. By controlling the spontaneous curvature, we analyse the swimmers motion using both linear and weakly nonlinear approaches. Linear analysis reveals steady harmonic solutions for small-amplitude controls bu

Morteza Rohanian, Roya M. Hüppi, Farhad Nooralahzadeh, Noemi Dannecker

Capturing subtle speech disruptions across the psychosis spectrum is challenging because of the inherent variability in speech patterns. This variability reflects individual differences and the fluctuating nature of symptoms in both clinical and non-clinical populations. Accounting for uncertainty in speech data is essential for predicting symptom severity a

Zonghao Chen, Masha Naslidnyk, François-Xavier Briol

This paper considers the challenging computational task of estimating nested expectations. Existing algorithms, such as nested Monte Carlo or multilevel Monte Carlo, are known to be consistent but require a large number of samples at both inner and outer levels to converge. Instead, we propose a novel estimator consisting of nested kernel quadrature estimato

Alessandro Andrea Zecchi, Claudio Sanavio, Simona Perotto, Sauro Succi

The quantum simulation of classical fluids often involves the use of probabilistic algorithms that encode the result of the dynamics in the form of the amplitude of the selected quantum state. In most cases, however, the amplitude probability is too low to allow an efficient use of these algorithms, thereby hindering the practical viability of the quantum si

Shanshan Xu, T. Y. S. S Santosh, Yanai Elazar, Quirin Vogel

Recent works have shown that Large Language Models (LLMs) have a tendency to memorize patterns and biases present in their training data, raising important questions about how such memorized content influences model behavior. One such concern is the emergence of political bias in LLM outputs. In this paper, we investigate the extent to which LLMs' political

Kun Gao, Tiago F. T. Cerqueira, Antonio Sanna, Yue-Wen Fang

The theoretical maximum critical temperature ($T_c$) for conventional superconductors at ambient pressure remains a fundamental question in condensed matter physics. Through analysis of electron-phonon calculations for over 20,000 metals, we critically examine this question. We find that while hydride metals can exhibit maximum phonon frequencies of more tha

Ishan Koralege, Arthur S. de Sena, Nurul H. Mahmood, Farjam Karim

Reconfigurable intelligent surfaces (RISs) have emerged as a promising solution that can provide dynamic control over the propagation of electromagnetic waves. The RIS technology is envisioned as a key enabler of sixth-generation networks by offering the ability to adaptively manipulate signal propagation through the smart configuration of its phase shift co

Veit Wild, James Wu, Dino Sejdinovic, Jeremias Knoblauch

We propose a scalable inference algorithm for Bayes posteriors defined on a reproducing kernel Hilbert space (RKHS). Given a likelihood function and a Gaussian random element representing the prior, the corresponding Bayes posterior measure $\Pi_{\text{B}}$ can be obtained as the stationary distribution of an RKHS-valued Langevin diffusion. We approximate th

Bastiaan Cnossen, Tobias Lenz, Maxime Ramzi

Given an $\infty$-category $\mathcal{C}$ with pullbacks, its $(\infty,2)$-category $\mathbf{Span}(\mathcal{C})$ of spans has the universal property of freely adding right adjoints to morphisms in $\mathcal{C}$ satisfying a Beck--Chevalley condition. We show that this universal property is implemented by an $(\infty,2)$-categorical refinement of Barwick's \em

Chuanyang Zheng, Yihang Gao, Guoxuan Chen, Han Shi

The softmax function is crucial in Transformer attention, which normalizes each row of the attention scores with summation to one, achieving superior performances over other alternative functions. However, the softmax function can face a gradient vanishing issue when some elements of the attention scores approach extreme values, such as probabilities close t

Pinaki Mondal

We revisit the fundamental problem of assigning intersection multiplicities to subsets of solutions of (square) systems of polynomials. Severi [Ann. Mat. Pura Appl. 26 (4), 1947] suggested an intuitive dynamic solution to this problem which was later corrected and made rigorous by Lazarsfeld [Compos. Math. 43, 1981]. We consider an asymmetric variant of this

Adrian Bekasiewicz, Khadijeh Askaripour, Mariusz Dzwonkowski, Tom Dhaene

Design of antennas for contemporary applications presents a complex challenge that integrates cognitive-driven topology development with the meticulous adjustment of parameters through rigorous numerical optimization. Nevertheless, the process can be streamlined by emphasizing the automatic determination of structure geometry, potentially reducing the relian

Guoxin Wang, Minyu Gao, Shuai Yang, Ya Zhang

Large language models (LLMs), particularly those with reasoning capabilities, have rapidly advanced in recent years, demonstrating significant potential across a wide range of applications. However, their deployment in healthcare, especially in disease reasoning tasks, is hindered by the challenge of acquiring expert-level cognitive data. In this paper, we i

Ru Wang, Wei Huang, Selena Song, Haoyu Zhang

Generalization to novel compound tasks under distribution shift is important for deploying transformer-based language models (LMs). This work investigates Chain-of-Thought (CoT) reasoning as a means to enhance OOD generalization. Through controlled experiments across several compound tasks, we reveal three key insights: (1) While QA-trained models achieve ne

Valerio Faraoni, Andrea Giusti

The convergence of scalar-tensor gravity to general relativity, or the departure from it, are described in a new analogy with heat dissipation in a viscous fluid. This new thermal picture is applied to cosmology, shedding light on whether gravity deviates from general relativity early on and approaches it later in the cosmic history.

Mohamed Nedal, David M. Long, Catherine Cuddy, Lidia Van Driel-Gesztelyi

Solar flares and coronal mass ejections (CMEs) are manifestations of energy release in the solar atmosphere, which can be accompanied by dynamic mass motions and waves in the surrounding atmosphere. Here, we present observations of plasma moving in a helical trajectory along a set of coronal loops formed following the eruption of a CME on 2024 May 14. This h

Fabian Fuchs, Max Nendel

In this work, we provide conditions for nonlinear monotone semigroups on locally convex vector lattices to give rise to a generalized notion of viscosity solutions to a related nonlinear partial differential equation. The semigroup needs to satisfy a convexity estimate, so called $K$-convexity, w.r.t. another family of operators, defined on a potentially lar

Wiebke Bennecke, Thi Lan Dinh, Jan Philipp Bange, David Schmitt

Following electronic processes in molecules and materials at the level of the quantum mechanical electron wavefunction with angstrom-level spatial resolution and with full access to its femtosecond temporal dynamics is at the heart of ultrafast condensed matter physics. A breakthrough invention allowing experimental access to electron wavefunctions was the r

Pedro De La Torre Luque, Daniele Gaggero, Dario Grasso, Antonio Marinelli

The LHAASO collaboration has recently released the spectrum and the angular distribution of the $\gamma$-ray Galactic diffuse emission from 1 TeV to 1 PeV measured with the Kilometer-2 Array (KM2A) and Water Cherenkov Detector Array (WCDA). We show that these data are in remarkably good agreement with a set of models that assume the emission to be produced b

Weilin Zhang, Hongjian Li, Sunben Chiu, Pingzhi Yuan

In 1946, P. Erd\H{o}s and I. Niven proved that there are only finitely many positive integers $n$ for which one or more of the elementary symmetric functions of $1,1 / 2$, $\cdots, 1 / n$ are integers. In 2012, Y. Chen and M. Tang proved that if $n \geqslant 4$, then none of the elementary symmetric functions of $1,1 / 2, \cdots, 1 / n$ are integers. In this

Aryan Roy, Jim Pivarski

Uproot can read ROOT files directly in pure Python but cannot (yet) compute expressions in ROOT's TTreeFormula expression language. Despite its popularity, this language has only one implementation and no formal specification. In a package called "formulate," we defined the language's syntax in standard BNF and parse it with Lark, a fast and modern parsing t

Andreas Charalampopoulos, Dimitris Fotakis, Panagiotis Patsilinakos, Thanos Tolias

We consider online procurement auctions, where the agents arrive sequentially, in random order, and have private costs for their services. The buyer aims to maximize a monotone submodular value function for the subset of agents whose services are procured, subject to a budget constraint on their payments. We consider a posted-price setting where upon each ag

Gaurang Agrawal, Pritam Halder, Aditi Sen De

We explore the performance of the metrology scheme by employing a quantum time flip during encoding, a specific case of processes with indefinite time direction, which we refer to as indefinite time directed metrology (ITDM). In the case of single parameter estimation of a unitary, we demonstrate that our protocol can achieve Heisenberg scaling (1/N) with pr

Yu-Ning Wang, Xin-Chen Duan, Tian-Peng Tang, Ziwei Wang

We revisit constraints on sub-GeV dark matter (DM) annihilation via $s$-wave, $p$-wave, and resonance processes using current and future CMB data from Planck, FIRAS, and upcoming experiments such as LiteBIRD, CMB-S4, PRISTINE, and PIXIE. For $s$-wave annihilation, we provide updated limits for both $e^{+}e^{-}$ and $\pi\pi$ channels, with the profile likelih

Ingo Rehberg, Peter Blümler

Homogeneous magnetic fields can be generated through the strategic arrangement of permanent magnets. The Halbach array serves as a prominent example of an effective design following this principle. However, it is a two-dimensional approach because it is optimal when placing infinitely long magnets -- line dipoles -- on a circle. If shorter, more realistic ma

Hao Shen, Zhouhong Gu, Haokai Hong, Weili Han

The widespread adoption of Large Language Models (LLMs) has raised significant privacy concerns regarding the exposure of personally identifiable information (PII) in user prompts. To address this challenge, we propose a query-unrelated PII masking strategy and introduce PII-Bench, the first comprehensive evaluation framework for assessing privacy protection

Asahi Sato

Traditionally, the impact of minimum wages on employment has been studied, and it is generally believed to have a negative effect. Yet, some recent studies have shown that the impact of minimum wages on employment can sometimes be positive. In addition, certain recent proposals set a higher minimum wage than the wage earned by some high-productivity workers.

Xi-guang Wang, Guang-hua Guo, Jamal Berakdar, Hui Jing

Low energy excitations of a magnetically ordered system are spin waves with magnon being their excitation quanta. Magnons are demonstrated to be useful for data processing and communication. To achieve magnon transport across extended distances, it is essential to minimize magnonic dissipation which can be accomplished by material engineering to reduce intri

Tommaso Flaminio, Sara Ugolini

We provide a new foundational approach to the generalization of terms up to equational theories. We interpret generalization problems in a universal-algebraic setting making a key use of projective and exact algebras in the variety associated to the considered equational theory. We prove that the generality poset of a problem and its type (i.e., the cardinal

Zhiyuan Peng, Xin Yin, Gang Wang, Chenhao Ying

With its decentralization and immutability, blockchain has emerged as a trusted foundation for data management and querying. Because blockchain storage space is limited, large multimodal data files, such as videos, are often stored offline, leaving only lightweight metadata on the chain. While this hybrid storage approach enhances storage efficiency, it intr

Raphael Bennett-Tennenhaus, Isambard Goodbody, Janina C. Letz, Amit Shah

A tensor extriangulated category is an extriangulated category with a symmetric monoidal structure that is compatible with the extriangulated structure. To this end we define a notion of a biextriangulated functor $\mathcal{A} \times \mathcal{B} \to \mathcal{C}$, with compatibility conditions between the components. We have two versions of compatibility cond

Yu-Ming Yang, Xing-Jian Lv, Xiao-Jun Bi, Peng-Fei Yin

Lorentz invariance is a fundamental symmetry of spacetime and serves as the cornerstone of modern physics, supporting the constancy of the speed of light. A crucial implication of this principle is that no particle can propagate faster than this universal speed limit. In this study, we present a stringent neutrino-based test of Lorentz invariance, utilizing

Leoncio Jimenez, Yolanda Valdes, Jorge Vistoso, Germain Lacoste

Imperfect Knowledge Management (IKM) aids in managing imprecise, uncertain, or incomplete aspects of meaning. IKM acknowledges that an enterprise's knowledge is often imperfect, characterized by varying degrees of imprecision, uncertainty, or incompleteness. In this context, knowledge is viewed as an object described by attributes and values. Our focus is on

Shuai Mo, Shiwang Ma

We study the normalized solutions to the following Choquard equation \begin{equation*} \aligned &-\Delta u + \lambda u =\mu g(u) + \gamma (I_\alpha * |u|^{\frac{N+\alpha}{N}})|u|^{\frac{N+\alpha}{N}-2}u & \text{in\ \ } \mathbb{R}^N \endaligned \end{equation*} under the $L^2$-norm constraint $\|u\|_2=c$. Here $\gamma>0$, $ N\geq 1$, $\alpha\in(0,N)$, $I_{\alp

Chen Wang, Shichao Han, Shan Huang

Participants in online experiments often enroll over time, which can compromise sample representativeness due to temporal shifts in covariates. This issue is particularly critical in A/B tests, online controlled experiments extensively used to evaluate product updates, since these tests are cost-sensitive and typically short in duration. We propose a novel f

Weilin Zhang, Fengyuan Chen, Hongjian Li, Pingzhi Yuan

Let $b>1$ be an odd positive integer and $k, l \in \mathbb{N}$. In this paper, we show that every positive rational number can be written as $\varphi(m^{2})/(\varphi(n^{2}))^{b}$ and $\varphi(k(m^{2}-1))/\varphi(ln^{2})$, where $m, n\in \mathbb{N}$ and $\varphi$ is the Euler's totient function. At the end, some further results are discussed.

Ali Gholami, Tayyebeh Jahani-Nezhad, Kai Wan, Giuseppe Caire

Gradient coding is a distributed computing technique for computing gradient vectors over large datasets by outsourcing partial computations to multiple workers, typically connected directly to the server. In this work, we investigate gradient coding in a hierarchical setting, where intermediate nodes sit between the server and workers. This structure reduces

Stefan Deaconu

The question of existence of Ulrich bundles on nonsingular projective varieties is posed here in weaker terms: either to find a K-theoretic solution, or to find one in the derived category of the variety. We observe that if any motivic vector bundle is algebraic, there is always a solution in the Grothendieck group. Also, by considering the derived problem,

Mitchell Plyler, Min Chi

Counterfactual data augmentation (CDA) is a method for controlling information or biases in training datasets by generating a complementary dataset with typically opposing biases. Prior work often either relies on hand-crafted rules or algorithmic CDA methods which can leave unwanted information in the augmented dataset. In this work, we show iterative CDA (

Song Chen, Elmer Monteblanco, Benjamin Borie, Shimpei Ono

We have investigated electric field (E-field) induced modulation of perpendicular magnetic anisotropy (PMA) in both amorphous and crystalline W/CoFeB/MgO/HfO2 ultra-thin films. We find that in the amorphous state, the E-field effect is volatile and reversible, which is consistent with the conventional electrostatic effect through charge accumulation and depl

Pieter Thijs Eendebak, Önder Gül

Many architectures for quantum information processing rely on qubits dedicated for the readout of a larger quantum register. These ancilla readout qubits present a physical overhead not contributing to the computational resource. A common implementation in spin qubit architectures is the readout schemes based on Pauli exclusion of charges confined in a doubl

K. Bakke, C. Furtado

From the interaction of the permanent magnetic dipole moment of a neutral particle with an electric field inside a long non-conducting cylindrical shell of inner radius $r_{a}$ and outer radius $r_{b}$, we show that a geometric quantum phase stems from the missing electric charge per unit length. Thus, we discuss the possibility of existing Aharonov-Bohm-typ

Hannah Lehr, Igor Lesanovsky, Gabriele Perfetto

We study the one-dimensional Fermi gas subject to dissipative reactions. The dynamics is governed by the quantum master equation, where the Hamiltonian describes coherent motion of the particles, while dissipation accounts for irreversible reactions. For lattice one-dimensional fermionic systems, emergent critical behavior has been found in the dynamics in t

Gerardo Tapia-Otaegui, Jorge A. Solsona, Sebastian Gomez Jorge, Ana Susperregui

In this document, a nonlinear control law for a grid-tied converter is introduced. The converter topology consists of a voltage source inverter (VSI) linked to the grid through an inductive-capacitive second-order filter, its input being connected to a capacitive DC-link supplied by a renewable energy-based input power source. In order to achieve good perfor

M. Brienza, K. Rajpurohit, E. Churazov, I. Heywood

Nest200047 is a clear example of multiple radio bubbles from an Active Galactic Nucleus (AGN) in a galaxy group, featuring non-thermal filaments likely shaped by buoyancy, gas motions, and stabilized by magnetic fields. This study presents high-quality data obtained from uGMRT, MeerKAT, and VLA, alongside existing LOFAR data, to analyze the system's morpholo

Andreas Hofmann, Yorgos Stratakos, Leonidas Marantis, Vasileios Spanakis-Misirlis

This study proposes a 3D-printed, quad-ridged, dual-pol, flared horn antenna feeder to meet the demands of a modern radio-telescope. The research work presented in this paper involves both the theoretical and the customized / adapted mechanical design of the proposed horn antenna, as well as a description of the 3D-printing and coating process. A novel slott

Blaise Melly, Martina Pons

We propose a minimum distance estimation approach for quantile panel data models where unit effects may be correlated with covariates. This computationally efficient method involves two stages: first, computing quantile regression within each unit, then applying GMM to the first-stage fitted values. Our estimators apply to (i) classical panel data, tracking

Hongqi Min, Xinrui Li, Ruoguang Li, Yong Zeng

For the 6G wireless networks, achieving high-performance integrated localization and communication (ILAC) is critical to unlock the full potential of wireless networks. To simultaneously enhance localization and communication performance cost-effectively, this paper proposes sparse multiple-input multiple-output (MIMO) based ILAC with nested and co-prime spa

Saurabh Jha, Ameet Rahane, Laura Shwartz, Marc Palaci-Olgun

Modern applications are built as large, distributed systems spanning numerous modules, teams, and data centers. Despite robust engineering and recovery strategies, failures and performance issues remain inevitable, risking significant disruptions and affecting end users. Rapid and accurate root cause identification is therefore vital to ensure system reliabi

Jiarun Fu, Lizhong Ding, Hao Li, Pengqi Li

Although Chain-of-Thought (CoT) has achieved remarkable success in enhancing the reasoning ability of large language models (LLMs), the mechanism of CoT remains a ``black box''. Even if the correct answers can frequently be obtained, existing CoTs struggle to make the reasoning understandable to human. In this paper, we unveil and causalize CoT from a causal

Quentin Lampin, Louis-Adrien Dufrène, Guillaume Larue

This paper addresses the challenge of integrating semantic communication principles into operated networks, traditionally optimized based on network-centric metrics rather than application-specific needs. Operated networks strongly adhere to the principle of ``separation of concerns", which emphasizes a clear distinction between network operation and applica

Mihaela Cătălina Stoian, Eleonora Giunchiglia

Synthetic tabular data generation has traditionally been a challenging problem due to the high complexity of the underlying distributions that characterise this type of data. Despite recent advances in deep generative models (DGMs), existing methods often fail to produce realistic datapoints that are well-aligned with available background knowledge. In this

Kamran Behnia

In a growing list of insulators, experiments find that magnetic field induces a misalignment between the heat flux and the thermal gradient vectors. This phenomenon, known as the phonon thermal Hall effect, implies energy flow without entropy production along the orientation perpendicular to the temperature gradient. The experimentally-measured thermal Hall

Michael Damron, Wai-Kit Lam

For $a>0$ and $b \geq 0$, let $\mathbb{G}_{a,b}$ be the subgraph of $\mathbb{Z}^2$ induced by the vertices between the first coordinate axis and the graph of the function $f = f_{a,b}(u) = a \log (1+u) + b \log(1+\log(1+u))$, $u \geq 0$. It is known that for $a>0$, the critical value for Bernoulli percolation on $\mathbb{G}_f = \mathbb{G}_{a,b}$ is strictly

Luiz Eduardo Cotta Monteiro, Rafael Martinelli

Electric Location-Routing models (ELRP) can contribute to the effective planning of electric vehicles (EVs) fleets and charging infrastructure within EV logistic networks because it simultaneously combines routing and location decisions to find optimal solutions to the network design. This study introduces ELRP models that incorporate nonlinear charging proc

Mykola Kozlenko, Olena Zamikhovska, Leonid Zamikhovskyi

In recent years, more and more attention has been paid to the use of artificial neural networks (ANN) for diagnostics of gas pumping units (GPU). Usually, ANN training is carried out on models of GPU workflows, and generated sets of diagnostic data are used to simulate defect conditions. At the same time, the results obtained do not allow assessing the real

Satoshi Inagaki, Alireza Alikhani, Nassir Navab, Peter C. Issa

Several robotic frameworks have been recently developed to assist ophthalmic surgeons in performing complex vitreoretinal procedures such as subretinal injection of advanced therapeutics. These surgical robots show promising capabilities; however, most of them have to limit their working volume to achieve maximum accuracy. Moreover, the visible area seen thr

Mirsad Cosovic, Ognjen Kundacina, Muhamed Delalic, Armin Teskeredzic

Modern electric power systems have an increasingly complex structure due to rise in power demand and integration of diverse energy sources. Monitoring these large-scale systems, which relies on efficient state estimation, represents a challenging computational task and requires efficient simulation tools for power system steady-state analyses. Motivated by t

Xiaofeng Wang, Zhixin Zhang, Jinguang Zheng, Yiming Ai

Debt collection negotiations (DCN) are vital for managing non-performing loans (NPLs) and reducing creditor losses. Traditional methods are labor-intensive, while large language models (LLMs) offer promising automation potential. However, prior systems lacked dynamic negotiation and real-time decision-making capabilities. This paper explores LLMs in automati

Yachao Yuan, Xiao Tang, Yu Huang, Yingwen Wu

Tensor-valued data, increasingly common in distributed big data applications like autonomous driving and smart healthcare, poses unique challenges for privacy protection due to its multidimensional structure and the risk of losing critical structural information. Traditional local differential privacy methods, designed for scalars and matrices, are insuffici

Sayan Sarkar, Sunit Das, Amit Agarwal

The generation of pure spin current, spin angular momentum transport without charge flow, is crucial for developing energy-efficient spintronic devices with minimal Joule heating. Here, we introduce the intrinsic nonlinear pure spin Hall effect (NPSHE), where both linear and second-order charge Hall currents vanish. We show intrinsic second-order spin angula

Eduardo Aguilar, Bogdan Raducanu, Petia Radeva

A crucial requirement for machine learning algorithms is not only to perform well, but also to show robustness and adaptability when encountering novel scenarios. One way to achieve these characteristics is to endow the deep learning models with the ability to detect out-of-distribution (OOD) data, i.e. data that belong to distributions different from the on

Xiang Ye, Janet Van Niekerk, Håvard Rue

Advancements in computational power and methodologies have enabled research on massive datasets. However, tools for analyzing data with directional or periodic characteristics, such as wind directions and customers' arrival time in 24-hour clock, remain underdeveloped. While statisticians have proposed circular distributions for such analyses, significant ch

Lisa Nicklasson, Manolis C. Tsakiris

We study the algebraic matroid induced by the ideal of (r+1)-minors of a matrix of variables over a field. This is inherently connected to the bounded-rank matrix completion problem, in which the aim is to complete a partially observed rank r matrix. We give criteria that detect dependent sets in the matroid, we describe a family of bases of the matroid, and

Besat Kassaie, Frank Wm. Tompa

Improving data quality in unstructured documents is a long-standing challenge. Unstructured data, especially in textual form, inherently lacks defined semantics, which poses significant challenges for effective processing and for ensuring data quality. We propose leveraging information extraction algorithms to design, apply, and explain data cleaning process

He Wang, Tianyang Xu, Zhangyong Tang, Xiao-Jun Wu

Multi-modal tracking is essential in single-object tracking (SOT), as different sensor types contribute unique capabilities to overcome challenges caused by variations in object appearance. However, existing unified RGB-X trackers (X represents depth, event, or thermal modality) either rely on the task-specific training strategy for individual RGB-X image pa

Botao Ye, Sifei Liu, Xueting Li, Marc Pollefeys

Large diffusion models demonstrate remarkable zero-shot capabilities in novel view synthesis from a single image. However, these models often face challenges in maintaining consistency across novel and reference views. A crucial factor leading to this issue is the limited utilization of contextual information from reference views. Specifically, when there is

Bingke Zhu, Xiaoxiao Wang, Minghui Jia, Yihan Tao

Stellar flare events are critical observational samples for astronomical research; however, recorded flare events remain limited. Stellar flare forecasting can provide additional flare event samples to support research efforts. Despite this potential, no specialized models for stellar flare forecasting have been proposed to date. In this paper, we present ex

Pradipta Bandyopadhyay, Deepak Gothwal

In this article, we discuss a ball separation characterisation of asymptotically uniformly smooth (AUS) norms. We use this characterisation to prove the residuality of the set of equivalent AUS norms. We discuss similar residuality results for uniformly smooth norms and norms with uniform Mazur intersection property (UMIP).

ATLAS Collaboration

The mass of the top quark is measured using top-antitop-quark pair events with high transverse momentum top quarks. The dataset, collected with the ATLAS detector in proton--proton collisions at $\sqrt{s}=13$ TeV delivered by the Large Hadron Collider, corresponds to an integrated luminosity of 140 fb$^{-1}$. The analysis targets events in the lepton-plus-je

Samy Ouzerrout

Aligned audio corpora are fundamental to NLP technologies such as ASR and speech translation, yet they remain scarce for underrepresented languages, hindering their technological integration. This paper introduces a methodology for constructing LoReSpeech, a low-resource speech-to-speech translation corpus. Our approach begins with LoReASR, a sub-corpus of s

Tianyang Xu, Jiyong Rao, Xiaoning Song, Zhenhua Feng

General mammal pose estimation is an important and challenging task in computer vision, which is essential for understanding mammal behaviour in real-world applications. However, existing studies are at their preliminary research stage, which focus on addressing the problem for only a few specific mammal species. In principle, from specific to general mammal

Yi Li, Wai Ming Tai

The active regression problem of the single-index model is to solve $\min_x \lVert f(Ax)-b\rVert_p$, where $A$ is fully accessible and $b$ can only be accessed via entry queries, with the goal of minimizing the number of queries to the entries of $b$. When $f$ is Lipschitz, previous results only obtain constant-factor approximations. This work presents the f

Chenjia Zhu, Ziteng Wang, Shiying Xiong, Yaomin Zhao

Entangled vortex filaments are essential to turbulence, serving as coherent structures that govern nonlinear fluid dynamics and support the reconstruction of fluid fields to reveal statistical properties. This study introduces an quantum implicit representation of vortex filaments in turbulence, employing a level-set method that models the filaments as the i

Nicolas Bédaride, Valérie Berthé, Antoine Julien

This paper studies balance properties for billiard words. Billiard words generalize Sturmian words by coding trajectories in hypercubic billiards. In the setting of aperiodic order, they also provide the simplest examples of quasicrystals, as tilings of the line obtained via cut and project sets with a cubical canonical window. By construction, the number of