November 2025 arXiv papers — page 4

Lin Zhu, Kezhi Wang, Luping Xiang, Kun Yang

Efficient information exchange and reliable contextual reasoning are essential for vehicle-to-everything (V2X) networks. Conventional communication schemes often incur significant transmission overhead and latency, while existing trajectory prediction models generally lack environmental perception and logical inference capabilities. This paper presents a tra

Rupesh Raj Karn, Lakshmi Likhitha Mankali, Zeng Wang, Saideep Sreekumar

Modern circuits face various threats like reverse engineering, theft of intellectual property (IP), side-channel attacks, etc. Here, we present a novel approach for IP protection based on logic encryption (LE). Unlike established schemes for logic locking, our work obfuscates the circuit's structure and functionality by encoding and encrypting the logic

Cheng Zhang, Hanwen Liang, Donny Y. Chen, Qianyi Wu

Panoramic video generation has attracted growing attention due to its applications in virtual reality and immersive media. However, existing methods lack explicit motion control and struggle to generate scenes with large and complex motions. We propose PanFlow, a novel approach that exploits the spherical nature of panoramas to decouple the highly dynamic ca

Yuchen Zeng, Shuibai Zhang, Wonjun Kang, Shutong Wu

Large Reasoning Models (LRMs) are Large Language Models (LLMs) explicitly trained to generate long-form Chain-of-Thoughts (CoTs), achieving impressive success on challenging tasks like math and programming. However, their underlying reasoning "algorithms" remain poorly understood. To investigate this, we propose ReJump, which represents a reasoning trace as

Weilun Cheng, Zongxia Liang, Sheng Wang, Jianming Xia

This paper studies a continuous-time portfolio selection problem under a general distribution of random risk aversion (RRA). We provide a complete characterization of all deterministic equilibrium strategies in closed form. Our results show that the structure of the solution depends crucially on the distribution of RRA: the equilibrium is unique (if exits) w

Md Mehrab Hossain Opi, Sumaiya Khan, Moshammad Farzana Rahman

Training models for Natural Language Processing (NLP) requires substantial computational resources and time, posing significant challenges, especially for NLP development in Bangla, where access to high-end hardware is often limited. In this work, we explore automatic mixed precision (AMP) training as a means to improve computational efficiency without sacri

Mohd Talib, M. A. H. Ahsan

The emergence of quantum chaos in a system of trapped interacting bosons with externally impressed rotation is studied through spectral form factor (SFF) and power spectrum using exact diagonalization. Two distinct interaction regimes are considered: the moderate, when the interaction energy is small compared to the trap energy and the strong, when the inter

M. Murakami

We present a class of self-similar solutions describing ultrahigh compression of a uniform-density target by spherically converging, stacked shock waves. Extending the classical Guderley model, we derive a scaling law for the final density of the form $\rho_{r}/\rho_{0} \propto \hat{P}^{\beta (N-1)}$, where $N$ is the number of shocks, $\hat{P}$ the stage pr

Reina Camacho, Melissa Cruz, Salvatore Mele, Fernando Monticelli

This document collects input from Latin America as a contribution to the Update of the European Strategy for Particle Physics. It emerges from a survey of members of the Latin American Association for High Energy, Cosmology and Astroparticle Physics (LAA-HECAP) that collected data in February and a subsequent town-hall meeting, inspired by the ECFA guideline

Inyoung Kim

We show that a compact oriented riemannian four-manifold with harmonic and pinched self-dual Weyl curvature is anti-self-dual if the type is nonpositive. The main part is to show that there is an almost-K\"ahler structure outside the zero set of the self-dual Weyl curvature.

Alvin Nahabwe, Sulaiman Kagumire, Denis Musinguzi, Bruno Beijuka

Automatic speech recognition (ASR) for African languages remains constrained by limited labeled data and the lack of systematic guidance on model selection, data scaling, and decoding strategies. Large pre-trained systems such as Whisper, XLS-R, MMS, and W2v-BERT have expanded access to ASR technology, but their comparative behavior in African low-resource c

Arpit Kottur, Meet Mehta, Raka Dabhade

We present an empirical investigation into the relationship between galactic age and dark matter content across a sample of 16 nearby, well-resolved spiral galaxies. Using raw rotation curve data from IOA Tokyo's publicly available repository, we model each galaxy's mass distribution via a three-component decomposition (Hernquist bulge, exponential disk, and

Marianela Quirós-Rojas, Alfredo Montaña, Jorge A. Zavala, Itziar Aretxaga

We study the multiplicity of galaxies in the largest sample of red-Herschel sources ($S_{250 \mu \mathrm{m}} < S_{350 \mu \mathrm{m}} < S_{500 \mu \mathrm{m}}$) using archival ALMA observations. Out of 2416 fields with ALMA detections (from a total of 3,089 analyzed maps), we identify 474 multiple systems within a radius of 16 arcsec (equivalent to the 500 $

Michael Kerber, Elena Xinyi Wang

The Persistent Homology Transform (PHT) summarizes a shape in $\mathbb{R}^m$ by collecting persistence diagrams obtained from linear height filtrations in all directions on $\mathbb{S}^{m-1}$. It enjoys strong theoretical guarantees, including continuity, stability, and injectivity on broad classes of shapes. A natural way to compare two PHTs is to use the b

Salvador J. Robles-Perez, Salvador Castillo-Rivera

This work studies the relationship between parametric amplification (or particle creation), adiabaticity and irreversibility in the non-quasi-static regime of a time-dependent quantum harmonic oscillator (TDHO) that evolves unitarily. We provide analytical results for the evolution of the TDHO valid for any functional value of the frequency, which enables us

Haozhen Gong, Xiaozhong Ji, Yuansen Liu, Wenbin Wu

MLLMs MLLMs are beginning to appear in clinical workflows, but their ability to perform complex medical reasoning remains unclear. We present Med-CMR, a fine-grained Medical Complex Multimodal Reasoning benchmark. Med-CMR distinguishes from existing counterparts by three core features: 1) Systematic capability decomposition, splitting medical multimodal reas

Florent P. Baudier, Gilles Lancien

This book discusses the interactions between the (nonlinear) metric structure of Banach spaces and their linear asymptotic behavior. The overarching problem is to understand how the various linear structures of a Banach space are preserved under certain nonlinear maps. The first chapters contain what are by now classical results to study the most basic and f

Toshihito Osada, Mitsuyuki Sato, Takako Konoike, Woun Kang

We experimentally confirm the \nu = 0 quantum Hall ferromagnetic (QHF) state, accompanied by helical edge states, in the layered organic Dirac-fermion system \alpha-(ET)2I3 by demonstrating helical edge transport in multilayers. The saturation of interlayer magnetoresistance (MR) in the high-magnetic-field quantum limit does not scale with the sample cross-s

Yeongju Choi, Seungjin Lee, Dongwon Shin, Sukhoon Sim

Hybrid heterostructures composed of graphene and perovskite oxides provide a promising platform for exploiting synergetic interfacial functionalities. Conventional fabrication methods of the hybrid heterostructures rely on transferring graphene grown on metallic substrates-- a process that is time-consuming, labor-intensive, and prone to introducing numerous

Savitha K S, Sandi Klavžar, Tijo James

In the Maker-Breaker resolving game, two players named Resolver and Spoiler alternately select unplayed vertices of a given graph $G$. The aim of Resolver is to select all the vertices of some resolving set of $G$, while Spoiler aims to select at least one vertex from every resolving set of $G$. In this paper, this game is investigated on the lexicographic p

Yijia Fan, Jusheng Zhang, Kaitong Cai, Jing Yang

Multi-label classification (MLC) remains vulnerable to label imbalance, spurious correlations, and distribution shifts, challenges that are particularly detrimental to rare label prediction. To address these limitations, we introduce the Causal Cooperative Game (CCG) framework, which conceptualizes MLC as a cooperative multi-player interaction. CCG unifies e

Tony J. Puthenpurakal

Let $k$ be a field and let $V$ be a $k$-vector space of dimension $d$. Let $G \subseteq GL(V)$ be a finite group. Let $r = \dim_k (V^*)^G$. Assume $r \geq 1$. Let $R = k[V]^G$ be the ring of invariants of $G$. Let $H_R(n) = a_{d-1}(n)n^{d-1} + \cdots a_1(n)n + a_0(n)$ be the Hilbert polynomial of $R$ where $a_i(-)$ are periodic functions. We show $a_{d-1}(-)

Saeed Hedayatian, Stefanos Nikolaidis

Quality-Diversity (QD) algorithms constitute a branch of optimization that is concerned with discovering a diverse and high-quality set of solutions to an optimization problem. Current QD methods commonly maintain diversity by dividing the behavior space into discrete regions, ensuring that solutions are distributed across different parts of the space. The Q

Wen-Han Zhou, Yun Zhang, Jiamu Huang, Douglas N. C. Lin

Sgr A*, the supermassive black hole at the center of the Milky Way, exhibits frequent short-duration flares with luminosity greater than 1e34 erg/s across multiple wavelengths. The origin of the flares is still unknown. We revisited the role of small planetary bodies, originally from the stellar disk, and their tidally disrupted fragments as a source of flar

Qiao Ke, Chengjun Zhang, Chuang Liu, Mingxia Jing

Identifying the diffusion source in complex networks is critical for understanding and controlling epidemic spread. In realistic settings, full observation of node states is rarely available, making sensor-based source detection a practical alternative. However, existing sensor-based methods are often confined to simple networks, failing to capture the highe

Pengfei Hu, Meng Cao, Yingyao Wang, Yi Wang

Long video understanding is essential for human-like intelligence, enabling coherent perception and reasoning over extended temporal contexts. While the emerging thinking-with-frames paradigm, which alternates between global temporal reasoning and local frame examination, has advanced the reasoning capabilities of video multi-modal large language models (MLL

M. Murakami, D. Balusu, S. Maruyama, Y. Murakami

Our proposed ion acceleration scheme, micronozzle acceleration (MNA), generates proton beams with extremely high kinetic energies on the giga-electron-volt (GeV) order. The underlying physics and performance of MNA are studied with two-dimensional particle-in-cell simulations. In MNA targets, a micron-sized hydrogen rod is embedded inside a hollow micronozzl

Grigorios Fournodavlos, Vassili Nestoridis, Spyros Pasias

Arakelian's classical approximation theorem \cite{Ar} gives necessary and sufficient conditions such that functions can be uniformly approximated in (unbounded) closed sets $F\subset \mathbb{C}$ by entire functions. The conditions are purely topological and concern the connectedness of the complement of $F$. We give a new characterization of Arakelian sets i

Sedef Karakiliç, Sedef Özcan

We present an analytical investigation of the asymptotic behavior of non-resonance eigenvalues for the fractional Schr\"odinger operator under homogeneous Neumann boundary conditions. Our findings reveal an intriguing convergence: as the system evolves, the eigenvalues of the fractional Schr\"odinger operator increasingly resemble those of the fractional Lap

Marc Aubreville, Taryn A. Donovan, Christof A. Bertram

Recent advances in agentic artificial intelligence, i.e. systems capable of autonomous perception, reasoning, and tool use, offer new opportunities for digital pathology. In this pilot study, we evaluate whether two agentic multimodal AI systems (OpenAI's ChatGPT 5.0 in agentic mode, and H Company's Surfer) can autonomously navigate, describe, and interpret

Shawan K. Jha, Makoto Tsubota, Pankaj K. Mishra

In this work, we analyze the evolution of four vortex configurations, namely, dipole, plasma, cluster, and lattice, using the two-dimensional mean-field Gross-Pitaevskii equation, focusing on their dynamical decay and approach to the equilibrium. Our analysis reveals that the cluster vortex configuration reaches equilibrium more rapidly than the others, whil

Taha Anwar

The Standard Model of particle physics is built on the principle of local gauge symmetry. This work provides a pedagogical introduction for advanced undergraduates by using quantum electrodynamics (QED) as the simplest example of a gauge theory. Beginning with the Lagrangian formulation of classical mechanics, special relativity, and basic quantum mechanics,

Jiangwei Zhang, Juntao Wu

In this paper, we investigate the uniform measure attractors of the distribution-dependent nonautonomous 2D stochastic Navier-Stokes equations driven by nonlinear noise and subject to almost periodic external forcing. Owing to the distribution-dependent structure and the almost periodicity of the external forcing, the resulting solution process becomes an in

Nan Sun, Bo Mao, Yongchang Li, Chenxu Wang

Foundation models have become central to unifying perception and planning in robotics, yet real-world deployment exposes a mismatch between their monolithic assumption that a single model can handle all cognitive functions and the distributed, dynamic nature of practical service workflows. Vision-language models offer strong semantic understanding but lack e

Jiajian He, Enjie Hu, Shiqi Chen, Tianchen Qiu

The point spread function (PSF) serves as a fundamental descriptor linking the real-world scene to the captured signal, manifesting as camera blur. Accurate PSF estimation is crucial for both optical characterization and computational vision, yet remains challenging due to the inherent ambiguity and the ill-posed nature of intensity-based deconvolution. We i

Qirui Ji, Bin Qin, Yifan Jin, Yunze Zhao

Graph contrastive learning (GCL) aims to learn discriminative semantic invariance by contrasting different views of the same graph that share critical topological patterns. However, existing GCL approaches with structural augmentations often struggle to identify task-relevant topological structures, let alone adapt to the varying coarse-to-fine topological g

D. Pan, M. Murakami

We demonstrate the generation of ultrahigh magnetic fields in the order of gigagauss using a bladed microtube target whose inner surface is periodically slanted in a sawtooth-like pattern. When irradiated by ultra-intense, ultrashort laser pulses, hot electrons with MeV energies are produced at the outer surface and swiftly transported to the inner surface,

Bo Guo, Sijia Wen, Yifan Zhao, Jia Li

Recent advances in surface reconstruction for 3D Gaussian Splatting (3DGS) have enabled remarkable geometric accuracy. However, their performance degrades in photometrically ambiguous regions such as reflective and textureless surfaces, where unreliable cues disrupt photometric consistency and hinder accurate geometry estimation. Reflected light is often par

A. Arshinova, K. Sanderson, A. Moiseev

Green Bean is a rare type of galaxy which represents a short-lived phase in the life cycle of active galactic nuclei (AGN), characterised by large-scale, powerful ionised clouds in the circumgalactic medium. Recent studies demonstrate that these extended ionised structures may reflect fading signatures of past AGN activity, often manifested in the form of la

Liyu Zerihun

Deep networks are heavily over-parameterized, yet their learned representations often admit low-rank structure. We introduce a framework for estimating a model's intrinsic dimensionality by treating learned representations as projections onto a low-rank subspace of the model's full capacity. Our approach: train a full-rank teacher, factorize its weights at m

Jordi Pérez-Guijarro

When the distributions of the training and test data do not coincide, the problem of understanding generalization becomes considerably more complex, prompting a variety of questions. Prior work has shown that, for some fixed learning methods, there are scenarios where training on a distribution different from the test distribution improves generalization. Ho

Kirill Shulga, Shunsuke Nishimura, Pavel A. Volkov, Ryota Hasegawa

We demonstrate the detection and control of individual Abrikosov vortices in superconducting microwave resonators. $\lambda/4$ resonators with a narrowed region near the grounded end acting as a vortex trap were fabricated and studied using microwave transmission spectroscopy at millikelvin temperatures. Sharp stepwise drops in resonance frequency are detect

Xiaodong Cai, Hai Lin, Shaoxiong Zhan, Weiqi Luo

Token sampling strategies critically influence text generation quality in large language models (LLMs). However, existing methods introduce additional hyperparameters, requiring extensive tuning and complicating deployment. We present Entropy Equilibrium Sampling (EES), an auxiliary hyperparameter-free approach inspired by information theory that can dynamic

Anupam, Sheryl Mathew, Sibasish Ghosh

Quantum batteries have emerged as a platform for investigating whether quantum effects can accelerate energy storage beyond classical limits. Although a variety of charging schemes have reported signatures of quantum advantage, the fundamental physical requirements for achieving superextensive charging power remain insufficiently understood. Here, we show th

Takao Yamazaki, Yifan Yang, Hwajong Yoo, Myungjun Yu

We define and study a biadditive symmetric (not necessarily perfect) pairing on the torsion part $\mathrm{Pic}(X)_{\mathrm{tors}}$ of the Picard group of a smooth projective curve $X$ over a field $k$ with values in $k^\times \otimes \mathbb{Q}/\mathbb{Z}$. We call its kernel the intrinsic subgroup of $X$. It turns out that some information on the reduction

Masao Takata, Simon J. Murphy, Donald W. Kurtz, Hideyuki Saio

An asteroseismic analysis has revealed a magnetic field in the deep interior of a slowly-rotating main-sequence F star KIC9244992, which was observed by the Kepler spacecraft for four years. The star shows clear asymmetry of frequency splittings of high-order dipolar gravity modes, which cannot be explained by rotation alone, but are fully consistent with a

Emre Akusta

This study analyzes OECD countries in the context of the energy trilemma index and clusters countries with similar characteristics. In the study, the k-means clustering technique is used. The optimum number of clusters was determined using the Elbow method in combination with the Silhouette Index. Moreover, all results are visualized to enhance comprehensibi

Libo Wang

To address a fundamental limitation in cognitive systems, namely the absence of a time-updatable mediating thought space between semantics and continuous control, this work constructs and trains a vision-language-action model termed Sigma, deployed on a single RTX 4090. The model is built upon the open-source pi0.5_base backbone, with the svla_so101_pickplac

Senyu Zhang, Wei Luo, Shuang Zheng, Yunlong Li

Microwave photonics (MWP) serves as a powerful bridge between the radio-frequency and optical worlds, unlocking unprecedented bandwidth and speed for critical information systems. Recently, MWP-based radar jamming has demonstrated significant potential in overcoming electronic bottlenecks; however, existing solutions rely heavily on bulky discrete components

Tianyu Ma, Yuchen Liu, Zhangfeng Gao, Zuokang Lin

Neutrons serve as unique probes for exploring the microscopic structure of matter, with the performance of a neutron source fundamentally governing the depth of scientific exploration and the breadth of industrial applicability. To address application demands including nuclear data measurement in the ultra-high-energy region, fundamental particle physics res

Chang He, Bo Jiang, Hongye Wang, Xihua Zhu

Quaternion optimization has attracted significant interest due to its broad applications, including color face recognition, video compression, and signal processing. Despite the growing literature on quadratic and matrix quaternion optimization, to the best of our knowledge, the study on quaternion polynomial optimization still remains blank. In this paper,

Nitin Kumar Singh, Arie Rachmad Syulistyo, Yuichiro Tanaka, Hakaru Tamukoh

Sign language recognition (SLR) facilitates communication between deaf and hearing individuals. Deep learning is widely used to develop SLR-based systems; however, it is computationally intensive and requires substantial computational resources, making it unsuitable for resource-constrained devices. To address this, we propose an efficient sign language reco

Yaxin Sun, I. S. Lobanov, Jiahao Su, Ho-Kin Tang

Controlling the magnetic properties of nanosystems by an electric field offers a number of advantages for spintronics applications. Using the noncollinear Alexander-Anderson model, we have shown that the interaction of localized magnetic moments formed by itinerant electrons strongly depends on the position of the d-level relative to the Fermi level, which d

Ruijia Liu, Ancheng Hou, Xiang Yin

Linear Temporal Logic (LTL) provides a rigorous framework for specifying long-horizon robotic tasks, yet existing approaches face a trade-off: model-based synthesis relies on accurate labeled transition systems, whereas learning-based methods often require online interaction, task-specific rewards, or specification-conditioned training. We study LTL-specifie

Jiasi Zhou, Huiyun Xia, Chuan Wu, Chintha Tellambura

Near-field spherical wavefronts enable spotlight-like beam focusing to mitigate unintended energy leakage, creating new opportunities for physical-layer security (PLS). However, under hybrid analog-digital (HAD) antenna architectures, beamfocusing alone may not provide foolproof privacy protection due to reduced focusing precision. To address this issue, thi

Toshiki Katsube, Taiga Fukuhara, Kenichiro Ando, Yusuke Mukuta

This work addresses the scarcity of high-quality, large-scale resources for Japanese Vision-and-Language (V&L) modeling. We present a scalable and reproducible pipeline that integrates large-scale web collection with rigorous filtering/deduplication, object-detection-driven evidence extraction, and Large Language Model (LLM)-based refinement under grounding

Hyunseok Ryu, Wonjune Shin, Hyun Park

Retrieval-Augmented Generation (RAG) is gaining recognition as one of the key technological axes for next generation information retrieval, owing to its ability to mitigate the hallucination phenomenon in Large Language Models (LLMs)and effectively incorporate up-to-date information. However, specialized expertise is necessary to construct ahigh-quality retr

Xiaoshan Wu, Yifei Yu, Xiaoyang Lyu, Yihua Huang

Robust 3D geometry estimation from videos is critical for applications such as autonomous navigation, SLAM, and 3D scene reconstruction. Recent methods like DUSt3R demonstrate that regressing dense pointmaps from image pairs enables accurate and efficient pose-free reconstruction. However, existing RGB-only approaches struggle under real-world conditions inv

Jiasi Zhou, Chintha Tellambura, Geoffrey Ye Li

Near-field integrated sensing and communication (ISAC) leverages distance-dependent channel variations for joint distance and angle estimation. However, full-digital architectures have prohibitive hardware costs, making hybrid analog-digital (HAD) designs the primary alternative. Nevertheless, such architectures compromise beamfocusing precision and lead to

Xingchen Zhou, Nan Li, Peng Jia, Yingfeng Liu

Source extraction is crucial in analyzing data from next-generation, large-scale sky surveys in radio bands, such as the Square Kilometre Array (SKA). Several source extraction programs, including SoFiA and Aegean, have been developed to address this challenge. However, finding optimal parameter configurations when applying these programs to real observation

Hamed Razavi

The fast growth of digital health systems has led to a need to better comprehend how they interpret and represent patient-reported symptoms. Chatbots have been used in healthcare to provide clinical support and enhance the user experience, making it possible to provide meaningful clinical patterns from text-based data through chatbots. The proposed research

Aditya Rallapalli, Suraj Kumar, Rijesh MP, C K Koteswar Rao

Recent successful lunar landing missions have generated significant interest among space agencies in establishing a permanent human settlement on the Moon. Building a lunar base requires multiple and frequent landing missions to support logistics and mobility applications. In these missions, maximizing payload mass defined as the useful cargo for human settl

Zenghui Zhou, Yuechen Li, Yi Cai, Jinlong Wen

Quantum computing is gaining attention from academia and industry. With the quantum Software Development Kits (SDKs), programmers can develop quantum software to explore the power of quantum computing. However, programmers may face challenges in understanding quantum software due to the non-intuitive quantum mechanics. To facilitate software development and

Haojie Ji, Te Hu, Haowen Li, Long Jin

Intelligent driving systems are vulnerable to physical adversarial attacks on traffic signs. These attacks can cause misclassification, leading to erroneous driving decisions that compromise road safety. Moreover, within V2X networks, such misinterpretations can propagate, inducing cascading failures that disrupt overall traffic flow and system stability. Ho

Myeongju Chae, Soyeun Jung

Within the framework developed in \cite{Gr, JLL, RT1}, we rigorously establish the nonlinear instability of roll solutions to the two-dimensional generalized Swift-Hohenberg equation (gSHE). Our analysis is based on spectral information near the maximally unstable Bloch mode, combined with precise semigroup estimates. We construct a certain class of small in

Robin Yadav, Shuo Xie, Tianhao Wang, Zhiyuan Li

Adaptive optimization methods (such as Adam) play a major role in LLM pretraining, significantly outperforming Gradient Descent (GD). Recent studies have proposed new smoothness assumptions on the loss function to explain the advantages of adaptive algorithms with structured preconditioners, e.g., coordinate-wise or layer-wise, and steepest descent methods w

Zhiyuan Gao, Jiageng Mao, Hong-Xing Yu, Haozhe Lou

A longstanding goal in computer vision is to model motions from videos, while the representations behind motions, i.e. the invisible physical interactions that cause objects to deform and move, remain largely unexplored. In this paper, we study how to recover the invisible forces from visual observations, e.g., estimating the wind field by observing a leaf f

Guangzhao Yang, Marek Gluza, Si Yan Koh, Kelvin Onggadinata

Semiconductor double quantum dot (DQD) qubits coupled via superconducting microwave resonators provide a powerful means of long-range manipulation of the qubits' spin and charge degrees of freedom. Quantum gates can be implemented by parametrically driving the qubits while their transition frequencies are detuned from the resonator frequency. Long-range two-

Subarna Khanra, Vijay Kumar Kukreja, Indu Bala

Demographic forecasting remains a fundamental challenge for policy planning in rapidly evolving nations such as India, where fertility transitions, policy interventions, and age structured dynamics interact in complex ways. In this study, we present a hybrid modelling framework that integrates policy-aware fertility functions into a Physics-Informed Neural N

Jiachen Li, Xu Duan, Shihao Li, Soovadeep Bakshi

We extend the Datamodels framework from supervised learning to Model Predictive Path Integral (MPPI) control. Whereas Datamodels estimate sample influence via regression on a fixed dataset, we instead learn to predict influence directly from sample cost features, enabling real-time estimation for newly generated samples without online regression. Our influen

Sungmoon Kim, Hyuna Jeon, Dahye Kim, Mingyu Kim

Retrieval-Augmented Generation (RAG) has emerged as a powerful approach for grounding Large Language Model (LLM)-based chatbot responses on external knowledge. However, existing RAG studies typically assume well-structured textual sources (e.g. Wikipedia or curated datasets) and perform retrieval and generation at query time, which can limit their applicabil

Yushen Wang, Weidong Mei, Xin Wei, Ya Fei Wu

Movable antenna (MA) technology exhibits great promise for enhancing the sensing capabilities of future sixth-generation (6G) networks due to its capability to alter antenna array geometry. With the growing prevalence of near-field propagation at ultra-high frequencies, this paper focuses on the application of one-dimensional (1D) and two-dimensional (2D) MA

Zongjian Han, Yiran Liang, Ruiwen Wang, Yiwei Luo

This paper presents a neural network filter method based on contraction operators to address model collapse in recursive training of generative models. Unlike \cite{xu2024probabilistic}, which requires superlinear sample growth ($O(t^{1+s})$), our approach completely eliminates the dependence on increasing sample sizes within an unbiased estimation framework

Ruihan Chen, Qiming Li, Xiaocheng Feng, Weihong Zhong

Large Vision-Language Models (LVLMs) have shown strong potential as multilingual Graphical User Interface (GUI) agents, as evidenced by existing GUI benchmarks. However, these benchmarks exhibit two primary limitations: (1) although Perception and Reasoning (P&R) capabilities are fundamental for GUI agents, current benchmarks lack fine-grained diagnostics to

Subham Kumar, Prakrithi Shivaprakash, Abhishek Manoharan, Astut Kurariya

Automatic Speech Recognition (ASR) is increasingly used to document clinical encounters, yet its reliability in multilingual and demographically diverse Indian healthcare contexts remains largely unknown. In this study, we conduct the first systematic audit of ASR performance on real world clinical interview data spanning Kannada, Hindi, and Indian English,

Antonin Sulc, Patrick L. S. Connor

This study presents an analysis of modern open-source large language models (LLMs) -- including Llama, Qwen, and Gemma -- to evaluate their encoded knowledge of Quantum Chromodynamics (QCD). Through reverse engineering of these models' representations, we uncover the naturally idiosyncratic patterns in how foundational QCD concepts are embedded within their

Shawn Li, Ryan Rossi, Sungchul Kim, Sunav Choudhary

Generative models, such as diffusion and autoregressive approaches, have demonstrated impressive capabilities in editing natural images. However, applying these tools to scientific charts rests on a flawed assumption: a chart is not merely an arrangement of pixels but a visual representation of structured data governed by a graphical grammar. Consequently, c

Mikhail Mints, Eric R. Anschuetz

In certain classes of physical quantum systems, the exponentially large state space "fragments" into many low-dimensional, dynamically disconnected subspaces. We introduce a learning problem known as fragment classification, where given a quantum state input, one is interested in classifying to which subspace the state belongs. We prove that solving this lea

Kishor Chaudhury, Abhradeep Roy, Varsha R. Chitnis, Prajval Shastri

We present the results of the multi-epoch broadband spectral study of 1ES 2344+514 and study the evolution of physical parameters. We used nearly simultaneous data obtained from 2017 June 6 to 2022 August 6 (MJD 57910 -- 59797) in optical, UV, X-ray and $\gamma$-ray wavebands from various instruments including Swift-UVOT, Swift-XRT, NuSTAR, AstroSat (SXT and

Gianluca Bande, Gregorio Franzoni

In this paper, after explaining some basic aspects of the modern theory of foliations with the aim of describing the celebrated Reeb foliation, we propose the first construction of a comprehensive physical model of it. The construction of the model is obtained by an implementation of geometric methods for 3D printing.

Ke Liu, Shangde Gao, Yichao Fu, Shuaike Shen

Lesion segmentation is inherently influenced by imaging uncertainty, arising from ill-defined lesion boundaries and inter-observer variability in diagnosis. To address this challenge, previous works formulated the multi-rater medical image segmentation task, where multiple experts provide separate annotations for each image. However, existing models are typi

Tingjun Zhang, Steven J. Gomez Alvarado, Sijie Xu, Thomas Hulse

We use inelastic neutron scattering (INS) and angle-resolved photoemission spectroscopy (ARPES) to study the impact of Li doping on the semiconducting altermagnet $\alpha$-MnTe. Introducing Li results in a spin reorientation from in-plane to out-of-plane direction and increases the density of itinerant carriers. While our ARPES measurements do not indicate a

Yusef Maleki, Luis D. Zambrano Palma, M. Suhail Zubairy

We investigate the information distribution among different entities in the weak measurements protocol. Focusing on multilevel, decaying systems under continuous (no-click) monitoring, we derive exact, conservation-type information relations that hold for each outcome in the record. Analogous relations hold when an explicit reversal is applied, with the reve

Md Abdullah Al Kafi, Sumit Kumar Banshal

This study proposes a language-agnostic transformer-based POS tagging framework designed for low-resource languages, using Bangla and Hindi as case studies. With only three lines of framework-specific code, the model was adapted from Bangla to Hindi, demonstrating effective portability with minimal modification. The framework achieves 96.85 percent and 97 pe

Zhengxin Chen, Xiaohai He, Tingrong Zhang, Shuhua Xiong

Recently, learned image compression methods have made remarkable achievements, some of which have outperformed the traditional image codec VVC. The advantages of learned image compression methods over traditional image codecs can be largely attributed to their powerful nonlinear transform coding. Convolutional layers and shifted window transformer (Swin-T) b

Qiang Lyu, Zicong Chen, Chongxiao Wang, Haolin Shi

Recently, Group Relative Policy Optimization (GRPO) has shown promising potential for aligning text-to-image (T2I) models, yet existing GRPO-based methods suffer from two critical limitations. (1) \textit{Shared credit assignment}: trajectory-level advantages derived from group-normalized sparse terminal rewards are uniformly applied across timesteps, failin

K. J. Kevin Feng, Tae Soo Kim, Rock Yuren Pang, Faria Huq

AI agents that take actions in their environment autonomously over extended time horizons require robust governance interventions to curb their potentially consequential risks. Prior proposals for governing AI agents primarily target system-level safeguards (e.g., prompt injection monitors) or agent infrastructure (e.g., agent IDs). In this work, we explore

Bojing Li, Duo Zhong, Dharani Nadendla, Gabriel Terceros

In recent years, the explosion of malware and extensive code reuse have formed complex evolutionary connections among malware specimens. The rapid pace of development makes it challenging for existing studies to characterize recent evolutionary trends. In addition, intuitive tools to untangle these intricate connections between malware specimens or categorie

Qingwen Yang, Feiyu Qu, Tiezheng Guo, Yanyi Liu

LLM-based multi-agent systems have demonstrated significant capabilities across diverse domains. However, the task performance and efficiency are fundamentally constrained by their collaboration strategies. Prevailing approaches rely on static topologies and centralized global planning, a paradigm that limits their scalability and adaptability in open, decen

Diyu Shen, Jinhui Chen, Xu-Guang Huang, Yu-Gang Ma

In heavy-ion collisions at relativistic energies, the incident nuclei travel at nearly the speed of light. These collisions deposit kinetic energy into the overlap region and create a high-temperature environment where hadrons ``melt'' into deconfined quarks and gluons. The spectator nucleons, which do not undergo scatterings, generate an ultra-intense elect

Paul Osemudiame Oamen, Robert Wesley, Pius Onobhayedo

Despite their evolution from early copper-token schemes to sophisticated digital solutions, loyalty programs remain predominantly closed ecosystems, with brands retaining full control over all components. Coalition loyalty programs emerged to enable cross-brand interoperability, but approximately 60\% fail within 10 years in spite of theoretical advantages r

G. Channagowdra, A. Singh, H. Y. Huang, M. Furo

An altermagnet is a recently identified class of magnets that exhibit a zero net magnetic moment but break symmetry under the combined operations of parity and time reversal. It typically consists of two magnetic sites of opposite spins related by rotation within the unit cell. Here, we use circular dichroism (CD) in resonant inelastic X-ray scattering (RIXS

Abdul Rab

A recently introduced two-phase flow model by Chun Shen is studied in this work. The model is derived to describe the dynamics of immersed water bubbles in liquid water as carrier. Several assumptions are made to obtain a reduced form of the mathematical model. The established model consists of nonlinear coupled PDEs in which the unknowns are the densities o

Jacob Thompson, Emiliano Garcia-Lopez, Yonatan Bisk

Humans build viewpoint-independent cognitive maps through navigation, enabling intuitive reasoning about object permanence and spatial relations. We argue that multimodal large language models (MLLMs), despite extensive video training, lack this fundamental spatial reasoning capability, a critical limitation for embodied applications. To demonstrate these li

S. K. Ivanov, A. V. Kireev, K. Sabour, N. S. Kostyuchenko

Topological dislocations in otherwise periodic lattices represent global structural defects that, nevertheless, typically leave the lattice periodicity intact far from the dislocation. Such dislocations arise in diverse physical systems ranging from crystalline solids, acoustic and photonic lattices and crystals to matter waves in optical lattices. Dislocati

Aaradhya Pandey, Arian Maleki, Sanjeev Kulkarni

Differential privacy is increasingly formalized through the lens of hypothesis testing via the robust and interpretable $f$-DP framework, where privacy guarantees are encoded by a baseline Blackwell trade-off function $f_{\infty} = T(P_{\infty}, Q_{\infty})$ involving a pair of distributions $(P_{\infty}, Q_{\infty})$. The problem of choosing the right priva

Ho-Lin Chen, Pin-Ju Huang

In this paper, we extend the discussion of the price of anarchy of machine scheduling games to a multi-stage machine setting. The multi-stage setting arises naturally in manufacturing pipelines and distributed computing workflows, when each job must traverse a fixed sequence of processing stages. While the classical makespan price of anarchy of $2 - \frac{1}

Ning Du, Yanlin Liu, Lei Zhang, Xiangcheng Zheng

Non-convex optimal control arises from various applications but may contain multiple stationary points. Classical solvers usually perform a ``local'' search near a saddle point or a local minimum, thus rely on good initial guess to reach the (quasi-)optimal control. We introduce a novel solution strategy for the non-convex optimal control of an elliptic equa

Shipeng Yao, Hao Sun, Zhang Liang, Zhen Wang

Erbium-based materials have long been recognized for their important telecom-band applications, yet their widespread adoption in integrated optoelectronics has been hindered by two fundamental limitations: the difficulty in achieving high erbium density without concentration quenching which leads to small optical gain in doped materials, and the difficulty i

Xuheng Ma

We determine the $z=6-8$ ultraviolet (UV) LF in the JWST UNCOVER field behind Abell 2744, through a depth-tied completeness model and source-plane selection taking multiple images into account. We compute the intrinsic $M_{UV}$ LFs and lens-dependent effective volumes $V_{eff,\ell}(M_{UV})$ for two of them (CATS, GLAFIC), and construct binned LFs with statis