November 2025 arXiv papers — page 179

Grigory Kovalev, Natalia Loukachevitch, Mikhail Tikhomirov, Olga Babina

In this paper, we present a novel series of Russian information retrieval datasets constructed from the "Did you know..." section of Russian Wikipedia. Our datasets support a range of retrieval tasks, including fact-checking, retrieval-augmented generation, and full-document retrieval, by leveraging interesting facts and their referenced Wikipedia articles a

Mahid M. Mangontarum, Norlailah M. Madid, Asnawi A. Campong

In this paper, we established some integral formulas for and involving the noncentral Tanny-Dowling polynomials. These formulas are shown to be generalizations of some known results on the classical geometric polynomials.

Manan Sharma, Arya Suneesh, Manish Jain, Pawan Kumar Rajpoot

We address claim normalization for multilingual misinformation detection - transforming noisy social media posts into clear, verifiable statements across 20 languages. The key contribution demonstrates how systematic decomposition of posts using Who, What, Where, When, Why and How questions enables robust cross-lingual transfer despite training exclusively o

Akshat Singh Jaswal

This paper introduces DuTerm, a novel two-stage architecture for terminology-constrained machine translation. Our system combines a terminology-aware NMT model, adapted via fine-tuning on large-scale synthetic data, with a prompt-based LLM for post-editing. The LLM stage refines NMT output and enforces terminology adherence. We evaluate DuTerm on English-to

Yun Ma, Pengkun Yang

Statistical inference on histograms and frequency counts plays a central role in categorical data analysis. Moving beyond classical methods that directly analyze labeled frequencies, we introduce a framework that models the multiset of unlabeled histograms via a mixture distribution to better capture unseen domain elements in large-alphabet regime. We study

Raju Biswas, Rajib Mandal

In this paper, we introduce definitions of the pre-Schwarzian and the Schwarzian derivatives for any locally univalent log-harmonic mappings defined in the unit disk $\mathbb{D}=\{z\in\mathbb{C}: |z|<1\}$. We explore the properties and applications of these concepts in the context of geometric function theory, and we also establish a necessary and sufficient

Zhu-Ling Deng, Xiang-Dong Li, Yong Shao, Ying-Han Mao

PSR J1928+1815, the first recycled pulsar-helium (He) star binary discovered by the Five-hundred-meter Aperture Spherical radio Telescope, consists of a 10.55 ms pulsar and a companion star with mass $1-1.6\,M_{\sun}$ in a 0.15-day orbit. Theoretical studies suggest that this system originated from a neutron star (NS) intermediate-mass or high-mass X-ray bin

Hugo Germain, Blanka Balogh, Olivier Geoffroy, David Saint-Martin

In this study, we improve a neural network (NN) parameterization of deep convection in the global atmosphere model ARP-GEM. To take into account the sporadic nature of convection, we develop a NN parameterization that includes a triggering mechanism that can detect whether deep convection is active or not within a grid-cell. This new data-driven parameteriza

Jun Li, Yanwei Xu, Keran Li, Xiaoli Zhang

Understanding intrinsic differences between adversarial examples and clean samples is key to enhancing DNN robustness and detection against adversarial attacks. This study first empirically finds that image-based adversarial examples are notably sensitive to occlusion. Controlled experiments on CIFAR-10 used nine canonical attacks (e.g., FGSM, PGD) to genera

Yu. A. Markov, M. A. Markova, D. M. Gitman, N. Yu. Markov

Within the framework of the Zakharov-Schulman approach, in close analogy with the methods of quantum field theory, the classical scattering matrix for the simplest process of interaction between hard and soft excitations in a quark-gluon plasma (QGP), is determined. The classical $\mathcal{S}$-matrix is defined in the form of the most general integro-power s

Yibai Liu, Shihang Wang, Zeming Liu, Zheming Song

Despite large language models (LLMs) have achieved impressive achievements across numerous tasks, supervised fine-tuning (SFT) remains essential for adapting these models to specialized domains. However, SFT for domain specialization can be resource-intensive and sometimes leads to a deterioration in performance over general capabilities due to catastrophic

Tommaso Proietti, Alessandro Giovannelli

The quantification of the interannual component of variability in climatological time series is essential for the assessment and prediction of the El Ni\~{n}o - Southern Oscillation phenomenon. This is achieved by estimating the deviation of a climate variable (e.g., temperature, pressure, precipitation, or wind strength) from its normal conditions, defined

Chenghao Li, Pengyang An, Ziao Huang, Qiwen Zhan

Modal crosstalk is a fundamental limitation for orbital angular momentum (OAM)-based spatial-division multiplexing. Here, we introduce Annular Channel Eigenmodes (ACEs) - rigorously derived as the optimal band-limited solution for maximizing energy concentration within distinct annular channels. This approach reformulates the design as a Hermitian eigenvalue

P. Berk, K. Frączek, Ł. Kotlewski, F. Trujillo

In this article, we study affine interval exchange transformations (AIETs) which are semi-conjugated to interval exchange transformations (IETs) of hyperbolic periodic type. More precisely, we study the Hausdorff dimension of their invariant measures, as well as the Hausdorff dimension of conformal measures of self-similar interval exchange transformations,

Chung Park, Taesan Kim, Hyeongjun Yun, Dongjoon Hong

Traditional recommender systems (RS) have been primarily optimized for accuracy and short-term engagement, often overlooking transparency and trustworthiness. Recently, platforms such as Amazon and Instagram have begun providing recommendation rationales to users, acknowledging their critical role in fostering trust and enhancing engagement; however, most ex

Bruno Dall'Agnol de Oliveira, Thaisa Storchi-Bergmann, Neil Nagar, Santiago Garcia-Burillo

We present a study of the cold molecular gas kinematics in the inner ~ 4-7 kpc (projected sizes) of three nearby Seyfert galaxies, with AGN luminosities of ~ 10$^{44}$ erg/s, using observations of the CO(2-1) emission line, obtained with the Atacama Large Millimeter/submillimeter Array (ALMA) at ~ 0.5-0.8$^{\prime\prime}$ (~ 150-400 pc) spatial resolutions.

Giuseppe Esposito, Juan-David Guerrero-Balaguera, Josie Esteban Rodriguez Condia, Matteo Sonza Reorda

Graphics Processing Units (GPUs) are specialized accelerators in data centers and high-performance computing (HPC) systems, enabling the fast execution of compute-intensive applications, such as Convolutional Neural Networks (CNNs). However, sustained workloads can impose significant stress on GPU components, raising reliability concerns due to potential fau

Philipp Schaad, Tal Ben-Nun, Torsten Hoefler

Control flow graphs (CFGs) are essential tools for understanding program behavior, yet the size of real-world CFGs makes them difficult to interpret. With thousands of nodes and edges, sophisticated graph drawing algorithms are required to present them on screens in ways that make them readable and understandable. However, being designed for general graphs,

Sophia Smyrli

In this work we study the following classical still challenging Calculus problem: {\it If $f:(0,\infty)\to\mathbb{R}$ is a continuous function, for which the sequence $\{f(nx)\}$ tends to zero, for every positive $x$, as $n$ tends to infinity, then $f(x)$ also tends to zero, as $x$ tends to infinity.}

V. N. Mantsevich, D. S. Smirnov, E. L. Ivchenko

The polarization entanglement of photons emitted by semiconductor quantum dots is unavoidably limited by the spin fluctuations of the host lattice nuclei. To overcome this limitation, we develop a theory of entangled photon pair generation by a symmetric colloidal quantum dot mediated by a triplet exciton. We derive general analytical expressions for the con

Jinglin Liang, Jin Zhong, Shuangping Huang, Yunqing Hu

In this paper, we explore an important yet previously neglected question: Do context aggregation patterns across Language Models (LMs) share commonalities? While some works have investigated context aggregation or attention weights in LMs, they typically focus on individual models or attention heads, lacking a systematic analysis across multiple LMs to explo

Pramod N. Achar, Simon Riche

These notes are our contribution to the Proceedings of the ICM 2026. We discuss some results we have obtained (in part jointly with coauthors) regarding the representation theory of reductive algebraic groups over algebraically closed fields of positive characteristic. These statements mainly concern tilting modules, in particular their characters and suppor

Yu-Chen Hua, Xiao-Jun Bi, Yu-Ming Yang, Peng-Fei Yin

The Lorentz invariance violation (LIV) predicted by some quantum gravity theories would manifest as an energy-dependent speed of light, which may potentially distort the observed temporal profile of photons from astrophysical sources at cosmological distances. The dispersion cancellation (DisCan) algorithm offers a powerful methodology for investigating such

Aleksandr Mazur, Roman Sharypov, Andrey Shirokov

An ensemble of neural networks is employed to extrapolate no-core shell model (NCSM) results to infinite model space for light nuclei. We present a review of our neural network extrapolations of the NCSM results obtained with the Daejeon16 NN interaction in different model spaces and with different values of the NCSM basis parameter $\hbar\Omega$ for energie

Yizheng Liu, Zachary J. Biegler, Ashley E. Wissel-Garcia, James S. Speck

This work reports the demonstration of lateral p-NiOx/p-GaN/n-GaN-based super-heterojunction (SHJ) diodes using p-GaN with additional sputtered p-type nickel oxide (NiOx) layers to realize charge-balanced structures. The heterojunction diode capacitance-voltage (C-V) model is applied to extract effective the acceptor concentration from the p-NiOx. Net donor

Mingyu Sheng, Jianan Fan, Dongnan Liu, Guoyan Zheng

During laparoscopic surgery, smoke generated by tissue cauterization can significantly degrade the visual quality of endoscopic frames, increasing the risk of surgical errors and hindering both clinical decision-making and computer-assisted visual analysis. Consequently, removing surgical smoke is critical to ensuring patient safety and maintaining operative

Yuanxiang Huangfu, Chaochao Wang, Weilei Wang

The effectiveness of Contrastive Language-Image Pre-training (CLIP) models critically depends on the semantic diversity and quality of their training data. However, while existing synthetic data generation methods primarily focus on increasing data volume, such emphasis often leads to limited semantic diversity and redundant or shallow captions. To address t

Jia-Kai Wu, Zhi-Wei Liu, Yong Zhao, Yan-Wu Wang

This paper proposes an energy-workload coupled migration optimization strategy for virtual power plants (VPPs) with data centers (DCs) to enhance resource scheduling flexibility and achieve precise demand response (DR) curve tracking. A game-based coupled migration framework characterized by antisymmetric matrices is first established to facilitate the coord

Mingyu Sung, Hyeonmin Choe, Il-Min Kim, Sangseok Yun

Monocular depth estimation (MDE), inferring pixel-level depths in single RGB images from a monocular camera, plays a crucial and pivotal role in a variety of AI applications demanding a three-dimensional (3D) topographical scene. In the real-world scenarios, MDE models often need to be deployed in environments with different conditions from those for trainin

M. Z. Mo, M. B. Maigler, T. Held, B. K. Ofori-Okai

Melting is an everyday phase transition that is determined by thermodynamic parameters like temperature and pressure. In contrast, ultrafast melting is governed by the microscopic response to a rapid energy input and, thus, can reveal the strength and dynamics of atomic bonds as well as the energy flow rate to the lattice. Accurately describing these process

Wakuto Matsumi, Riaz-Ul-Haque Mian

Machine learning based on neural networks has advanced rapidly, but the high energy consumption required for training and inference remains a major challenge. Hyperdimensional Computing (HDC) offers a lightweight, brain-inspired alternative that enables high parallelism but often suffers from lower accuracy on complex visual tasks. To overcome this, hybrid a

Zihao Li, Yiming Zhu, Zhe Zhong, Qinyuan Ren

Robotic manipulation in complex, constrained spaces is vital for widespread applications but challenging, particularly when navigating narrow passages with elongated objects. Existing planning methods often fail in these low-clearance scenarios due to the sampling difficulties or the local minima. This work proposes Topology-Aware Planning for Object Manipul

Abimbola Agboke, Felicia Nkatv Undie

This paper focused on the utilization of social media by library professionals and library users. It provides an understanding of social media, the most popular social media platforms utilized in the libraries. It also mentions the reasons for the adoption of social media in libraries be it academic, public, school libraries and other types of libraries. Thi

Minghan Chu, Weicheng Qian

Predicting the evolution of turbulent flows is central across science and engineering. Most studies rely on simulations with turbulence models, whose empirical simplifications introduce epistemic uncertainty. The Eigenspace Perturbation Method (EPM) is a widely used physics-based approach to quantify model-form uncertainty, but being purely physics-based it

Yihong Zou

At the rapid pace of technological evolution, the emerging cloud computing technology has promoted the digitalization and business innovation of the enterprise in all industries due to its advantages of data storage and service mode. Nevertheless, given the swift progress in cloud computing services, the security problems have gradually appeared. The data br

Zhenyu Xiao, Xiangyu Pi, Songqi Cao, Lipeng Zhu

Movable antenna (MA) has been recognized as a promising technology for performance enhancement in wireless communication and sensing systems by exploiting the spatial degrees of freedom (DoFs) in flexible antenna movement. However, the integration of MAs into next-generation wireless networks still faces design challenges due to the paradigm shift from conve

Muhammad Talha, Qi Yang, Zhu Li, Anique Akhtar

Point clouds (PC) are essential for AR/VR and autonomous driving but challenge compression schemes with their size, irregular sampling, and sparsity. MPEG's Geometry-based Point Cloud Compression (GPCC) methods successfully reduce bitrate; however, they introduce significant blocky artifacts in the reconstructed point cloud. We introduce a novel multi-scale

Huan Liu

We introduce and systematically develop two classes of discrete integrable operators: those with $2\times 2$ matrix kernels and those possessing general differential kernels, thereby generalizing the discrete analogue previously studied. A central finding is their inherent connection to higher-order pole solutions of integrable hierarchies, contrasting sharp

Xinyu Chen, Yiran Wang, Gaoyang Pang, Jiafu Hao

Medical Referring Image Segmentation (MRIS) involves segmenting target regions in medical images based on natural language descriptions. While achieving promising results, recent approaches usually involve complex design of multimodal fusion or multi-stage decoders. In this work, we propose NTP-MRISeg, a novel framework that reformulates MRIS as an autoregre

The STAR Collaboration

We present measurements of cumulants of event-by-event net-proton distribution at mid-rapidity and their ratios up to the sixth order as a function of charged-particle multiplicity in Zr+Zr and Ru+Ru(isobars) collisions at a nucleon-nucleon center-of-mass energy ($\sqrt{s_{NN}}$) of 200 GeV. The data are collected from the STAR experiment with a total of two

Seokhwan Min, Junhyung Park, Jonghwa Shin

Although freeform devices with complex internal structures promise drastic increases in performance, the discreteness of the set of available materials presents challenges for gradient-based optimization necessary for the efficient exploration of the high-dimensional freeform parameter space. Several schemes have been devised to utilize a continuous latent p

Mykyta Syromiatnikov, Victoria Ruvinskaya

Evaluating the real capabilities of large language models in low-resource languages still represents a challenge, as many existing benchmarks focus on widespread tasks translated from English or evaluate only simple language understanding. This paper introduces UA-Code-Bench, a new open-source benchmark established for a thorough evaluation of language model

Jiuqi Yan, Chendong Xu, Dongyu Liu

Radar systems are increasingly favored for medical applications because they provide non-intrusive monitoring with high privacy and robustness to lighting conditions. However, existing research typically relies on single-domain radar signals and overlooks the temporal dependencies inherent in human activity, which complicates the classification of similar ac

Zhengxuan Li, Qinhui Yang, Yiyu Zhuang, Chuan Guo

We present Pressure2Motion, a novel motion capture algorithm that reconstructs human motion from a ground pressure sequence and text prompt. At inference time, Pressure2Motion requires only a pressure mat, eliminating the need for specialized lighting setups, cameras, or wearable devices, making it suitable for privacy-preserving, low-light, and low-cost mot

C. Piyakulworawat, K. Morita, Y. Fukumoto, W. -Y. Hsieh

We analyze powder-averaged inelastic neutron scattering and magnetization data for the distorted honeycomb compound Cu$_5$SbO$_6$ using a first-order dimer expansion calculation and quantum Monte Carlo simulations. We show that, in contrast to the previously proposed honeycomb lattice model, Cu$_5$SbO$_6$ accommodates interacting dimerized spin chains with a

I. Villani, L. Zappacosta, E. Piconcelli, M. Ginolfi

The most luminous and obscured quasars (QSOs) detected in infrared all-sky surveys could represent a key co-evolutionary phase from nuclear to circum-galactic (CG) scales in the formation of massive galaxies. In this context, Hot Dust Obscured Galaxies (Hot DOGs) at z ~2-4 provide a unique opportunity to study the link between cosmic mass assembly and nuclea

Robert Andrews, Mrinal Kumar, Shanthanu S. Rai

Modular composition is the problem of computing the coefficient vector of the polynomial $f(g(x)) \bmod h(x)$, given as input the coefficient vectors of univariate polynomials $f$, $g$, and $h$ over an underlying field $\mathbb{F}$. While this problem is known to be solvable in nearly-linear time over finite fields due to work of Kedlaya & Umans, no such nea

Jing Jin, Xu Liu, Te Gao, Zhihong Shi

Whole Slide Image (WSI) representation is critical for cancer subtyping, cancer recognition and mutation prediction.Training an end-to-end WSI representation model poses significant challenges, as a standard gigapixel slide can contain tens of thousands of image tiles, making it difficult to compute gradients of all tiles in a single mini-batch due to curren

Jennifer K. Leestma, Siddharth R. Nathella, Christoph P. O. Nuesslein, Snehil Mathur

Epically Powerful is an open-source robotics infrastructure that streamlines the underlying framework of wearable robotic systems - managing communication protocols, clocking, actuator commands, visualization, sensor data acquisition, data logging, and more - while also providing comprehensive guides for hardware selection, system assembly, and controller im

Katharina Kormann, Eric Sonnendrücker

Geometric particle-in-cell discretizations have been derived based on a discretization of the fields that is conforming with the de Rham structure of the Maxwell's equation and a standard particle-in-cell ansatz for the fields by deriving the equations of motion from a discrete action principle. While earlier work has focused on finite element discretization

Isabel Neto, Alexandre S. Pires, Filipa Correia, Fernando P. Santos

Social interactions increasingly involve artificial agents, such as conversational or collaborative bots. Understanding trust and prosociality in these settings is fundamental to improve human-AI teamwork. Research in biology and social sciences has identified mechanisms to sustain cooperation among humans. Indirect reciprocity (IR) is one of them. With IR,

Zhuang Ma, Peng Zhao, Xinsheng Tan, Yang Yu

Superconducting circuits are a leading platform for scalable quantum computing, where parametric modulation is a widely used technique for implementing high-fidelity multi-qubit operations. A critical challenge, however, is that this modulation can induce a dense landscape of parasitic couplings, leading to detrimental frequency collisions that constrain pro

Panagiotis G. Papaioannou, Athanassios N. Yannacopoulos

We introduce a Geometry Informed Model for financial forecasting by embedding high dimensional market data onto constant curvature 2manifolds. Guided by the uniformization theorem, we model market dynamics as Brownian motion on spherical S2, Euclidean R2, and hyperbolic H2 geometries. We further include the torus T, a compact, flat manifold admissible as a q

Sakiko Obuchi, Kohei Ichikawa, Satoshi Yamada, Nozomu Kawakatu

We report the multiwavelength properties of eFEDS J084222.9+001000 (hereafter ID830), a quasar at $z=3.4351$, identified as the most X-ray luminous radio-loud quasar in the eROSITA Final Equatorial Depth Survey (eFEDS) field. ID830 shows a rest-frame 0.5-2 keV luminosity of $\log (L_\mathrm{0.5-2\,keV}/\mathrm{erg}~\mathrm{s}^{-1}) = 46.20 \pm 0.12$, with a

Dongjin Park, Hasung Yeo, Joon-Woo Lee

Federated fine-tuning (FFT) adapts foundation models to decentralized data but remains fragile under heterogeneous client distributions due to local drift, i.e., client-level update divergences that induce systematic bias and amplified variance in the global model. Existing aggregation and personalization methods largely correct drift post hoc, which proves

Zhuoling Chen, Yi Zhong, Martin Haenggi

The directional RTS/CTS mechanism of mm-wave Wi-Fi hardly resolves the hidden terminal problem perfectly. This paper proposes cross-link RTS/CTS under multi-link operation (MLO) to address this problem and introduces a novel point process, named the generalized RTS/CTS hard-core process (G-HCP), to model the spatial transceiver relationships under the RTS/CT

Xingyuan Zhou, Peter Paik, S. Farokh Atashzar

Centralized Multiport Networked Dynamic (CMND) systems have emerged as a key architecture with applications in several complex network systems, such as multilateral telerobotics and multi-agent control. These systems consist of a hub node/subsystem connecting with multiple remote nodes/subsystems via a networked architecture. One challenge for this system is

Hala Sheta

The proliferation of assistive chatbots offering efficient, personalized communication has driven widespread over-reliance on them for decision-making, information-seeking and everyday tasks. This dependence was found to have adverse consequences on information retention as well as lead to superficial emotional attachment. As such, this work introduces 8bit-

Haoyu Qin, Weixuan Zhang, Shaohu Chen, Huizhen Zhang

Bound states in the continuum (BICs) are widely known spatially localized states experimentally implemented as quasi-BICs. Although they emerged as a promising solution for achieving high-quality resonances in photonic structures, quasi-BICs are confined to a very narrow range in k-space and are highly sensitive to disorder. Here, we introduce quasi-bound fl

Yifan Deng, Ming Cheng, Lanxin Liu, Nan Zhou

The Kagome lattice has attracted extensive attention due to the diverse magnetic properties and non-trivial electronic states generated by its unique atomic arrangement, which provides an excellent system for exploring macroscopic quantum behavior. Here, we report the anomalous transport properties in 166-type Kagome metal ZrV$_6$Sn$_6$ single crystals. The

Charles Melvin, N. Rich Nguyen

PriorityFresh is a semantic, actionability-first caching policy designed for offline emergency warning systems. Within the AWARE system's simulation environment, PriorityFresh optimizes which alerts to retain and surface under constrained connectivity. Experiments indicate improved actionability-first performance without harming efficiency. A separate Priori

Leixin Wu, Congtian Deng, Jiayu Pan, Lingtao Zhang

Although multiple-input multiple-output (MIMO) terahertz (THz) continuous-variable quantum key distribution (CVQKD) is theoretically secure, practical vulnerabilities may arise due to detector imperfections. This paper explores a CV measurement-device-independent (MDI) QKD system operating at THz frequencies within a MIMO framework. In this system, measureme

Yawei Cai, Jiapeng Mi, Nan Ji, Haotian Rong

Composed Image Retrieval (CIR) is a cross-modal task that aims to retrieve target images from large-scale databases using a reference image and a modification text. Most existing methods rely on a single model to perform feature fusion and similarity matching. However, this paradigm faces two major challenges. First, one model alone can't see the whole pictu

Satoshi Nakada, Kensei Nakamura

This paper studies the axiomatic bargaining problem and proposes a new class of bargaining solutions, called coarse Nash solutions. These solutions assign to each problem a set of outcomes coarser than that chosen by the classical Nash solution (Nash, 1950). Our main result shows that these solutions can be characterized by new rationality axioms for choice

Prasoon Varshney, Makesh Narsimhan Sreedhar, Liwei Jiang, Traian Rebedea

Large language models (LLMs) are typically aligned to a universal set of safety and usage principles intended for broad public acceptability. Yet, real-world applications of LLMs often take place within organizational ecosystems shaped by distinctive corporate policies, regulatory requirements, use cases, brand guidelines, and ethical commitments. This reali

E. F. Talantsev

Recently, Ksenofontov et al (arXiv:2510.03256) observed ambient pressure room-temperature superconductivity in graphite intercalated with lithium-based alloys with transition temperature (according to magnetization measurements) $T_c=330$ $K$. Here, I analyzed the reported temperature dependent resistivity data $\rho(T)$ in these graphite-intercalated sample

Chin-Ping Hu, Naoyuki Ota, Takuya Takahashi, Tomoshi Takeda

We report a long-term, high-cadence timing and spectral observation of the X-ray pulsar SMC X-1 using NinjaSat, a 6U CubeSat in low-Earth orbit, covering nearly a full superorbital cycle. SMC X-1 is a high-mass X-ray binary exhibiting a 0.7 s X-ray pulsar and a non-stationary superorbital modulation with periods ranging from approximately 40 to 65 days. Its

Zhen Cao, F. Aharonian, Y. X. Bai, Y. W. Bao

The $\gamma$-ray from Giant molecular clouds (GMCs) is regarded as the most ideal tool to perform in-situ measurement of cosmic ray (CR) density and spectra in our Galaxy. We report the first detection of $\gamma$-ray emissions in the very-high-energy (VHE) domain from the five nearby GMCs with a stacking analysis based on a 4.5-year $\gamma$-ray observation

Arvind Singh, Jan Kunc, Tinkara Troha, Hynek Němec

We study broadband terahertz (THz) conductivity and ultrafast photoconductivity spectra in lithographically fabricated multilayer epitaxial graphene nanoribbons grown on C- face of 6H-SiC substrate. THz near-field spectroscopy reveals local conductivity variations across nanoscale structural inhomogeneities such as wrinkles and grain boundaries within the mu

LHAASO Collaboration, Zhen Cao, F. Aharonian, Y. X. Bai

We report a measurement of the cosmic ray helium energy spectrum in the energy interval 0.16 -- 13~PeV, derived by subtracting the proton spectrum from the light component~(proton and helium) spectrum obtained with observations made by the Large High Altitude Air Shower Observatory~(LHAASO) under a consistent energy scale. The helium spectrum shows a signifi

Ryuya Hora

This paper provides a new categorical definition of a normalization operator motivated by topos theory and its applications to algebraic language theory. We first define a normalization operator $\Xi \to \Xi$ in any category that admits a colimit of all monomorphisms $\Xi$, which we call a local state classifier. In the category of group actions for a group

Ravshan Ashurov, Elbek Husanov

This paper explores the forward and inverse problems for a fractional subdiffusion equation characterized by time-dependent diffusion and reaction coefficients. Initially, the forward problem is examined, and its unique solvability is established. Subsequently, the inverse problem of identifying an unknown time-dependent reaction coefficient is addressed, wi

Yi Wang, Hang Yuan

It is known that a model for the differential graded algebra (dga) of differential forms on the free loop space $LN$ of a simply connected smooth manifold $N$ is given by the Hochschild chain complex of the dga $\Omega(N)$ of differential forms on $N$, as shown by K.-T. Chen via his theory of iterated integrals. We develop a relative version of Chen's model.

A. Rostami, K. Rezazadeh, M. Rostampour

We derive a relativistic extension of Modified Newtonian Dynamics (MOND) within the framework of entropic gravity by introducing temperature-dependent corrections to the equipartition law on a holographic screen. Starting from a general modification of the surface degrees of freedom and employing the Unruh relation between acceleration and temperature, we ob

S. Zhao, W. Lu, B. Wang, T. Wang

Ultra-high-definition (UHD) images often suffer from severe degradations such as blur, haze, rain, or low-light conditions, which pose significant challenges for image restoration due to their high resolution and computational demands. In this paper, we propose UHDRes, a novel lightweight dual-domain decoupled spectral modulation framework for UHD image rest

Baiye Cheng, Tianhai Liang, Suning Huang, Maanping Shao

Diffusion policies have emerged as a powerful framework for robotic visuomotor control, yet they often lack the robustness to recover from subtask failures in long-horizon, multi-stage tasks and their learned representations of observations are often difficult to interpret. In this work, we propose the Mixture of Experts-Enhanced Diffusion Policy (MoE-DP), w

Yang Liu

We propose a unified framework within Type IIA string theory, based on a globally consistent intersecting D6-brane model compactified on a $T^6/(\mathbb{Z}_2 \times \mathbb{Z}_2)$ orientifold. The model realizes the MSSM-like spectrum providing a framework for addressing four fundamental problems: CP violation originates from both geometric phases in Yukawa

Dongsu Lee, Daehee Lee, Amy Zhang

This work presents MAC-Flow, a simple yet expressive framework for multi-agent coordination. We argue that requirements of effective coordination are twofold: (i) a rich representation of the diverse joint behaviors present in offline data and (ii) the ability to act efficiently in real time. However, prior approaches often sacrifice one for the other, i.e.,

Siu-Ming Tam, Min Wang, Alicia Rambaldi, Dehua Tao

By amalgamating data from disparate sources, the resulting integrated dataset becomes a valuable resource for statistical analysis. In probabilistic record linkage, the effectiveness of such integration relies on the availability of linkage variables free from errors. Where this is lacking, the linked data set would suffer from linkage errors and the resulta

Ruifen Ma, Yanjing Sun, Xiaofei Qi

Quantum steering is a crucial quantum resource that lies intermediate between entanglement and Bell nonlocality. Gaussian channels, meanwhile, play a foundational role in diverse quantum protocols, secure communication, and related fields. In this paper, we focus on several classes of Gaussian channels associated with quantum steering: Gaussian steering-anni

Hyunkyu Kim, Yeeun Yoo, Youngjun Kwak

As financial applications of large language models (LLMs) gain attention, accurate Information Retrieval (IR) remains crucial for reliable AI services. However, existing benchmarks fail to capture the complex and domain-specific information needs of real-world banking scenarios. Building domain-specific IR benchmarks is costly and constrained by legal restri

Youzi He, Wei Wu, Hongyi Dang

This paper establishes uniqueness results of inverse elastic scattering problem with phaseless near-field data in periodic structures in $\mathbb{R}^2$ and periodic/biperiodic structures in $\mathbb{R}^3$. We use a superposition of two point sources in each periodic unit with different positions as the incident field, and measures the phaseless near-field da

Daniel S. Lee, Mayra S. Haedo-Cruz, Chen Jiang, Oshin Miranda

Transformer-based deep learning models have shown promise for disease risk prediction using electronic health records(EHRs), but modeling temporal dependencies remains a key challenge due to irregular visit intervals and lack of uniform structure. We propose a Bi-Positional Embedding Transformer Encoder or BiPETE for single-disease prediction, which integrat

Walter L. Leite, Huibin Zhang, Shibani Rana, Yide Hao

To expand the use of intelligent tutoring systems (ITS) in K-12 schools, it is essential to understand the conditions under which their use is most beneficial. This meta-analysis evaluated the heterogeneity of ITS effects across studies focusing on elementary, middle, and high schools in the U.S. It included 18 studies with 77 effect sizes across 11 ITS. Ove

Yukihiko Funaki, Yukio Koriyama, Satoshi Nakada, Yuki Tamura

We study efficient, linear, and symmetric (ELS) values, a central family of allocation rules for cooperative games with transferable-utility (TU-games) that includes the Shapley value, the CIS value, and the ENSC value. We first show that every ELS value can be written as the Shapley value of a suitably transformed TU-game. We then introduce three types of i

Amol Harsh, Brainerd Prince, Siddharth Siddharth, Deepan Raj Prabakar Muthirayan

This research-to-practice full paper was inspired by the persistent challenge in effective communication among engineering students. Public speaking is a necessary skill for future engineers as they have to communicate technical knowledge with diverse stakeholders. While universities offer courses or workshops, they are unable to offer sustained and personal

Xingyuan Zhou, Peter Paik, S. Farokh Atashzar

Maintaining system stability and accurate position tracking is imperative in networked robotic systems, particularly for haptics-enabled human-robot interaction. Recent literature has integrated human biomechanics into the stabilizers implemented for teleoperation, enhancing force preservation while guaranteeing convergence and safety. However, position desy

Bibekananda Patra, Sandipan Bandyopadhyay

This article presents a method for computing the largest singularity-free sphere (SFS) of a 6-6 Stewart-Gough platform manipulator (SGPM) over a specified orientation workspace. For a fixed orientation of the moving platform, the SFS is computed analytically. This process is repeated over a set of samples generated within the orientation workspace, and the s

Mengjia Bai, Jingrun Chen, Keke Wu

In this work, we propose a uniformly accurate, structure-preserving neural surrogate for the radiative transfer equation with periodic boundary conditions based on a multiscale parity decomposition framework. The formulation introduces a refined decomposition of the particle distribution into macroscopic, odd, and higher-order even components, leading to an

Yongsu Jung, Minji Kang, Muyoung Kim, Min Sup Choi

This study presents a comprehensive framework for uncertainty quantification (UQ) and design optimization of plasma etching in semiconductor manufacturing. The framework is demonstrated using experimental measurements of etched depth collected at nine wafer locations under various plasma conditions. A heteroscedastic Gaussian process (hetGP) surrogate model

Genheng Zhao

Let $E(X)$ denote the number of even integers below $X$ which are not a sum of two primes. We prove the bound $E(X)=O(X^{\frac{7}{10}})$, where the implicit constant is ineffective. The method applied here also leads to $P(q)=O(q^5)$, where $P(q)$ denotes the least prime, if it exists, in any arithmetic progression modulo $q$.

Ya Wang, Guangzheng Zhu, Cungen Cao, Jingjing Li

Knowledge about emotional events is an important kind of knowledge which has been applied to improve the effectiveness of different applications. However, emotional events cannot be easily acquired, especially common or generalized emotional events that are context-independent. The goal of this paper is to obtain common emotional events in Chinese language s

Fupeng Xu

We derive the $s$-invariants of certain simply connected $7$-manifolds whose second homology groups are isomorphic to $\mathbb{Z}^{2}$. We apply the $s$-invariants to give a partial classification of simply connected total spaces of circle bundles over $\left(\mathbb{C}P^{1}\times\mathbb{C}P^{2}\right)\#\mathbb{C}P^{3}$ up to diffeomorphism. As an applicatio

Runsheng Ren, Jing Li, Yanxiu Li, Shixun Huang

Accurately forecasting carbon prices is essential for informed energy market decision-making, guiding sustainable energy planning, and supporting effective decarbonization strategies. However, it remains challenging due to structural breaks and high-frequency noise caused by frequent policy interventions and market shocks. Existing studies, including the mos

Mohammadreza Saeidi, Ethan Thoma, Raula Gaikovina Kula, Gema Rodríguez-Pérez

Background: Widespread use of third-party libraries makes ecosystems like Node Package Manager (npm) critical to modern software development. However, this interconnected chain of dependencies also creates challenges: bugs in one library can propagate downstream, potentially impacting many other libraries that rely on it. We hypothesize that maintainers may

Anuraag Kumar

We investigate the hitting times of random walks on graphs, where a hitting time is defined as the number of steps required for a random walker to move from one node to another. While much of the existing literature focuses on calculating or bounding expected hitting times, this approach is insufficient, as hitting time distributions often exhibit high varia

Xinheng He, Yijia Zhang, Haowei Lin, Xingang Peng

Structure-based drug design has seen significant advancements with the integration of artificial intelligence (AI), particularly in the generation of hit and lead compounds. However, most AI-driven approaches neglect the importance of endogenous protein interactions with peptides, which may result in suboptimal molecule designs. In this work, we present Pept

Assma Habadi, Milos Zefran, Lijuan Yin, Woojin Song

Background and Objectives: This paper focuses on using AI to assess the cognitive function of older adults with mild cognitive impairment or mild dementia using physiological data provided by a wearable device. Cognitive screening tools are disruptive, time-consuming, and only capture brief snapshots of activity. Wearable sensors offer an attractive alternat

Tianxing Ding, Hongyang Liu, Yitong Yin, Can Zhou

The Coupling from the Past (CFTP) paradigm is a canonical method for perfect sampling. For uniform sampling of proper $q$-colorings in graphs with maximum degree $\Delta$, the bounding chains of Huber (STOC 1998) provide a systematic framework for efficiently implementing CFTP algorithms within the classical regime $q \ge (1 + o(1))\Delta^2$. This was subseq

Hyunseok Kwak, Kyeongwon Lee, Kyeongpil Min, Chaebin Jung

The growing demands of distributed learning on resource constrained edge devices underscore the importance of efficient on device model compression. Tensor Train Decomposition (TTD) offers high compression ratios with minimal accuracy loss, yet repeated singular value decompositions (SVDs) and matrix multiplications can impose significant latency and energy