April 2026 arXiv papers — page 8

Bahadur Yadav, Sanjay Kumar Mohanty

In finance, portfolio management is a traditional yet difficult problem that has drawn attention from practitioners and researchers for many years. However, there are still difficult technological problems that need to be solved. In the world of finance, managing a portfolio has never been easy. Selecting portfolios in a volatile market is made easier with t

Felipe H. Navarrete, Dominik R. G. Schleicher, Petri J. Käpylä, Marcel Völschow

The nature of eclipsing time variations (ETVs) in post-common-envelope binaries (PCEBs) is still unknown. Circumbinary planets routinely fail the test of time and the Applegate mechanism has energetic constraints and problems in reproducing observations. Based on recent analytic models of magnetically-induced ETVs and stellar dynamo simulations, we aim at ex

Zheng Liu, Ding-hui Xu, Yi-jia Yang, Chang-shui Yu

We present a transient quantum sensing framework for cavity-magnon systems that circumvents the inevitable loss of initial-state quantum properties plaguing conventional steady-state protocols. Explicitly incorporating finite-time dynamics and adopting an engineered steady state as the initial condition, we derive the exact transient noise spectrum. We show

Jullajak Karnjanaekarin, Pontakorn Trakuekul, Narongkorn Panitsrisit, Sumana Sumanakul

We present JaiTTS-v1.0, a state-of-the-art Thai voice cloning text-to-speech model built through continual training on a large Thai-centric speech corpus. The model architecture is adapted from VoxCPM, a tokenizer-free autoregressive TTS model. JaiTTS-v1.0 directly processes numerals and Thai-English code-switching, which is very common in realistic settings

Al Zadid Sultan Bin Habib, Tanpia Tasnim, Md. Ekramul Islam, Muntasir Tabasum

Learning informative representations from tabular data in remote sensing and environmental science is challenging due to heterogeneity, scarce labels, and redundancy among features. We present ZAYAN (Zero-Anchor dYnamic feAture eNcoding), a self-supervised, feature-centric contrastive framework for tabular data. ZAYAN performs contrastive learning at the fea

Yuki Nakanishi, Junki Tanaka, Atsushi Tamii, Shimpei Endo

We propose a method to probe weakly bound s-wave neutron components near the neutron emission threshold in heavy nuclei using Coulomb-assisted neutron transfer reactions. Weakly bound s-wave neutrons have large asymptotic amplitudes, which are difficult to access directly with conventional methods. This work focuses on the $(d,p)$ reaction at low incident en

Mohammad Partohaghighi

Information-theoretic generalization bounds analyze stochastic optimization by relating expected generalization error to the mutual information between learned parameters and training data. Virtual perturbation analyses of SGD add auxiliary Gaussian noise only in the proof, making mutual information tractable while leaving the actual SGD trajectory unchanged

Jingning Yao, Ajay Jasra, Sheng Jiang

In this paper we consider parameter estimation for discretely observed diffusion processes. In particular, we focus on data that are observed at low frequency and methodology that can estimate parameters with uncertainty quantification. Most statistical work in this domain develops advanced Markov chain Monte Carlo (MCMC) algorithms for sampling from the pos

Ziwei Ou, Jie Wang

Extended gamma-ray sources provide significant information about particle propagation. 4FGL J1626.0-4917 was labeled as an unassociated source in 4FGL catalog without known counterparts at other wavelengths. We report an analysis on 4FGL J1626.0-4917 with 17 years Fermi Large Area Telescope data and archival Chandra X-ray Observatory data. We find extended G

Xihang Wang, Zihan Wang, Chengkai Huang, Cao Liu

Multimodal Retrieval-Augmented Generation (MRAG) is widely adopted for Multimodal Large Language Models (MLLMs) with external evidence to reduce hallucinations. Despite its success, most existing MRAG frameworks treat retrieved evidence as indivisible documents, implicitly assuming that all content within a document is equally informative. In practice, howev

Gaurang Sharma, Juha Pajula, Aada Illikainen, Markus Rautell

Protecting sensitive health data while enabling collaborative analysis is a central challenge in healthcare. Traditional machine learning (ML) requires institutions to pool anonymized patient records, centralizing analytical development and privacy risks at a single site. Privacy-enhancing technologies (PETs), including Differential Privacy (DP) and Homomorp

Idoia Cortes Garcia, Jonas Pade

Field/circuit coupling is a common approach when a lumped representation of a certain electrotechnical device is not accurate enough. To exploit existing code and underlying properties of the coupled systems, cosimulation techniques such as waveform relaxation can be used. The coupled system is of differential-algebraic type, which can potentially lead to di

Hezhao Liu, Jiacheng Yang, Junlong Gao, Mengke Li

In open-world semi-supervised learning (OWSSL), a model learns from labeled data and unlabeled data containing both known and novel classes. In practical OWSSL applications, models are expected to perform rigorous classification by directly selecting the most semantically relevant label from a candidate set for each sample. Existing OWSSL methods fail to ach

Alberto Santonocito, Barbara Patrizi, Alessio Gabbani, Francesco Pineider

Tunable flat optics are essential for advancing compact photonic devices. Here we show a numerical study of a reflective magneto-optical metasurface with a dynamically tunable focal length. The structure comprises bismuth iron garnet nanodisks in a Gires-Tournois resonator configuration. The magneto-optical properties of the garnet modulate the reflected pha

Olivier Parisot

Recent technological advances in astronomy, particularly the growing popularity of smart telescopes for the general public, make it possible to develop highly effective detection solutions that are accessible to a wide audience, rather than being reserved for major scientific observatories. Published in 2023, DeepSpaceYoloDataset is a collection of annotated

Prachi Saini, Anupam Singh

Let $\mathcal A$ be an $\mathbb F$-algebra and $\omega \in \mathcal A\langle x_1, \ldots, x_m \rangle$ which defines a map $\mathcal A^m \rightarrow \mathcal A$ by evaluation, called a polynomial map with constant. We consider $\mathcal {A} = M_n(\mathbb{F})$, the algebra of $n \times n$ matrices over an algebraically closed field $\mathbb{F}$ of characteris

Ji-Hyeon Kim, Ho-Joong Kim, Seong-Whan Lee

Video moment retrieval is the task of retrieving specific segments of a video corresponding to a given text query. Recent studies have been conducted to improve multimodal alignment performance through visual-linguistic similarity learning at the snippet-level and transformer-based temporal boundary regression. However, existing models do not calculate simil

Davide Di Nucci, Riccardo Catalini, Guido Borghi, Roberto Vezzani

Recent advances in 3D reconstruction and neural rendering,particularly 3D Gaussian Splatting, make it feasible and simple to edit 3D scenes and re-render them as highly realistic images. Therefore, security concerns arise regarding the authenticity of 3D content. Despite this threat, 3D fake detection remains largely unexplored in the literature, and most ex

Zihan Jia, Ze Wang, Chen Chen, Ziren Xiao

The convergence of 5G and IoT enables fully connected, intelligent environments, but it faces challenges from the fragmentation of public/private 5G networks and the heterogeneity of IoT networks. We propose a unified framework using CAMARA open gateways, which provide standardized, open APIs to expose network capabilities, reducing fragmentation and simplif

César López-Pastor, Tatiana Pedraza, Jesús Rodríguez-López

We prove that the category of quasi-pseudometric modular spaces whose morphisms are the nonexpansive mappings is isomorphic to a quantale enriched category. To achieve this, we construct an appropriate quantale of isotone functions. We also show that, by means of this isomorphism, the topology associated with a quasi-pseudometric modular coincides with that

Shyam Kamal, Baby Diana, Sunidhi Pandey, Sandip Ghosh

This paper develops a sliding mode control based frame work for equality constrained optimization by reformulation the first order Karush Kuhn Tucker conditions as control affine dynamical system. The optimization variables are treated as states and the Lagrange multipliers as control input, with equality constraints defined as sliding manifold. The resultin

Anna Mazhar, Huzaifa Suri, Sainyam Galhotra

Reasoning over heterogeneous artifacts (PDFs, spreadsheets, slide decks, etc.) increasingly occurs within structured agent workflows that iteratively extract, transform, and reference external information. In these workflows, uncertainty is not merely an input-quality issue: it can redirect decomposition and routing decisions, reshape intermediate state, and

Jia-Xin Zhong, Chang Shu, Nan Cheng, Jee Woo Kim

In non-Hermitian systems, spectra can be maximally boundary-sensitive, yet bulk physics need not be. Here we experimentally show that spectral moments provide boundary-robust bulk observables in finite non-Hermitian lattices, even when the spectra undergo dramatic geometry-dependent reshaping due to the skin effect. Using a unified acoustic platform with ful

Nageen Pervaiz, Guo-Yin Zhang, Alexander Men'shchikov, Jin-Zeng Li

We present a comprehensive analysis of dense cores and filamentary structures in the M16 Eagle Nebula using high-resolution ($11.7^{\prime\prime}$) surface density and temperature maps derived from \textit{Herschel} observations. Using the \textit{hires} algorithm for map construction and the \textit{getsf} method for source and filament extraction, we ident

M. Riera-Marín, O. K. Sikha, J. Rodríguez-Comas, M. S. May

Surgical resection remains the only potentially curative treatment for pancreatic ductal adenocarcinoma (PDAC), and eligibility depends on accurate assessment of vascular invasion (VI), i.e., tumor extension into adjacent critical vessels. Despite its importance for preoperative staging and surgical planning, computational VI assessment remains underexplored

Taichi Miyagawa, Junki Tanaka, Shinsuke Ota, Masanori Dozono

The trade-off between angular resolution and acceptance in scattering-angle measurements with a magnetic spectrometer is quantitatively evaluated for the Large Acceptance Spectrometer (LAS). The dependence on the multipole magnet field strength is investigated. Third-order transfer matrices were calculated with GICOSY, and particle transport was simulated wi

Yiyang Wei, Tingyu Song, Siyue Zhang, Yilun Zhao

Reasoning-Intensive Retrieval (RIR) targets retrieval settings where relevance is mediated by latent inferential links between a query and supporting evidence, rather than semantic similarity. Motivated by the emergent reasoning abilities of Large Language Models (LLMs), recent work integrates these capabilities into the IR field, spanning the entire pipelin

Yanyu Cheng, Haitao Du, Liqin Hu, Wei Yang Bryan Lim

In this paper, we propose an enhanced physical layer security approach, named joint secrecy and covert communication (JSACC), which aims to improve the performance of physical layer security (PLS). The JSACC system can dynamically switch between secrecy mode and covert mode according to the channel difference between legitimate and illegitimate receivers. We

Lechao Zhang, Haoran Xu, Jingyu Gong, Xuhong Wang

Embodied intelligence requires high-fidelity simulation environments to support perception and decision-making, yet existing platforms often suffer from data contamination and limited flexibility. To mitigate this, we propose World2Minecraft to convert real-world scenes into structured Minecraft environments based on 3D semantic occupancy prediction. In the

Mandeep Rathee, V Venktesh, Sean MacAvaney, Avishek Anand

The classical cascading pipeline of retrieve--rerank suffers from a bounded recall problem, stemming from limitations of the first-stage retriever. Most current approaches address the bounded recall problem by improving the first-stage retriever, but this incurs substantial training and inference costs, especially to handle queries that require substantial r

Samuel Pastva, Van-Giang Trinh

We present BAss (BDD-based ADF symbolic solver), a novel analysis tool for Abstract Dialectical Frameworks (ADFs) based on Binary Decision Diagrams (BDDs). It supports the fully symbolic computation of all admissible, complete, and preferred interpretations, as well as two-valued and stable models of an ADFs. Our approach is inspired by the recently discover

Zhenzhou Jin, Li You, Xiang-Gen Xia, Xiqi Gao

Channel fingerprint (CF) is considered a key enabler for facilitating the acquisition of channel state information (CSI) in massive multiple-input multiple-output (MIMO) communication systems. In this work, we investigate a novel type of CF that stores statistical CSI (sCSI) at each potential location, referred to as statistical CF (sCF). Specifically, we re

Yilin Wang, Haojie Huang, Chen Li, Yang Li

Sand painting is a process-driven art where visual appearance emerges from granular accumulation. Given a single image, reconstructing a plausible sand painting process requires modeling coherent stroke structures and material-dependent effects. Existing methods, including stroke-based optimization and diffusion-based video synthesis, often lack structural c

Lin Chen, Tingwei Hu, Yuchen Mao, Yong Chen

In the bottleneck multiple knapsack problem, we are given a set of items and a set of knapsacks, where each item has a profit and a weight, and each knapsack has a capacity. Our goal is to assign items to knapsacks so as to maximize the minimum profit received by any knapsack subject to the capacity constraint. When all knapsacks have identical capacity, we

Zhe Wang, Mahmoud Zaher, Vitaly Petrov, Emil Björnson

This paper studies flexible non-uniform array design for monostatic integrated sensing and communication (ISAC) systems. An antenna pool is considered at the base station, where each candidate antenna can be dynamically assigned to transmit, receive, or inactive modes, such that a non-uniform effective array is jointly constructed with the ISAC precoding des

Antoine Lavandier, Bastien Buil, Chrystel Gaber, Emmanuel Baccelli

Software stacks embedded on microcontroller-based hardware typically provide rudimentary APIs programmed in C/C++, basic connectivity and, sometimes, a firmware update mechanism. Such coarse mechanisms contrast with widely used APIs and more advanced networked interaction expected from software stacks deployed on less resource-constrained hardware (microproc

Kanghyun Wi, Hyoeun Kim, Tomáš Mrkvička, Jorge Mateu

Reliable inference for spatial regression remains challenging because it requires the correct specification of the spatial dependence structure, the mean trend, and the error distribution. Existing parametric testing methods rely on restrictive assumptions that are difficult to verify in practice and can lead to inaccurate conclusions under misspecification.

Robin Valtin, Alexander Ganz, Guillem Domènech

The Paneitz operator is a dimension-4 conformally invariant fourth-order differential operator that has recently attracted attention for possible cancellations of the vacuum energy. We show that, in four dimensions, the Paneitz operator acting on a scalar field falls within the class of extended mimetic gravity theories. Thus, it exhibits the usual instabili

Ze-Shan He, Yukuan Zhao, Hao-Shu Tian, Kai Sun

Quantum universal invariants of a Gaussian state's covariance matrix, which can be derived from intensity correlation moments, have been adopted to characterize the entanglement properties of Gaussian states via the positive partial transpose criterion, also known as the Peres-Horodecki separability criterion. Such intensity correlation moments enable the ex

Enrico Maria Del Regno

We prove a conjecture of Paquette, Rock, and Yildirim by showing that, for every thread quiver, the abelian category of pointwise finite dimensional representations is hereditary. Since this category typically lacks enough projectives and injectives, standard homological methods do not apply directly. Our approach combines a Yoneda Ext criterion for heredita

Zi-Xu Lu, Gang Liu, Matteo Fadel, Jie Li

Bosonic quantum error correction encodes a logical qubit in an oscillator, avoiding the hardware overhead of large qubit arrays. Among such encodings, Gottesman-Kitaev-Preskill (GKP) states are paticularly powerful because their phase-space grid structure protects against small displacement errors simultaneously in both conjugate quadratures. Here we provide

Branislav Kveton, Michal Valko

Face recognition from a single image per person is a challenging problem because the training sample is extremely small. We consider a variation of this problem. In our problem, we recognize only one person, and there are no labeled data for any other person. This setting naturally arises in authentication on personal computers and mobile devices, and poses

Mohammad Ghavamzadeh, Yaakov Engel, Michal Valko

Policy gradient methods are reinforcement learning algorithms that adapt a parameterized policy by following a performance gradient estimate. Conventional policy gradient methods use Monte-Carlo techniques to estimate the gradient, which tend to have high variance, requiring many samples and resulting in slow convergence. We first propose a Bayesian framewor

Branislav Kveton, Michal Valko, Matthai Phillipose, Ling Huang

This paper proposes an algorithm for real-time learning without explicit feedback. The algorithm combines the ideas of semi-supervised learning on graphs and online learning. In particular, it iteratively builds a graphical representation of its world and updates it with observed examples. Labeled examples constitute the initial bias of the algorithm and are

Yashuang Zhao, Shijun Li, Shaopeng Xu

\indent In this paper, we study a class of parabolic-elliptic Keller-Segel systems with diffusion sensitivity dependent on spatial position, given by type \begin{equation} \left\{ \begin{array}{ll} u_{t} = \bigtriangledown\cdot(|x|^{\beta} \bigtriangledown u)-\bigtriangledown\cdot(u^{\alpha} \bigtriangledown v), 0=\bigtriangleup v-\mu +u, \qquad \mu:=\frac{1

Arnaud Valence

Boolean circuits form the foundational computational substrate of symmetric cryptography, yet the exploration of their architectural design space has remained largely confined to a handful of canonical paradigms - SPN, Feistel networks, and their immediate variants. This paper takes a deliberately broader perspective by formalizing the design space of crypto

Yucheng Chen, Yang Yu, Yufei Shi, Conghao Xiong

Radiology report generation (RRG) has emerged as a promising approach to alleviate radiologists' workload and reduce human errors by automatically generating diagnostic reports from medical images. A key challenge in RRG is achieving fine-grained alignment between complex visual features and the hierarchical structure of long-form radiology reports. Although

Pauliina Hirvi, Jaakko Olkkonen, Qianqian Fang, Ilkka Nissilä

Significance: Jacobians, or spatially resolved sensitivity profiles, are central to image reconstruction in model-based optical tomography of biological tissue. Although Monte Carlo (MC) simulations are the gold standard for modeling light transport in turbid media, methodology for frequency- and time-domain Jacobians remains incomplete. Aim: This work exten

Mohammad Amin Mirzaee, Harsh Gupta, Wenzhen Yuan

Despite advances in dexterous hand manipulation, robotic hand design is still largely decoupled from task-driven evaluation and control, limiting systematic optimization. Existing robotic hand co-design approaches are often limited in scope, optimizing a small subset of design parameters. We introduce a comprehensive parametric framework for robotic hand gen

Luca Rossi

We address the question of the large-time behavior of solutions to reaction-diffusion equations in periodic media. We start with the description of the asymptotic shape of the invasion set, which is characterized by the Freidlin-G\"artner formula. We outline a proof of the formula that holds true for general types of reaction terms. We then present some rece

Song Tang, Kaiyong Zhao, Yuliang Li, Qingsong Yan

Automatically generating interactive 3D indoor scenes from natural language is crucial for virtual reality, gaming, and embodied AI. However, existing LLM-based approaches often suffer from spatial errors and collisions, in part because common scene representations-raw coordinates or verbose code-are difficult for models to reason about 3D spatial relationsh

Hirofumi Wada, Hayato Mizobata, Shuto Ueno, Taiju Yoneda

{\it Jacob's ladder} -- a classic children's toy -- is a simple mechanical frame comprising rigid blocks connected by strings that shows curious unidirectional flipping waves. Nonetheless, its physical origin remains elusive. By combining experiment, numeral simulation, and theory, we show that understanding the underlying design principle of this toy requir

Xiaomeng Wang, Martha Larson, Zhengyu Zhao

When the visual style of text is considered, a wide variety can be observed in font, color, and size. However, when a word is read, its meaning is independent of the style in which it has been written or rendered. In this paper, we investigate whether, and how, the style in which a word is visualized in an image impacts the description that a Large Visual La

Jian Lin, Jiancheng Fang, Shaoyu Wang, Changan Lai

While 3D Gaussian splatting (3DGS) offers explicit and efficient scene representations for cone-beam computed tomography reconstruction, conventional photometric optimization inherently suffers from spectral bias under ultra sparse-view conditions, leading to over-smoothing and a loss of high-frequency anatomical details. Since wavelet transforms provide ric

Henrik Voigt, Michael Habeck, Joachim Giesen

Large-scale transformers achieve impressive results on program synthesis benchmarks, yet their true generalization capabilities remain obscured by data contamination and opaque training corpora. To rigorously assess whether models are truly generalizing or merely retrieving memorized templates, we introduce a strictly controlled program synthesis environment

Pengyun Zhu, Qiheng Sun, Long Wen, Yanbo Wang

Privacy policies are essential for users to understand how service providers handle their personal data. However, these documents are often long and complex, as well as filled with technobabble and legalese, causing users to unknowingly accept terms that may even contradict the law. While summarizing and interpreting these privacy policies is crucial, there

Chunjin Li, Shijun Li, Shaopeng Xu

We consider a class of nonlinear parabolic equations \[ \dfrac{\partial}{\partial t} b(u)-\nabla \cdot (A(x,t,u,\nabla u))+H(x,t,\nabla u)=f , \] where $H$ is a nonlinear lower order term satisfied the Carath$\acute{e}$odory condition and \[ \left\lvert H(x,t,\nabla u)\right\rvert\leqslant g(x,t)\left\lvert \nabla u\right\rvert^{\delta(x)} \] with \[ \delta

Saeid Asgari Taghanaki, Rakshanda Agarwal, Bruce Sun, Rohan Jha

Fine-tuning large language models (LLMs) for domain-specific tasks requires training datasets that comprehensively cover the target capabilities a practitioner needs. Yet identifying which capabilities a dataset fails to support, and doing so before an expensive fine-tuning run, remains a largely unsolved problem. We introduce GoalCover, a framework that hel

Bo Hou, Yuanchang Lin

There is a Lie algebra structure on the tensor product of a Leibniz algebra and a Zinbiel algebra for the operads of Leibniz algebras and Zinbiel algebras are Koszul dual. In this paper, we extend such conclusion to the context of bialgebras. We show that there is a Lie bialgebra structure on the tensor product of a Leibniz bialgebra and a quadratic Zinbiel

Maria Teresa Mercaldo, Mario Cuoco, Carmine Ortix

Optoelectronic and nonlinear transport experiments probe the quantum geometric tensor of Bloch states, whose real and imaginary components -- the quantum metric and the Berry curvature -- are typically constrained by symmetry. Here, we show that geometric bending provides a route to engineer such responses in centrosymmetric ferromagnets. Curvature-induced s

Eugen Beck, Sarah Beranek, Uma Moothiringote, Daniel Mann

Evaluating English ASR systems for conversational AI applications remains difficult, as many publicly available corpora are either pre-segmented into short segments, consist of read or prepared speech, or lack explicit dialect annotations to evaluate robustness for a diverse user base. This work presents the AppTek Call-Center Dialogues corpus, a collection

Thibault Bañeras Roux, Jane Wottawa, Mickael Rouvier, Teva Merlin

Conventionally, Automatic Speech Recognition (ASR) systems are evaluated on their ability to correctly recognize each word contained in a speech signal. In this context, the word error rate (WER) metric is the reference for evaluating speech transcripts. Several studies have shown that this measure is too limited to correctly evaluate an ASR system, which ha

Irene Celino

As information ecosystems grow more heterogeneous, both humans and artificial agents increasingly face a simple yet unresolved question: when seeking knowledge, whom should we ask, and why? Inspired by how people intuitively "read a room", this paper introduces the concept of knowledge affordance (KA) to systematize how agents identify meaningful opportuniti

Jingya Li, Ye Ji, Hugo Verhelst, Henk den Besten

Body-fitted arbitrary Lagrangian-Eulerian (ALE) methods provide a sharp representation of the fluid-structure interface but rely on mesh-update strategies that incrementally deform a reference configuration. To address this issue, we reformulate the ALE mesh-motion problem in the isogeometric setting as a sequence of independent domain parameterization probl

Wenhao Yuan, Chenchen Lin, Jian Chen, Jinfeng Xu

In black-box large language model (LLM) services, response reliability is often only partially observable at decision time, while stronger inference pathways incur substantial computational cost, inducing a budgeted sequential decision problem: for each request, the system should decide whether the default low-cost response is sufficiently reliable or whethe

Luyi Li, Yubo Wang, Guiying Yan

Let $ n \in \mathbb{N} $ with $ n \geq 3 $, and let $\mathcal{G} = \{G_i:i\in [n]\} $ be a family of $ n $-vertex graphs on a common vertex set $V$, where the graphs in the family do not need to be distinct. A graph $H$ with vertex set $V$ is \emph{rainbow} in $\mathcal{G}$ if there exists an injection $ \phi: E(H) \to [n] $ such that $e \in E(G_{\phi(e)})$

Anton Lavreniuk, Mykyta Mudryi, Markiian Chaklosh

In natural language processing, the entropy of a language is a measure of its unpredictability and complexity. The first study on this subject was conducted by Claude Shannon in 1951. By having participants predict the next character in a sentence, he was able to approximate the entropy of the English language. Several follow-up studies by other authors have

Thibault Bañeras-Roux, Mickaël Rouvier, Jane Wottawa, Richard Dufour

Evaluating automatic speech recognition (ASR) systems is a classical but difficult and still open problem, which often boils down to focusing only on the word error rate (WER). However, this metric suffers from many limitations and does not allow an in-depth analysis of automatic transcription errors. In this paper, we propose to study and understand the imp

Jipeng Tan, Mengye Yang, Zhanghao Li, Yong Min

News consumption behavior is shaped by the coupling between temporal dynamics and content selection. This study proposes a multi-scale temporal-content framework and validates it on two large real-world news datasets, MIND and Adressa. Results reveal hierarchical temporal patterns. At the macroscale, Fourier modeling identifies clear circadian rhythms; at th

Kaixiang Shu

A foundational assumption in CNN interpretability -- that deep encoders suppress background pixels while classifiers merely select from a cleaned feature pool (the Spatial Funnel Hypothesis) -- remains untested due to spatial hallucinations in existing visualization tools. We address this by introducing a hallucination-free inversion framework built on magni

Lidia Angeleri Hügel, Andrew Hubery, Henning Krause

A self-contained introduction to infinite dimensional representations over a tame hereditary algebra is provided, assuming a basic knowledge of the category of finite dimensional representations. This includes a complete description of all pure-injective modules. Of particular interest are the torsionfree divisible modules, which are precisely the direct sum

Raymond Chou

We define a torus $U \subset T = (\mathbb{C}^\times)^K$ which acts on the $\Delta$-Springer varieties $Y_{n,\lambda,s}$ defined by Griffin-Levinson-Woo and give a Borel-style presentation for the equivariant cohomology ring $H^*_U(Y_{n,\lambda,s})$. Our presentation arises from the orbit harmonics deformation technique, and uses methods of Chou-Matsumura-Rho

Ignat Soroko, Nicolas Vaskou

We give a unified proof of property $R_\infty$ for the Higman groups $H_n$ ($n\ge 4$) and for their generalizations studied by Martin and Horbez--Huang. As a key step, we prove that the automorphism groups of these groups are acylindrically hyperbolic. As a byproduct, we obtain acylindrical hyperbolicity of the groups themselves. In addition, we give an inde

Shiva Meucci

We prove that the Lorentz--FitzGerald contraction is the unique deformation of a resonant cavity moving through a mechanical wave medium that preserves spherical-harmonic phase closure. For a cavity moving at speed $v = \beta c$ through a medium supporting nondispersive wave propagation at speed $c$, the round-trip phase of an internal ray at angle $\theta$

D. Choi, M. Först, M. Fechner, M. Buzzi

Piezoelectricity is a technologically important property of certain insulators in which mechanical strain induces an electrical polarization. However, the rate at which a piezoelectric response can be established over a macroscopic volume is limited by the sound velocity, constraining applications in high-bit-rate transduction and sensing. Furthermore, the s

Jiahui Zhuo, Arantza Oyanguren, Álvaro Fernández Casani, Luca Fiorini

In this paper we introduce the energy efficiency as a new metric for evaluating both hardware platforms based on Graphic Processor Units (GPU), and algorithm optimisations at High Energy Physics (HEP) experiments. We develop a method to compute the energy efficiency for the case of the first high level trigger (HLT1) of the LHCb experiment, relating the thro

Ramesh Kasilingam

This paper provides a diffeomorphism classification of smooth manifolds homeomorphic to the complex projective space $\mathbb{C}P^m$ for $m \in \{5, 6, 7, 8\}$. The classification is obtained by computing the group of concordance classes of smooth structures on $\mathbb{C}P^m$ and determining the orbit space under the action induced by the group of self-home

Shota Shibasaki, Wakaba Tateishi, Shuhei Fujii, Ryosuke Nakadai

The tragedy of the commons has traditionally been framed as a problem of resource overuse driven by self-interested exploitation. In contrast, growing empirical evidence shows that insufficient use or abandonment of natural resources, known as underuse, can also lead to ecological degradation and loss of ecosystem services. Despite its relevance, underuse ha

Felix Otto, Matteo Palmieri

Motivated by an optimal-matching problem (Leighton-Shor) and the random-field Ising model (Aizenman-Wehr, Ding-Wirth), we consider a variational problem for graphs in $1+1$ dimension maximizing an action that is the difference of a field term given by integrating white noise over the subgraph on the one hand, and the Dirichlet integral of the (continuum) hei

Evan Grand, Michael Klamkin

This paper presents lpviz, a browser-based visualization tool for linear programming. lpviz is deeply interactive, offering an intuitive interface where users can directly draw and edit the feasible region and objective vector, without requiring cumbersome manipulation of raw numerical coefficients. lpviz lets users compare the behavior of several classes of

Sumin Lee

Digital journaling creates an authenticity gap: users consciously translate raw emotions into text, often sanitizing narratives even in private writing. We formalize this as Cross-Modal Affective Dissonance Detection (CADD), a directional three-way classification distinguishing Masking (positive text, negative acoustics), Coping (negative text, positive acou

Anders Björn, Jana Björn

In this paper we study when the origin $(0,0)$ is a regular (or irregular) boundary point for the so-called soda can domains of the type \[ \Theta_{l,\theta}:= \{(x,t) \in \mathbf{R}^{n+1}: 0<-t < \theta |x|^l <\theta\}, \quad \text{with $l,\theta >0$,} \] for the $p$-parabolic equation $\partial_t u- \Delta_p u=0$, where $1<p<\infty$. For $p<2n/(n+1)$ and f

Mateusz Michałek, Leonid Monin, Botong Wang

Let $P\subset\mathbb R^n$ be a convex polytope and let $\ell$ be a linear functional which is nonconstant on every edge of $P$. The induced acyclic orientation determines positive and negative Bia{\l}ynicki-Birula type partitions of $P$ into unions of relative interiors of faces. Our first result establishes a duality: the positive partition is a stratificat

Wen-Xin Zhang, Yong Chen

This paper develops the numerical inverse scattering transform (NIST) framework for the coupled modified Korteweg-de Vries (mKdV) equation based on its associated Riemann-Hilbert problem. The coupled system gives rise to a $3\times3$ matrix-valued Riemann-Hilbert problem, whose jump matrix and scattering data have a more involved structure than in the scalar

Bikram Bir, Amiya K. Pani

Based on a discontinuous Galerkin method in the spatial directions and an improved implicit-explicit pressure-correction scheme in the temporal direction, this paper discusses a fully discrete scheme for the Poisson-Nernst-Planck-Navier-Stokes equations. Optimal error estimates are derived in $L^2$ and in the energy norms for the concentrations of positive a

Sangwoo Park, Arman Shafieloo, Alex G. Kim, Eric V. Linder

We present a model-independent, photometry-only framework for identifying strongly lensed supernovae when multiple images are unresolved and blended into a single point source. Building on the simulation-based methodology of Bag et al. (2021), we apply this approach to real Zwicky Transient Facility (ZTF) data using a validation sample of spectroscopically c

Mahad Ali, Laura J. Brattain

Federated Learning (FL) enables collaborative model training across distributed clients without sharing raw data, yet its performance deteriorates under statistical heterogeneity. Clustered Federated Learning addresses this challenge by grouping similar clients and training separate models per cluster. However, existing clustering strategies often rely on ra

Syed Pouladi

This paper addresses the stability analysis and state estimation of generalized Persidskii systems subject to time-varying delays and external disturbances. The generalized Persidskii class, which couples linear dynamics with sector-bounded nonlinear feedback loops, offers a tractable yet expressive framework for modeling electromechanical and neural network

Yongpeng Cao, Masahiro Hirano, Hyuno Kim, Yuji Yamakawa

Understanding human actions is critical for advancing behavior analysis in human-robot interaction. Particularly in tasks that demand quick and proactive feedback, robots must recognize human actions as early as possible from incomplete observations. \textit{Sub-actions} offer the semantic and hierarchical cues needed for this, since human actions are inhere

Yiran Du, Huimin He

This study examined university students' discontinuance intention towards AI-mediated informal digital learning of English (AI-IDLE). Drawing on the cognition-affect-conation framework, the study investigated how three cognitive factors, namely disconfirmation, perceived complexity, and perceived risk, influence two affective responses, namely dissatisfactio

Hankyeol Lee, Wooyeol Baek, Seongdo Kim, Jongyoo Kim

Recent generative models have shown strong performance in generating diverse 3D assets from 2D images, a fundamental research topic in computer vision and graphics. However, these models still struggle to generate voluminous 3D assets when the input is a flat image that provides limited 3D cues. We introduce REVIVE 3D, a two-stage, plug-and-play pipeline for

Karan Dogra, Alok C. Gupta, C. M. Raiteri, M. Villata

We analyzed 19 years of $R$-band data of the blazar 3C 454.3 from the Whole Earth Blazar Telescope (WEBT) archive, along with new data from its members and from public archives such as those provided by the Small and Moderate Aperture Research Telescope System (SMARTS) and the Steward Observatory projects to search for quasi-periodic oscillations (QPOs). We

P. U. Devanand, Alok C. Gupta, Paul J. Wiita, V. Jithesh

We present an extensive X-ray spectral variability study of the TeV photon-emitting high-energy-peaked BL Lacertae object PG 1553+113, using the data from EPIC-PN camera of XMM-Newton, which observed the source during its operational period from Sep 2001 to Nov 2024. X-ray spectra in this energy range, $0.6-7.0$ keV, were fitted with absorbed Power-law (PL)

Mark Lewko

Let $F$ be a finite field of odd characteristic. We prove that any set $A\subset F$ with $|A|\geq C|F|^{5/6}$ contains a nontrivial quadratic progression $(x, x+y, x+y^2), y\neq 0.$ For prime fields, this improves the previous best-known exponent of $7/8$, due to Kavrut and Wu. Unlike some of the previous papers, which rely on Katz's deep multivariate expone

Shuo Wang, Jilin Mei, Wenfei Guan, Shuai Wang

Off-road nighttime autonomous driving suffers from unreliable visible-light perception, making infrared modality crucial for accurate freespace detection. However, progress remains limited due to the scarcity of annotated infrared off-road datasets and the inter-frame inconsistencies inherent to current single-frame methods. To address these gaps, we present

Nel Escher, Bakyt Yrysov, Ashley McDermott, Daniel Chechelnitsky

Though online platforms claim to amplify Indigenous voices, Indigenous communities are worried that these systems are instead eroding their language and culture. We conduct a community-informed algorithmic audit to explore whether online platforms sustain or endanger Indigenous cultural practice. First, we review ethnographic research pertaining to the cultu

Muhammad Jazlan, Alexander Gamero-Garrido, Zubair Shafiq, Yash Vekaria

As web browsers increasingly restrict client-side tracking, the web tracking ecosystem is shifting from client-side to server-side tracking (SST). In SST, the browser sends tracking requests to an intermediate endpoint, which then forwards them to the tracker's endpoint, eliminating direct client-to-tracker requests. As a result, existing tracking protection

Gabriele Franciolini, Nadir Ijaz, Marco Peloso

We revisit the production of primordial black holes (PBHs) by a U(1) gauge field with a pseudo-scalar coupling to the inflaton. We improve upon the existing literature by working in the homogeneous backreaction regime with numerically computed gauge mode functions, adopting state-of-the-art PBH abundance calculations, and incorporating the uncertainty in the

Kazutoshi Shinoda, Kosuke Nishida, Kyosuke Nishida

Reward models (RMs) play a central role in aligning large language models (LLMs) with human preferences. However, RMs are often sensitive to spurious features such as response length. Existing inference-time approaches for mitigating these biases typically focus exclusively on response length, resulting in performance trade-offs. In this paper, we propose ca

Yu Gu, Yuhan Ma, Yiqi Song, Meixue Chen

Understanding the boundary between classical and nonclassical phenomena is important for both fundamental researches in quantum optics and applications in quantum information. One of the most interesting research directions in this field is exploring nonclassical effects with classical light. In this paper, we will show that it is possible to observe antibun