April 2026 arXiv papers — page 85

Sofiane Bouarroudj, Jiefeng Liu, Liwen Zhang

In this paper, we first introduce the notion of a hyper relative differential operator on a Lie algebra, in which Nijenhuis operators are used to characterize the relative differential operators and their inverse. We then introduce the notions of DN-structures, KN-structures, and KD-structures on Lie algebras and study the relationships between DN-structures

Utsab Saha, Lola Egherman, Ramiz Rahman, Mohd Toukir Khan

Undergraduates in work-based learning experiences often produce meaningful contributions as viewed by their supervisors, yet report a negative perception of their contributions because they struggled during the process or produced only a few lines of code change. As a result, many omit these contributions from their resumes and job interviews, losing a meani

Eunsik Choi, Jungin E. Kim, Xueling Lu, Yan Wang

Quantum scientific computing is to solve engineering and science problems such as simulation and optimization on quantum computers. Solving ordinary and partial differential equations (PDEs) is essential in simulations. However, existing quantum approaches to solve nonlinear PDEs suffer from the issues of curse of dimensionality and convergence during the li

Katharine Woo

We study sums of absolute values of Hecke eigenvalues of $\textrm{GL}(2)$ representations that are tempered at all finite places. We show that these sums exhibit logarithmic savings over the trivial bound if and only if the representation is cuspidal. Further, we connect the problem of studying the sums of Hecke eigenvalues along polynomial values to the bas

Douglas Stryker

We give a proof that every complete two-sided stable minimal surface in $\mathbb{R}^3$ is flat using the index theory for Dirac operators on twisted spinor bundles.

Yuan Tian, Yiru Chen, Rakesh R. Menon, Zifan Liu

LLM-based agents are increasingly being deployed for data-related tasks, including data sense-making, exploration, and retrieval. However, their performance heavily depends on the clarity and completeness of data semantics. In practice, many field descriptions remain ambiguous or incomplete, as much of the essential context (e.g., the meaning of a customized

Donghan Wu, Pengcheng Xie

Model-based derivative-free optimization relies on quadratic interpolation, but maintaining these models typically requires $\mathcal{O}(m^3)$ linear system solves. We show that for the least Frobenius norm updating model, the associated KKT matrix possesses a fixed inner-product structure. Both single-point replacements and a proposed coordinate-axis flippi

Vanessa Figueiredo, Wilter Franceschi

Reliability in large language model (LLM) systems is typically framed as a function of model capability. We challenge this by demonstrating that reliability is significantly influenced by \emph{inference-time control} -- the computational layer governing task framing and context selection. We introduce \emph{CogniConsole}, an architectural instantiation that

Poonam Yadav, Yifan Liu, Mohit Bidikar, Rana M. Sohaib

As 6G networks continue to evolve, the Open Radio Access Network (ORAN) framework is gaining prominence for its promise of network flexibility, vendor-neutral architecture, and enhanced service delivery. However, achieving true interoperability across diverse hardware and software components from multiple vendors remains a critical challenge. This research f

Alexandra V. Antoniouk, Anatoly N. Kochubei

We prove the monotone dependence of the heat kernel corresponding to the Vladimirov-Taibleson non-Archimedean fractional differentiation operator $D^α$ on the order $α$.

Danila Valko, Jorge Marx Gómez

The Lightning Network (LN) is a rapidly evolving payment channel network that enables scalable, off-chain transactions on top of Bitcoin. While prior research has documented its topological structure and liquidity concentration, the joint relationships between node lifetime, connectivity, and capacity remain insufficiently understood. This study provides a c

Sahil Rajesh Dhayalkar

Modern artificial intelligence remains fundamentally divided between the continuous, probabilistic spaces of Foundation Models and the discrete, deterministic structures of Knowledge Graphs. While Retrieval-Augmented Generation (RAG) attempts to connect them by serializing graph data into text, we argue this lexical bridging is merely a superficial patch. In

Chenyang Yang, Shen Yan, Yibo Yang, Litao Hu

Generative AI has enabled the creation of photorealistic images and videos that are increasingly disseminated on social media, often used for spam, misinformation, manipulation, and fraud. Existing AI-generated content (AIGC) detection methods face challenges including poor generalization to new generation models, reliance on single modalities, and lack of i

Quentin Fever, Naziha Aslam

We present NightFeats, a structured multi-agent retrieval-augmented generation (RAG) system submitted to the MMU-RAGent competition at NeurIPS 2025, where it was awarded Best Dynamic Evaluation in the text-to-text track. Rather than targeting benchmark maximization, this work proposes a principled pipeline that decomposes knowledge synthesis into three coord

Yuqi Zhang, Di Zhang

Retrieval-augmented generation (RAG) systems inject external knowledge to improve LLM outputs, yet the format of injected content -- distinct from its semantic relevance -- can independently distort the model's attention distribution. We identify and formalise a phenomenon we term the structural attention tax: knowledge graph (KG) triples, due to their r

Yue Zhao, Hongyan Li, Yong Chen, Luo Ji

Emotional interaction is increasingly crucial for conversational AI, yet current systems lack a self-emotion determination mechanism to drive the streaming text-to-speech (TTS) synthesis. We propose an emotion-planning framework that determines the emotion prior to the textual generation, grounding the downstream emotional TTS in a streaming manner. The fram

Ritvik Pandey, Sid Manchkanti, Mohammed Wazir Adain, Mohammed Hadi

We introduce PulseBench-Tab, an open multilingual benchmark for evaluating table extraction from document images. The benchmark comprises 1,820 human-annotated tables spanning 9 languages and 4 scripts (Latin, CJK, Arabic, Cyrillic), drawn from 380 real-world source documents including financial filings, government reports, and regulatory disclosures. Tables

Paweł Pozorski, Jakub Muszyński, Maria Ganzha

Multimodal Large Language Models (MLLMs) effectively integrate text and audio to interpret context in complex interactive dialogues. However, the internal mechanisms by which heterogeneous modalities influence model behavior remain opaque. While Shapley Values (SV) provide a robust, model-agnostic framework for local explainability in text-based NLP, their e

Jakub Muszyński, Paweł Pozorski, Maria Ganzha

We introduce mllm-shap, an open-source Python framework designed to extend Shapley Value (SV) explainability from text-only Large Language Models to Multimodal LLMs (MLLMs) processing joint text and audio inputs. While text-based attribution is well-studied, mllm-shap addresses three critical challenges unique to the multimodal regime: (1) Modality-aware coa

Yang Weikang, Chowdhury S. M. Mazharul Hoque, Jin Wei

In this digital world, data is everything and significantly impacts our everyday lives. Interestingly, in this small world, everything is part of an ecosystem, where everything is connected, directly or indirectly. The same thing happens to data as well. In most cases, it may seem like a particular topic does not have any connection with another one, but in

Shengli Zhou, Xiangchen Wang, Guanhua Chen, Feng Zheng

Large language models (LLMs) have recently been applied to 3D vision-language (3D-VL) tasks, which require spatial reasoning to identify target objects relative to anchors. Scene graphs are commonly employed to represent such relations, but reasoning over complete graphs incurs high token costs and computational inefficiencies, motivating the need for prunin

Ioanna Chatzopoulou, Paraskevi Tsoutsa, Panos Fitsilis

The integration of metaverse technologies within Smart Cities is transforming urban governance and citizen engagement. Despite the increasing academic and industry interest, research on the practical applications of the metaverse in SCs remains fragmented. This study addresses this gap through a systematic literature review on how metaverse-driven solutions

Jeba Maliha, Md Rafiul Kabir

Coronary artery disease (CAD) remains one of the leading causes of death globally, highlighting the need for reliable predictive systems to support early diagnosis and risk assessment. While traditional machine learning models perform well on structured clinical data, large language models (LLMs) present new possibilities to interpret medical information exp

Rohith Nama

Autonomous AI agents now plan, decide, and act on behalf of users across healthcare, financial services, and workplace contexts, often without step-by-step human approval. Existing AI literacy frameworks were built for a world in which humans evaluate AI outputs and decide whether to act; they have no vocabulary for the user who has delegated decision-making

Xianke Qiang, Zheng Chang, Geyong Min

Deploying large Transformer-based vision models on resource-limited mobile devices at network edge is severely constrained by hardware limitations and dynamic wireless environments. While federated learning (FL) enables collaborative training without sharing raw data, strictly local fine-tuning of such massive models remains computationally prohibitive for e

Ya-Ting Yang, Quanyan Zhu

Modern AI systems increasingly rely on workflows composed of multiple interacting agents, some powered by large language models (LLMs) and others by conventional computational modules. This paper analyzes the fundamental tradeoffs between latency, reliability, and cost in LLM-enabled agentic workflows. We introduce performance models for both LLM and non-LLM

Gregory Magarshak

We present Context, the intelligence layer of the Magarshak Architecture, which replaces reactive query-response chatbots with proactive goal-directed agents that advance shared tasks without waiting for user prompts. The architecture rests on three mutually reinforcing mechanisms. Write-time context assembly precomputes enriched typed attributes via Groker

Xingyu Xiao, Jiejuan Tong, Jingang Liang, Haitao Wang

Team-level failure in nuclear control rooms arises not from isolated operator error, but from emergent interaction dynamics, delayed diagnosis, suppressed dissent, and authority-driven error propagation, that conventional human reliability analysis methods are structurally unable to model. This study introduces TEAM-SimHRA, a multi-agent large language model

Zhiyuan Zhai, Xinkai You, Wenjing Yan, Xin Wang

Reasoning-capable large language models solve hard problems by emitting long chains of thought, paying heavily in latency, GPU time, and energy. Casual inspection of their traces reveals extensive reformulation, verification, and circular self-reflection, yet how much of this deliberation is actually necessary has never been measured at scale or explained fr

Gregory Magarshak

We present Intercloud, a decentralised economic network in which streams of private data are secured by Watcher swarms that observe only cryptographic hashes, never plaintext. Intercloud requires no global consensus beyond a single shared random seed per epoch. Two mechanisms provide security: (i) ripple deduplication via epoch-stamped identifiers, preventin

Payel Santra, Lavisha Sharma, Madhusudan Ghosh, Partha Basuchowdhuri

The rapid spread of misinformation on social media highlights the need for robust, automated fact correction frameworks. However, existing works rely on supervised learning from manually annotated claim-evidence pairs, which are scarce and prone to biases, limiting their generalization across domains. Moreover, these methods overlook semantic faithfulness in

Zhuoping Zhou, Davoud Ataee Tarzanagh, Sima Didari, Wenjun Hu

Graph-based Retrieval-Augmented Generation (RAG) systems leverage interconnected knowledge structures to capture complex relationships that flat retrieval struggles with, enabling multi-hop reasoning. Yet most existing graph-based methods suffer from (i) heuristic designs lacking theoretical guarantees for subgraph quality or relevance and/or (ii) the use of

Zeyu Tang, Sang T. Truong, Deonna Owens, Shreyas Sharma

LLM fairness should be evaluated through in-situ behavioral pattern rather than standardized-test Q&A benchmarks. We show that the standardized-test paradigm can be structurally unreliable: surface-level prompt construction choices, although entirely orthogonal to the fairness question being tested, account for the majority of score variance, shift fairness

John Alderete, Sebastian Benthall, Connie Xu, John Xing

Causal discovery through experimentation and intervention is fundamental to robust problem solving. It requires not just updating beliefs within a fixed framework but revising the hypothesis space itself, a capacity current AI agents lack when evidence demands representations they have not previously constructed. We extend the blicket detector paradigm from

Haoning Xue, Jingwen Zhang, Xiaohui Wang, Diane Dagyong Kim

The contemporary media landscape is characterized by sensational short videos. While prior research examines the effects of individual multimodal features, the collective impact of multimodal features on viewer engagement with short videos remains unknown. Grounded in the theoretical framework of Message Sensation Value (MSV), this study develops and tests a

Rajdeep Paul, Prabuddha Roy, A. K. Pan

We present a hitherto unexplored semi-device-independent (SDI) self-testing protocol designed to certify unitary operations within a variant of prepare-measure framework. We consider a communication game which we refer to as a variant of $3$-bit prepare-measure random access code (PMRAC) involving two parties, Alice and Bob, who share a prior two-qubit quant

Christopher Burger-Scheidlin, Brianna D. Ball, Sanja Lazarević, Roland Kothes

G310.7-5.4 is a supernova remnant (SNR) candidate identified as a faint shell in the second epoch Molonglo Galactic Plane Survey (MGPS-2), but this has not been followed up with multi-wavelength observations until now. It is an example of an SNR at high Galactic latitude showing spatially coinciding $γ$-ray emission. Here, we make the first detailed investig

Yu Zhang, Xing Shen, Kemeng Huang, Wei Chen

Incremental Potential Contact (IPC) guarantees intersection-free simulation but suffers from high computational costs due to the expensive Hessian assembly and linear solves required by Newton's method. While Preconditioned Nonlinear Conjugate Gradient (PNCG) avoids Hessian assembly, it has historically struggled with poor convergence in stiff, contact-r

Robbert W. Scholtens, Marcello Seri, Holger Waalkens, Rien van de Weygaert

The standard cosmological model is challenged by an ever-growing collection of observations, which invites (and stimulates) inquiry into possible additions and/or alterations. One such alteration comes from letting cosmic isotropy -- as demanded by the cosmological principle -- go, whilst maintaining only homogeneity. This study concerns Bianchi models, a cl

Zihao Fan, Xin Lu, Jie Xiao, Dong Li

In image restoration, single-step discriminative mappings often lack fine details via expectation learning, whereas generative paradigms suffer from inefficient multi-step sampling and noise-residual coupling. To address this dilemma, we propose IR-Flow, a novel image restoration method based on Rectified Flow that serves as a unified framework bridging the

Natascia Vignaroli

The anomalous magnetic moment of the tau lepton, $a_τ$, represents a fundamental test of the Standard Model (SM) and a high-sensitivity probe for New Physics in the third generation of leptons. Due to the tau's extremely short lifetime, traditional spin-precession measurements remain inaccessible, necessitating innovative experimental strategies at high-

Jiaxun Li, Tinggui Wang, Zheyu Lin

Context. Episodic accretion in young stellar objects (YSOs) is thought to play a critical role in addressing the "luminosity problem" associated with star formation. However, optical surveys tend to bias against sources that are heavily obscured. Infrared time-domain surveys, such as unTimely WISE, facilitate the identification of such sources within

Jianming Wen

We develop a compact theory of time-reversed Young (TRY) interference beyond the symmetric two-slit geometry by considering equally spaced three-slit, finite $N$-slit, and infinite periodic slit arrays. In the TRY configuration, a point emitter illuminates the aperture, a position-fixed detector records the signal, and the response is reconstructed in source

Yanbin Huang, Yisen Li, Guiyao Tie, Xiaoye Qu

Large vision-language models (LVLMs) frequently suffer from Object Hallucination (OH), wherein they generate descriptions containing objects that are not actually present in the input image. This phenomenon is particularly problematic in real-world applications such as medical imaging and autonomous driving, where accuracy is critical. Recent studies suggest

Alexios Liakos, David J. W. Moriarty, Julian F. West, Ahmet Erdem

This study is an in-depth examination of IZ Tel and UW Vir which are semi-detached oscillating Eclipsing Algol binary systems (oEA stars). The radial velocities of both components of each system were derived using spectra observed with the Australian National University's 2.3 m telescope. The spectral types of the IZ Tel primary and secondary components

K. Kawai, Y. Aritomo, K. Nakajima, S. Takagi

Fusion reactions with 48Ca beams, which have been used for synthesis of $Z \le 118$ nuclei, face practical limitations for the synthesis of nuclei with $Z \ge 119$ because of the limited availability of suitable target nuclei. We estimate evaporation-residue (ER) cross sections for the reactions 48Ca + 254Es, 50Ti + 249Bk, 51V + 248Cm, and 54Cr + 243Am and e

Jamie Lee, Flynn Teh, Hengcheng Zhu, Mengzhen Li

Large Language Models (LLMs) have recently shown strong potential for automated unit test generation. This has motivated us to investigate whether developer-defined test doubles (commonly referred to as mocks) available in existing test suites can be leveraged to improve LLM-driven test generation. To this end, we propose MOCKMILL, an LLM-based technique and

Inês Rolo, Daniel L. Holdsworth, Margarida S. Cunha, Victoria Antoci

The rapidly oscillating chemically peculiar A-type (roAp) stars offer valuable insights into the internal physical processes of all stars, but their study is challenged by their rarity. The large-scale TESS surveys have allowed for the collection of data for a sizeable dataset of roAp stars. Nevertheless, asteroseismic data obtained with TESS and Gaia has no

George K. Leontaris, Pramod Shukla

Fibre inflation is one of the most attractive models realized in the type IIB orientifold compactification. It is embedded in the framework of L(arge) V(olume) S(cenarios) using a class of compactifying Calabi-Yau (CY) threefolds having K3-fibration. The standard single-field fibre inflation is driven by a fibre modulus which needs to travel a trans-Planckia

Xiaotian Zhang, Jianhui Wei, Yuan Wang, Jie Tan

Despite remarkable progress toward general-purpose video models, a critical question remains unanswered: how far are these models from achieving true multimodal reasoning? Existing benchmarks fail to address this question rigorously, as they remain constrained by straightforward task designs and fragmented evaluation metrics that neglect complex multimodal r

Bo-Jyun Wang, Ying-Jia Lin, Hung-Yu Kao

Small language models (SLMs), such as BART, can achieve summarization performance comparable to large language models (LLMs) via distillation. However, existing LLM-based ranking strategies for summary candidates suffer from instability, while classical metrics (e.g., ROUGE) are insufficient to rank high-quality summaries. To address these issues, we introdu

Si-Yuan Zhu, Pak-Hin Thomas Tam, Fu-Wen Zhang, Hui-Ying Deng

Gamma-ray bursts (GRBs) are generally classified as Type~I GRBs, which originate from compact binary mergers, and Type~II GRBs, which originate from massive collapsars. The traditional correspondence between short--Type~I GRBs and long--Type~II GRBs, separated by a duration of 2 seconds, has been challenged by recent observations of long GRBs associated with

Hanchen Wang, Laura van Schie, Adam Erickson, Lauren J. Riddiford

Coherent control of domain wall dynamics offers a route to fast manipulation of magnetic textures beyond thermally activated motion. We demonstrate resonant excitation of linear and nonlinear dynamics of a pinned domain wall in a ferrimagnetic garnet thin film driven by a microwave field. Using scanning nitrogen-vacancy magnetometry and nonlocal spin-pumping

Kazushi Aoyama, Hikaru Kawamura

Spin-selective band splitting without net magnetization and spin-orbit couplings serves for a next-generation spin-current generator, and its typical platforms are altermagnets and compensated ferrimagnets as well, where the existence of a crystal asymmetry or nonequivalent sites is essential. Here, we theoretically demonstrate that such a splitting can be r

Masaki Uto

Automated essay scoring (AES) is commonly evaluated on public benchmarks using quadratic weighted kappa (QWK). However, because benchmark labels are assigned by human raters and inevitably contain scoring errors, it remains unclear both what QWK is theoretically attainable and what level is practically sufficient for deployment. We therefore derive two datas

Byunghyun Kim

UV-parameterized Gaussian Splatting (UVGS) maps an unstructured set of 3D Gaussians to a regular UV tensor, enabling compact storage and explicit control of representation capacity. Existing UVGS, however, uses a deterministic spherical pro- jection to assign Gaussians to UV locations. Because this mapping ignores the global Gaussian distribution, it often l

Tengyou Xu, Detao Ma, Xiang 'Anthony' Chen

The rise of large language models (LLMs) has given rise to a class of prompt-based interactive systems where users primarily express their input in natural language. However, composing a prompt as a linear text string becomes unwieldy when capturing users' multifaceted intents. We present Object-Oriented Prompting (OOPrompt), an emergent interaction para

Anzar Ali, Md Ezaz Hasan Khan, Mahmoud Abdel-Hafiez

Transition metal dichalcogenides exhibit a wide range of semiconducting, metallic, correlated, and topological electronic states that arise from strong coupling between lattice structure, dimensionality, and electronic degrees of freedom. In these materials, crystal growth is not merely a preparative step but a thermodynamic boundary condition that establish

Akihisa Koga, Takanori Sugimoto

We investigate the effects of stealthy hyperuniform bond distributions on the electronic and magnetic properties of the Hubbard model on the honeycomb lattice. Hyperuniform structures, distinct from random and quasiperiodic ones, have recently attracted considerable interest due to their anomalous suppression of density fluctuations. By diagonalizing the non

Joshua Covey, Dmitrii L. Maslov

Recent THz spectroscopy of the quantum paraelectric SrTiO$_3$ (arXiv:2501.15771) and a high-$T_c$ cuprate (arXiv:2503.15646) has renewed interest in energy relaxation in correlated electron systems. We consider a situation in which single-phonon scattering is forbidden by symmetry or momentum conservation, while two-phonon scattering is allowed. Solving the

B. Q. Lv, Yifan Su, Alfred Zong, Karna Morey

Metastability is fundamental not only to phase ordering and transitions, but also to a broad range of modern technologies, from memory devices to metallic glasses. In condensed-matter physics, charge density waves (CDWs) offer versatile platforms for accessing metastable states due to their sensitivity to external stimuli. However, most metastable CDW states

Dongxiao Zhao, Qiang Zhang

Let $F \ast G$ be a free product of a free group $F$ and a LERF group $G$. In this note, we provide sufficient conditions for a subgroup $H$ of $F \ast G$ to be $\mathcal{A} \cup \mathcal{S}$-separable, that is, for any finite set $\{γ_1, \ldots, γ_n\} \subset (F \ast G) \setminus H$, there is a surjection $f$ from $F \ast G$ to an alternating or symmetric g

Qingshun Hu, Yufei Cai, Caroline Soubiran, Yu Dai

Open clusters (OCs) in our Galaxy can be found in pairs, possibly forming physical binaries, or in groups. These objects offer unique insights into the process of star formation and testify to the dynamical interactions at local and galactic scales. Therefore, building as complete a census as possible is a valuable endeavor. This work is aimed at identifying

A. Bonfanti, D. Gandolfi, P. Leonardi, H. P. Osborn

Following the 2022 alert of a TESS object of interest transiting TOI-5624 (a G7 V star $\sim$100 pc away), a CHEOPS campaign in 2023 detected four planetary signals at $P_b\approx3.4$, $P_c\approx7.9$, $P_d\approx13.7$, and $P_e\approx21.5$ days, later confirmed by additional TESS and CHEOPS photometry in 2024-2025. After analysing the TESS & CHEOPS photomet

Ioannis Pantos, Leandros Perivolaropoulos

The fiducial-independent angular/transverse BAO dataset, obtained from two-point angular correlation functions in thin redshift shells (hereafter BAOtr), systematically prefers smaller comoving distance ratios $D_{\rm M}/r_{\rm d}$ than the DESI DR2 three-dimensional BAO measurements at $z \lesssim 0.65$, driving dataset-dependent CPL dark-energy inferences

Carmela Lardo, David Valcin, Raul Jimenez

Globular clusters encode the hierarchical assembly history of the Milky Way and the physics of multiple stellar populations. Using homogeneous stellar parameters for 69 Galactic globular clusters derived while modelling multiple populations, we reconstruct progenitor-specific age--metallicity relations (AMRs) and test whether helium-related multiple-populati

Ioana Doran, Leon Jeckel, Maximilian Beyer, Christian Jungen

We present a general theoretical treatment and calculations of the fine and hyperfine structures in the spectra of high-$n$ molecular Rydberg states in static uniform electric fields. The treatment combines (i) multichannel quantum-defect theory and long-range polarization models to determine the field-free energies of $n\ell$ Rydberg states of the molecules

Freja Høgholm Petersen, Jesper Sandvig Mariegaard, Rocco Palmitessa, Allan P. Engsig-Karup

While proper orthogonal decomposition (POD)-based surrogates are widely explored for hydrodynamic applications, the use of Koopman autoencoders for real-world coastal-ocean modelling remains relatively limited. This paper introduces a flexible Koopman autoencoder formulation that incorporates meteorological forcings and boundary conditions, and systematicall

Yuxing Chen, Guoqing Luo, Zijun Wu, Lili Mou

Large Language Models (LLMs) exhibit social biases, which can lead to harmful stereotypes and unfair outcomes. We propose \textbf{Multi-Persona Thinking (MPT)}, a simple inference-time framework that reduces social bias by encouraging reasoning from multiple perspectives. MPT guides the model to consider contrasting social identities, such as male and female

Daniel A. Perley, Anna Y. Q. Ho, Zoë McGrath, Michael Camilo

We present the discovery of AT 2024wpp ("Whippet"), a fast and luminous 18cow-like transient. At a redshift of z=0.0868, revealed by Keck Cosmic Web Imager spectroscopy of its faint star-forming host, it is the fourth-nearest example of its class to date. Rapid identification of the source in the Zwicky Transient Facility data stream permitted ultrav

Rachmad Vidya Wicaksana Putra, Pasindu Wickramasinghe, Muhammad Shafique

Large Language Models (LLMs) have been emerging as prominent AI models for solving many natural language tasks due to their high performance (e.g., accuracy) and capabilities in generating high-quality responses to the given inputs. However, their large computational cost, huge memory footprints, and high processing power/energy make it challenging for their

Baptiste Bergeot, Nils Berglund, Israa Zogheib

In this work, we analyse the effect of adding Gaussian white noise to the slow variable of a slow--fast system passing through a saddle--node (or fold) bifurcation. This problem is mainly motivated by applications to non-equilibrium energy sinks. While the effect of adding noise to the fast variable, which is important for noise-induced tipping, has been pre

Moritz Blumenthal, Tina Holliber, Jonathan I. Tamir, Martin Uecker

Purpose: The Unadjusted Langevin Algorithm (ULA) in combination with diffusion models can generate high quality MRI reconstructions with uncertainty estimation from highly undersampled k-space data. However, sampling methods such as diffusion posterior sampling (DPS) or likelihood annealing suffer from long reconstruction times and the need for parameter tun

Barnabas Porfy, Mate Csanad

Over the past few decades, progress in femtoscopy has been driven by the interplay between experimental measurements and theoretical calculations. Measurements provide data to support the theory, while theoretical predictions guide new measurements. In the recent decade, several experiments have confirmed that the two-particle pion-emitting source is well de

Josep Plana-Riu, Henrik Rosenberger, Benjamin Sanderse, F. Xavier Trias

This work introduces RedEigCD, the first self-adaptive timestepping technique specifically tailored for reduced-order models (ROMs) of the incompressible Navier-Stokes equations. Building upon linear stability concepts, the method adapts the timestep by directly bounding the stability function of the employed time integration scheme using exact spectral info

Roberto Hernández Palomares, Miho Mukohara

We discuss proper outerness for finite index endomorphisms and finite index bimodules of simple C$^*$-algebras, extending recent similar results by Izumi concerning the purely infinite setting. Our main result is that proper outerness holds automatically for finite index outer endomorphisms of simple C$^*$-algebras. Consequently, freeness for outer actions o

T. Wu, Y. C. Tung, Y. B. Hsiung, J. K. Ahn

We report a search for an invisible particle $X$ in the decay $K^0_L\rightarrow γX$ ($X \to \text{invisible}$), where $X$ can be interpreted as a massless or massive dark photon. No evidence for $X$ was found, based on 13 candidate events consistent with a predicted background of $12.66 \pm 4.42_{\text{stat.}} \pm 2.13_{\text{syst.}}$ events. Upper limits on

Jun-Ping Chen, Rong-Feng Shen, Jin-Hong Chen, Wei-Hua Lei

Recent studies indicate that mergers of a white dwarf (WD) with a neutron star (NS) or a stellar-mass black hole (BH) may be a potential progenitor channel for certain merger-kind, but long-duration $γ$-ray bursts (GRBs), e.g., GRBs 230307A and 211211A. The relatively large tidal disruption radius of the WD can result in non-negligible residual orbital eccen

G. R. Araujo, D. Bajpai, L. Baudis, V. Belov

Ordinary muon capture provides a benchmark for the nuclear physics models of neutrinoless double beta decay under comparable momentum transfer conditions. The total capture strength defines the lifetime of the muonic atom. The muon lifetime in $^{76}$Se, the daughter nucleus of $^{76}$Ge, was determined with improved accuracy by the MONUMENT collaboration, u

Luca Boccioli, Lorenzo Roberti

Explosive nucleosynthesis is affected by many uncertainties, particularly regarding assumptions and prescriptions adopted during the evolution of the star. Moreover, simple explosion models are often used in the literature, which can introduce large errors in the assumed explosion energy and mass cut. In this paper, our goal is to analyze the explosion prope

Tomoki Yamagami, Etsuo Segawa, Takatomo Mihana, André Röhm

Quantum reinforcement learning has emerged as a framework combining quantum computation with sequential decision-making, and applications to the multi-armed bandit (MAB) problem have been reported. The graph bandit problem extends the MAB setting by introducing spatial constraints, where the accessibility of arms is restricted by graph connectivity, yet quan

Matteo Scandi, Gonzalo Manzano

We derive detailed and intergral fluctuation relations as well as a Thermodynamic Uncertainty Relation constraining the exchange statistics of an arbitrary number of non-commuting conserved quantities among two quantum systems in transport setups arbitrary far from equilibrium. These universal relations, valid without the need of any efficacy parameter, exte

Raphaël Carroy, Maxwell Levine, Lorenzo Notaro

Entangled linear orders were first introduced by Abraham and Shelah. Todorčević showed that these linear orders exist under $\mathsf{CH}$. We prove the following results: (1) If $\mathsf{CH}$ holds, then, for every $n > 0$, there is an $n$-entangled linear order which is not $(n+1)$-entangled. (2) If $\mathsf{CH}$ holds, then there are two homeomorphic sets

Yizhuang Liu, Marcos Mariño

In this work we provide a massless perturbative framework for the two dimensional non-linear sigma model (NLSM), that allows the computation of the perturbative series attached to the operator condensates in the operator product expansion (OPE). It is based on a limit of the quartic linear sigma model (LSM) and is manifestly $O(N)$ symmetric. We show, at nex

Nam Anh Nguyen, Arnold Reusken

We consider the harmonic map heat flow problem for a corotational case. For discretization of this problem we apply a $H^1$-conforming finite element method in space combined with a semi-implicit Euler time stepping. The semi-implicit Euler method results in a linear problem in each time step. We restrict to the regime of smooth solutions of the continuous p

Ken'ichi Yoshida

We show that if two links in the real projective 3-space $\mathbb{RP}^{3}$ have isotopic preimages in the 3-sphere $S^{3}$ by the double covering map, then they are themselves isotopic in $\mathbb{RP}^{3}$.

Rajdeep Paul, Sneha Munshi, Alok Kumar Pan

Self-testing is the strongest certification procedure that uniquely characterizes the physical system based on the observed statistics, without any knowledge of the inner workings of the devices. The optimal quantum violation of a Bell inequality enables such a device-independent (DI) self-testing of the source and the measurement devices. In this work, we d

Lorenzo Focardi-Olmi, Anna Gottard, Michele Guindani, Marina Vannucci

In many research fields, researchers aim to identify significant associations between a set of explanatory variables and a response while controlling the FDR. The Knockoff filter has been recently proposed in the frequentist paradigm to introduce controlled noise in a model by cleverly constructing copies of the predictors as auxiliary variables. We develop

David Loeffler, Sarah Livia Zerbes

We prove an explicit reciprocity law for the Euler system attached to the spin motive of a genus 2 Siegel modular form. As consequences, we obtain one inclusion of the Iwasawa Main Conjecture for such motives, and the Bloch--Kato conjecture in analytic rank 0 for their critical twists.

Michael Poon, Dang Pham, Marta L. Bryan, Hanno Rein

Stellar binaries may form through several formation pathways, including disk or core fragmentation. Their spin-orbit angles are a signature of formation, although individual measurements for visual binaries are limited and broad. A seminal work by A. Hale (1994) found that visual binaries with separations $\lesssim 30$ AU tend to be more aligned, which laid

Chenqian Le, Ruisi Li, Beatrice Fumagalli, Yasamin Esmaeili

We test whether Speech Articulatory Coding (SPARC) features can linearly predict surface electromyography (sEMG) envelopes across aloud, mimed, and subvocal speech in twenty-four subjects. Using elastic-net multivariate temporal response function (mTRF) with sentence-level cross-validation, SPARC yields higher prediction accuracy than phoneme one-hot represe

Yura Yoshida, Masato Kanai, Masataka Nakayama, Haruki Ohsawa

Analyzing topics extracted from text data in relation to external outcomes is important across fields such as computational social science and organizational research. However, existing topic modeling methods struggle to simultaneously achieve interpretability, topic specificity (alignment with concrete actions or characteristics), and polarity stance consis

Linfeng Liang, Xiao Cheng, Tsong Yueh Chen, Xi Zheng

Simulation-based testing of autonomous driving systems (ADS) must uncover realistic and diverse failures in dense, heterogeneous traffic. However, existing search-based seeding methods (e.g., genetic algorithms) struggle in high-dimensional spaces, often collapsing to limited modes and missing many failure scenarios. We present PtoP, a framework that combine

Qirui Fu, Yupeng Jiang, Minchen Li

The numerical performance of the material point method (MPM) is strongly governed by the particle-grid kernel, which controls the trade-off among smoothness, locality, numerical diffusion, contact accuracy, and computational cost. Although wide-support smooth kernels can effectively suppress cell-crossing instability, they often introduce increased numerical

Bo Deng

In this paper, we introduce a new concept called Artificial Special Intelligence by which Machine Learning models for the classification problem can be trained error-free, thus acquiring the capability of not making repeated mistakes. The method is applied to 18 MedMNIST biomedical datasets. Except for three datasets, which suffer from the double-labeling pr

Jnana Ranjan Das, Santanu Sinha, Alex Hansen, Sitangshu Bikas Santra

Mixed-wet percolation was introduced recently in the context of two-phase flow in porous media. In this model, the sites of the primal lattice are occupied with a certain probability $p$, and bonds are placed on the dual lattice between two adjacent occupied and unoccupied sites of the primal lattice. The occupied bonds on the dual lattice form perimeter clu

Mehul Agarwal, Aditya Aggarwal, Arnav Goel, Medha Hira

While multilingual large language models (LLMs) perform well on high-level tasks like translation and question answering, their ability to handle grammatical gender and morphological agreement remains underexplored. In morphologically rich languages, gender influences verb conjugation, pronouns, and even first-person constructions with explicit and implicit

He Cheng, Yifu Wu, Saksham Khatwani, Maya Kruse

Knowledge graphs (KGs) are increasingly integrated with large language models (LLMs) to provide structured, verifiable reasoning. A core operation in this integration is multi-hop retrieval, yet existing systems struggle to balance efficiency, scalability, and interpretability. We introduce LogosKG, a novel, hardware-aligned framework that enables scalable a

Chih-Yu Chang, Qiyuan Chen, Tianhan Gao, David Fenning

Discovering optimal designs through sequential data collection is essential in many real-world applications. While Bayesian Optimization (BO) has achieved remarkable success in this setting, growing attention has recently turned to context-specific optimal design, formalized as Contextual Bayesian Optimization (CBO). Unlike BO, CBO is inherently more challen

Aaron R. Flouro, Shawn P. Chadwick

Computing Fourier transforms of k-sparse signals, where only k of N frequencies are non-zero, is fundamental in compressed sensing, radar, and medical imaging. While the Fast Fourier Transform (FFT) evaluates all N frequencies in $O(N \log N)$ time, sufficiently sparse signals should admit sub-linear complexity in N. Existing sparse FFT algorithms using Chin