December 2025 arXiv papers — page 9

Palle Jorgensen, Jay Jorgenson, Lejla Smajlovic

We explicitly construct a heat kernel as a Neumann series for certain function spaces, such as $L^{1}$, $L^{2}$, and Hilbert spaces, associated to a locally compact Hausdorff space $\mathfrak{X}$ with Borel $\sigma$-algebra $\mathcal{B}$, and endowed with additional measure-theoretic data. Our approach is an adaptation of classical work due to Minakshishunda

Samuel A. Moore

We study the period map from infinitesimal deformations of a qcqs derived scheme $X$ over a field $k$ to those of the associated $k$-linear $\infty$-category $\mathrm{QC}(X)$. We identify the corresponding map on tangent fibres with the dual HKR map $\mathrm{R}Γ(X, \mathbf{T}_{X/k})[1] \longrightarrow \mathrm{HH}^{\bullet}(X/k)[2]$ and study its injectivity

Svante Linusson, Alperen Özdemir

Let $\mathcal{P}_k(n)$ denote the set of partitions of $n$ whose largest part is bounded by $k,$ which are in well-known bijection with $(k+1)$-cores $\mathcal{C}_k$. We study a growth process on $\mathcal{C}_k$, whose stationary distribution is the $k$-Plancherel measure, which is a natural extension of the Plancherel measure in the context of $k$-Schur fun

Devika S, Vishnu Hari, Pratik Narang, Tejasvi Alladi

This works presents an encoder-only transformer built with minimum layers for intrusion detection in the domain of Connected and Autonomous Vehicles using Federated Learning.

Anthony J. Brady

These notes are adapted from six lectures that I delivered at Analogue Gravity in Benasque 2023. They present the unified Gaussian (phase-space) framework to describe linear bosonic quantum systems, the standard tool in quantum optics and continuous-variable quantum information, emphasizing its simplicity and platform independence, with applications to semi-

Farimah Shamsi, Andriy Derkach

The integration of data from multiple sources is increasingly used to achieve larger sample sizes and enhance population diversity. Our previous work established that, under random sampling from the same underlying population, integrating large incomplete datasets with summary-level data produces unbiased parameter estimates. In this study, we develop a nove

Andre G. Campos, Karen Z. Hatsagortsyan, Christoph H. Keitel

An effective model for describing the relativistic quantum dynamics of a radiating electron is developed via a relativistic generalization of the Lindblad master equation. By incorporating both radiation reaction and vacuum fluctuations into the Dirac equation within an open quantum system framework, our approach captures the Zitterbewegung of the electron,

Wen-wai Yim, Yujuan Fu, Asma Ben Abacha, Meliha Yetisgen

Recent advances in dermatological image analysis have been driven by large-scale annotated datasets; however, most existing benchmarks focus on dermatoscopic images and lack patient-authored queries and clinical context, limiting their applicability to patient-centered care. To address this gap, we introduce DermaVQA-DAS, an extension of the DermaVQA dataset

Chandrasekhar Gokavarapu

Rectified Linear Unit (ReLU) networks are piecewise-linear (PWL), so universal linear safety properties can be reduced to reasoning about linear constraints. Modern verifiers rely on SMT(LRA) procedures or MILP encodings, but a safety claim is only as trustworthy as the evidence it produces. We develop a proof-carrying verification core for PWL neural constr

Liam Frija-Altarac, Matthew Toews

This paper proposes elementary information mechanics as a new model for understanding the mechanical properties of convolutional filtering with rectification, inspired by physical theories of special relativity and quantum mechanics. We consider kernels decomposed into orthogonal even and odd components. Even components cause image content to diffuse isotrop

Henryk Fukś

For many cellular automata, it is possible to express the state of a given cell after $n$ iterations as an explicit function of the initial configuration. We say that for such rules the solution of the initial value problem can be obtained. In some cases, one can construct the solution formula for the initial value problem by analyzing the spatiotemporal pat

Sara Geremia, Michael Fop, Domenico De Stefano

Community structure in social and collaborative networks often emerges from a complex interplay between structural mechanisms, such as degree heterogeneity and leader-driven attraction, and homophily on node attributes. Existing community detection methods typically focus on these dimensions in isolation, limiting their ability to recover interpretable commu

Manish Krishan Lal

We establish two correspondences between reverse-mode automatic differentiation (backpropagation at a given forward-pass point) and compositions of projection maps in Kullback--Leibler (KL) geometry. In both settings, message passing enforces agreement and factorization constraints through KL projections. In the first setting, backpropagation arises as the d

Anbang Zhang, Chenyuan Feng, Wai Ho Mow, Jia Ye

The rapid deployment of mega-constellations is driving the long-term vision of space data centers (SDCs), where interconnected satellites form in-orbit distributed computing and learning infrastructures. Enabling distributed federated learning in such systems is challenging because iterative training requires frequent aggregation over inter-satellite links t

R. García-Delgado

In this work we study quadratic Lie algebras that contain the Heisenberg Lie algebra $\h_m$ as an ideal. We give a procedure for constructing these kind of quadratic Lie algebras and prove that any quadratic Lie algebra $\g$ that contains the Heisenberg Lie algebra as an ideal is constructed by using this procedure. We state necessary and sufficiency conditi

Junhong Liu, Nan Zhou, Minda Ma, Kairui You

The continuous growth of China's private passenger vehicle fleet has intensified material demand and embodied carbon emissions, underscoring the need for effective decarbonization pathways. This study develops a transferable, dynamic material flow analysis framework to assess vehicle stocks, metal flows (steel, aluminum, and copper), and embodied emissions f

Yong Xien Chng, Tao Hu, Wenwen Tong, Xueheng Li

While Vision-Language Models (VLMs) can solve complex tasks through agentic reasoning, their capabilities remain largely constrained to text-oriented chain-of-thought or isolated tool invocation. They fail to exhibit the human-like proficiency required to seamlessly interleave dynamic tool manipulation with continuous reasoning, particularly in knowledge-int

Keito Inoshita, Shinnosuke Mizuno

Sarcasm understanding is a challenging problem in natural language processing, as it requires capturing the discrepancy between the surface meaning of an utterance and the speaker's intentions as well as the surrounding social context. Although recent advances in deep learning and Large Language Models (LLMs) have substantially improved performance, most exi

Yuxiang Xin, Chen-Xin Yu, Jianru Wang, Jianbo Jin

The high-entropy halide-perovskite field has expanded rapidly, yet a key gap remains: configurational entropy is not yet a reliable, designable lever to co-deliver expanded photonic functionality and operational robustness with a composition-transferable mechanistic basis. Here we develop entropy-engineered rare-earth halide double-perovskite single crystals

Anna Calissano, Etienne Lasalle

Spatial graphs are particular graphs for which the nodes are localized in space (e.g., public transport network, molecules, branching biological structures). In this work, we consider the problem of spatial graph reduction, that aims to find a smaller spatial graph (i.e., with less nodes) with the same overall structure as the initial one. In this context, p

Camron Alexander Hirst, Chris Reale, Eric Frew

This paper presents the design, implementation, and flight test results of two novel 3D path-following guidance algorithms based on nonlinear model predictive control (MPC), with specific application to fixed-wing small uncrewed aircraft systems. To enable MPC, control-augmented modelling and system identification of the RAAVEN small uncrewed aircraft is pre

Wan Jiang, Xinyi Zang, Yudong Zhao, Yusi Zou

Modern recommender systems face significant computational challenges due to growing model complexity and traffic scale, making efficient computation allocation critical for maximizing business revenue. Existing approaches typically simplify multi-stage computation resource allocation, neglecting inter-stage dependencies, thus limiting global optimality. In t

Haojin Li, Anbang Zhang, Chen Sun, Chenyuan Feng

The low-altitude economy (LAE) is rapidly expanding driven by urban air mobility, logistics drones, and aerial sensing, while fast and accurate beam prediction in uncrewed aerial vehicles (UAVs) communications is crucial for achieving reliable connectivity. Current research is shifting from single-signal to multi-modal collaborative approaches. However, exis

Haijing Liu, Zhiyuan Song, Hefeng Wu, Tao Pu

Egocentric Referring Video Object Segmentation (Ego-RVOS) aims to segment the specific object actively involved in a human action, as described by a language query, within first-person videos. This task is critical for understanding egocentric human behavior. However, achieving such segmentation robustly is challenging due to ambiguities inherent in egocentr

Alan Miranda, Steven Staelens

Dynamic positron emission tomography (PET) reconstruction often presents high noise due to the use of short duration frames to describe the kinetics of the radiotracer. Here we introduce a new method to calculate a kernel matrix to be used in the kernel reconstruction for noise reduction in dynamic PET. We first show that the kernel matrix originally calcula

Nan Jiang, Zimo He, Wanhe Yu, Lexi Pang

A long-standing objective in humanoid robotics is the realization of versatile agents capable of following diverse multimodal instructions with human-level flexibility. Despite advances in humanoid control, bridging high-level multimodal perception with whole-body execution remains a significant bottleneck. Existing methods often struggle to translate hetero

Adam Boocher, Noah Huang, Harrison Wolf

We study two long-standing conjectures concerning lower bounds for the Betti numbers of a graded module over a polynomial ring. We prove new cases of these conjectures in codimensions five and six by reframing the conjectures as arithmetic problems in the Boij-S\"oderberg cone. In this setting, potential counterexamples correspond to explicit Diophantine obs

Diana Bakirova, Oleg Malkov

Based on the spatial distribution of objects in the solar neighbourhood with a radius of 20 parsecs, and after correcting for the incompleteness of observational data, an expression was obtained for estimating the probability of finding an object at a given distance from the Sun. According to these estimates, with a probability of about 0.5, there exists a b

Lukas Schembecker

Kastermans proved that consistently $\bigoplus_{\aleph_1} \mathbb{Z}_2$ has a cofinitary representation. We present a short proof that $\bigoplus_{\mathfrak{c}} \mathbb{Z}_2$ always has an arithmetic cofinitary representation. Further, for every finite group $F$ we construct an arithmetic maximal cofinitary group of isomorphism type $(\ast_{\mathfrak{c}} \ma

Nai-Heng Sheu

Given a group $G$ and $V$ a representation of $G$, denote the number of indecomposable summands of $V^{\otimes k}$ by $b_k^{G, V}$. Given a tilting representation $T$ of $\text{SL}_2(K)$ where $K=\overline{K}$ and of characteristic $p>2$, we show that $Ck^{-\alpha_p}(\text{dim} T)^k<b_k^{T, \text{SL}_2(K)}<Dk^{-\alpha_p}(\text{dim} T)^k$ for some $C, D>0$ wh

Wen Chang, Haibo Jin, Sibylle Schroll, Qi Wang

This paper investigates finiteness conditions for gentle and skew-gentle algebras. First, we prove that a skew-gentle algebra is $\tau$-tilting finite if and only if it is representation-finite, which extends the result for gentle algebras by Plamondon (2019). Second, using surface models, we characterize silting-discreteness for the perfect derived categori

Dian-Jun Zhao, Long Chen, Hongxin Dong, Xiangdong Ji

We report a state-of-the-art lattice QCD calculation of the total gluon helicity contribution to the proton spin, $\Delta G$. The calculation is done on ensembles with three different lattice spacings $a=\{0.08, 0.09, 0.11\}$ fm. By employing distillation and momentum smearing for proton external states, we extract the bare matrix elements of the topological

Shupeng Li, Weipeng Lu, Linyun Liu, Chen Lin

Domain-specific enhancement of Large Language Models (LLMs) within the financial context has long been a focal point of industrial application. While previous models such as BloombergGPT and Baichuan-Finance primarily focused on knowledge enhancement, the deepening complexity of financial services has driven a growing demand for models that possess not only

Grégoire Lambrecht, Mathieu Laurière

We introduce a general probabilistic framework for discrete-time, infinite-horizon discounted Mean Field Type Games (MFTGs) with both global common noise and team-specific common noises. In our model, agents are allowed to use randomized actions, both at the individual level and at the team level. We formalize the concept of Mean Field Markov Games (MFMGs) a

Julia Tokarska, Andrzej Dragan

Gravitationally induced entanglement has been proposed as a probe of the quantum nature of gravity. This work analyzes a system of two particles in harmonic traps interacting only through gravity, considering thermal and two-mode squeezed initial states. For thermal states, a maximum temperature is identified above which entanglement cannot be generated, and

Adrián Andrada, Agustín Garrone

We study the contact Lefschetz condition on compact contact solvmanifolds, as introduced by B.\ Cappelletti-Montano, A.\ De Nicola and I.\ Yudin. We seek to fill the gap in the literature concerning Benson-Gordon type results, characterizing $1$-Lefschetz contact solvmanifolds. We prove that the $1$-Lefschetz condition on Lie algebras is preserved via $1$-di

Yupeng Zheng, Jichao Peng, Weize Li, Yuhang Zheng

We introduce World In Your Hands (WIYH), a large-scale open-source ecosystem comprising over 1,000 hours of human manipulation data collected in-the-wild with millimeter-scale motion accuracy. Specifically, WIYH includes (1) the Oracle Suite, a wearable data collection kit with an auto-labeling pipeline for accurate motion capture; (2) the WIYH Dataset, feat

Jessica N. López-Sánchez

We study the cosmological impact of a transient self-interaction phase in Ultra-Light Dark Matter (ULDM), focusing on its simultaneous effects on the sound horizon and the late-time growth of structure. In the presence of a quartic self-interaction, the scalar field undergoes a short-lived radiation-like phase before evolving into matter-like behaviour, indu

Omer Gurevich, Maor Matityahu, Tal Mor

Ising formulation is important for many NP problems (Lucas, 2014). This formulation enables implementing novel quantum computing methods including Quantum Approximate Optimization Algorithm and Variational Quantum Eigensolver (VQE). Here, we investigate closely the traveling salesman problem (TSP). First, we present some non-trivial issues related to Ising m

Anna Ben-Hamou, Pierre Tarrago

In the present paper, we consider a class of Markov processes on the discrete circle which has been introduced by K\"onig, O'Connell and Roch. These processes describe movements of exchangeable interacting particles and are discrete analogues of the unitary Dyson Brownian motion: a random number of particles jump together either to the left or to the right,

Thijs Snelleman, Peter Lundestad Lawrence, Holger H. Hoos, Odd Erik Gundersen

Background. Reproducibility is essential to the scientific method, but reproduction is often a laborious task. Recent works have attempted to automate this process and relieve researchers of this workload. However, due to varying definitions of reproducibility, a clear problem statement is missing. Objectives. Create a generalisable problem statement, applic

Jian Xie, Zihao Huo, Zhimou Chen, Zaizhe Zhang

Recent studies of rhombohedral multilayer graphene (RMG) have revealed a variety of superconducting states that can be induced or enhanced by magnetic fields, reinforcing RMG as a powerful platform for investigating novel superconductivity. Here we report an insulator-superconductor transition driven by in-plane magnetic fields B|| in rhombohedral hexalayer

R. D. Hazeltine

We construct a coordinate system fitting the geometry of a given, cylindrically symmetric, magnetic field.

Antoni Wójcik, Jan Wójcik

In a recent paper, Chatterjee et al. [Phys. Rev. Lett 135, 220202 (2025)] analyze and experimentally implement a specific unitary evolution of a simple quantum system. The authors refer to this type of dynamics as a "superposition of unitary time evolutions." They claim that such an evolution enables a violation of the temporal Tsirelson bound in the Leggett

EJ Janse van Rensburg, E Orlandini, MC Tesi, SG Whittington

A system of two self and mutual interacting ring polymers, close together in space, can display several competing equilibrium phases and phase transitions. Using Monte Carlo simulations and combinatorial arguments on a corresponding lattice model, we determine three equilibrium phases, two in which the rings segregate in space and are either extended (the se

Long Zhang, Fangwei Lin, Weilin Wang

The rise of Human-AI Collaborative Learning (HAICL) is shifting education toward dialogue-centric paradigms, creating an urgent need for new assessment methods. Evaluating Self-Regulated Learning (SRL) in this context presents new challenges, as the limitations of conventional approaches become more apparent. Questionnaires remain interrupted, while the util

Hauke Brinkop, Hua Chen, Lin Chen, Klaus Jansen

The classic algorithm [Papadimitriou, J.ACM '81] for IPs has a running time $n^{O(m)}(m\cdot\max\{\Delta,\|\textbf{b}\|_{\infty}\})^{O(m^2)}$, where $m$ is the number of constraints, $n$ is the number of variables, and $\Delta$ and $\|\textbf{b}\|_{\infty}$ are, respectively, the largest absolute values among the entries in the constraint matrix and the righ

Shuang Li, Pingzhi Yuan

A subspace $U$ of $\mathbb{F}_q^n$ is called \textit{cyclically covering} if the whole space $\mathbb{F}_q^n$ is the union of the cyclic shifts of $U$. The case $\mathbb{F}_q^n$ itself is the only covering subspace, is of particular interest. Recently, Huang solved this problem completely under the condition $\gcd(n, q)=1$ using primitive idempotents and tra

Xiangyu Chen, Jixiang Luo, Jingyu Xu, Fangqiu Yi

Whether a video can be compressed at an extreme compression rate as low as 0.01%? To this end, we achieve the compression rate as 0.02% at some cases by introducing Generative Video Compression (GVC), a new framework that redefines the limits of video compression by leveraging modern generative video models to achieve extreme compression rates while preservi

Rainer Spurzem

From NBODY1 to NBODY6 : The Growth of an Industry is the title of a 1999 invited review by Sverre Aarseth, for Publications of the Astronomical Society of the Pacific (PASP). I took this as an inspiration for the title of this paper; it describes how Sverres NBODY Industry has further grown since 90s of the previous century, and how it is further flourishing

Meiqi Chen, Fandong Meng, Jie Zhou

Complex reasoning problems often involve implicit spatial and geometric relationships that are not explicitly encoded in text. While recent reasoning models perform well across many domains, purely text-based reasoning struggles to capture structural constraints in complex settings. In this paper, we introduce FIGR, which integrates executable visual constru

Jiatai Tong, Yilin Zhu, Thiago Serra, Samuel Burer

When optimizing a nonlinear objective, one can employ a neural network as a surrogate for the nonlinear function. However, the resulting optimization model can be time-consuming to solve globally with exact methods. As a result, local search that exploits the neural-network structure has been employed to find good solutions within a reasonable time limit. Fo

Md. Enamul Hoq, Linda Larson-Prior, Fred Prior

Robust preprocessing is rarely quantified in deep-learning pipelines for low-dose CT (LDCT) lung cancer screening. We develop and validate Virtual-Eyes, a clinically motivated 16-bit CT quality-control pipeline, and measure its differential impact on generalist foundation models versus specialist models. Virtual-Eyes enforces strict 512x512 in-plane resoluti

Likun Cao, James Evans

This study offers a new perspective on the depth-versus-breadth debate in innovation strategy, by modeling inventive search within dynamic collective knowledge systems, and underscoring the importance of timing for technological impact. Using frontier machine learning to project patent citation networks in hyperbolic space, we analyze 4.9 million U.S. patent

Joaquim Borges, Josep Rifà, Victor Zinoviev

We investigate when a maximum distance separable ($MDS$) code over $F_q$ is also completely regular ($CR$). For lengths $n=q+1$ and $n=q+2$ we provide a complete classification of the $MDS$ codes that are $CR$ or at least uniformly packed in the wide sense ($UPWS$). For the more restricted case $n\leq q$ with $q\leq 5$ we obtain a full classification (up to

Xu Shi, Yinglin Du, Rufeng Xiao, Rujun Jiang

Existing methods for nonconvex bilevel optimization (NBO) require prior knowledge of first- and second-order problem-specific parameters (e.g., Lipschitz constants and the Polyak-{\L}ojasiewicz (P{\L}) parameters) to set step sizes, a requirement that poses practical limitations when such parameters are unknown or computationally expensive. We introduce the

F. D. Amaro, R. Antonietti, E. Baracchini, L. Benussi

Optical-readout Time Projection Chambers (TPCs) produce megapixel-scale images whose fine-grained topological information is essential for rare-event searches, but whose size challenges real-time data selection. We present an unsupervised, reconstruction-based anomaly-detection strategy for fast Region-of-Interest (ROI) extraction that operates directly on m

Jonathan Schmoll, Adam Jatowt

The manual, resource-intensive process of complying with the EU Taxonomy presents a significant challenge for companies. While Large Language Models (LLMs) offer a path to automation, research is hindered by a lack of public benchmark datasets. To address this gap, we introduce a novel, structured dataset from 190 corporate reports, containing ground-truth e

Yinuo Zhao, Huiqian Jin, Lechun Jiang, Xinyi Zhang

Real-world reinforcement learning (RL) offers a promising approach to training precise and dexterous robotic manipulation policies in an online manner, enabling robots to learn from their own experience while gradually reducing human labor. However, prior real-world RL methods often assume that human interventions are optimal across the entire state space, o

Abhiram Soori

Altermagnets exhibit spin-split electronic bandstructures despite having zero net magnetization, making them attractive for field-free spintronic applications. In this work, we show that a finite rectangular altermagnetic sample can acquire a net spin polarization purely due to its geometry. This effect arises from the interplay between the anisotropic, spin

Yanbing Yang, Huiling Zhu, Wenchi Cheng, Jingqing Wang

Federated Learning (FL) enables mobile edge devices, functioning as clients, to collaboratively train a decentralized model while ensuring local data privacy. However, the efficiency of FL in wireless networks is limited not only by constraints on communication and computational resources but also by significant data heterogeneity among clients, particularly

Rajesh Senapati, Ashish Kumar Nandi

Recently, the weak Drazin inverse and its characterization have been crucial studies for matrices of index k. In this article, we have revisited W-weighted DMP and MPD inverses and constructed a general class of unique solutions to certain matrix equations. Moreover, we have generalized the W-weighted Drazin inverse of Meng, 2017 using the minimal rank Wweig

Ruitong Li, Lin Zhang, Yuenan Zhao, Chengxin Liu

Deep reinforcement learning (DRL) methods have demonstrated potential for autonomous navigation and obstacle avoidance of unmanned ground vehicles (UGVs) in crowded environments. Most existing approaches rely on single-frame observation and employ simple concatenation for multi-modal fusion, which limits their ability to capture temporal context and hinders

Alexander I. Bufetov, Ilya I. Zavolokin

The aim of this note is to present the simple observation that a slight refinement of the Contraction Mapping Principle allows one to recover the precise convergence rate in the Picard-Lindel\"of Theorem.

Attila Portik, Orsolya Kálmán, Tamás Kiss

We study measurement-induced nonlinear dynamics generated by an iterated quantum protocol combining an entangling gate, a single-qubit rotation, and post-selection. For pure single-qubit inputs, a particular choice of the single-qubit unitary yields globally chaotic, strongly mixing dynamics that explores the entire Bloch sphere, providing a physical realiza

Spyridon Syntakas, Kostas Vlachos

This paper presents a novel safe control framework that integrates Sliding Mode Control (SMC), High-Order Control Barrier Functions (HOCBFs) with state-dependent adaptiveness and a lightweight projection for collision-free navigation of an over-actuated 3-DOF marine surface vessel subjected to strong environmental disturbances (wind, waves, and current). SMC

S. Shukla, P. C. Srivastava

In the present work, we study nuclear structure properties of the $^{184-194}$Pb isotopes within the framework of the nuclear shell-model. We have performed shell-model calculations using KHH7B and KHHE interactions. We have reported results for energy spectra, electromagnetic properties such as quadrupole moment ($Q$), magnetic moment ($\mu$), $B(E2)$, and

Zicheng Qian

Let $n\geq 2$ be an integer, $p$ be a prime number and $K$ be a finite extension of $\mathbb{Q}_p$. Motivated by Schraen's thesis and Gehrmann's definition of automorphic simple $\mathscr{L}$-invariants, we study the first non-vanishing extension groups between a pair of locally $K$-analytic generalized Steinberg representations of $\mathrm{GL}_n(K)$. We stu

Jia Yu, Yan Zhu, Peiyao Fu, Tianyi Chen

Rare gastrointestinal lesions are infrequently encountered in routine endoscopy, restricting the data available for developing reliable artificial intelligence (AI) models and training novice clinicians. Here we present EndoRare, a one-shot, retraining-free generative framework that synthesizes diverse, high-fidelity lesion exemplars from a single reference

Yuan Jia, Ruimin Wu, Rui Song, Jiaojiao Li

Traditional image stitching techniques have predominantly utilized two-dimensional homography transformations and mesh warping to achieve alignment on a planar surface. While effective for scenes that are approximately coplanar or exhibit minimal parallax, these approaches often result in ghosting, structural bending, and stretching distortions in non-overla

Souvik Chatterjee, Prasenjit Deb, Chandan Datta, Pankaj Agrawal

Multipartite entangled states possess a number of non-intuitive properties, making them a useful resource for various quantum information-processing tasks. The three-qubit W-state is one such example where every state is robust to single-qubit loss. However, this state is not suitable for deterministic distribution, and deterministic communication protocols.

Valts Krumins, Ivars Krastins, Oskars Rudzitis, Reinis Lazda

In this work we present a compact and portable tabletop magnetometer that utilizes negatively charged nitrogen-vacancy (NV) centers in diamond. The magnetometer is operated using a dual microwave resonance detection approach in combination with an optically detected magnetic resonance (ODMR) technique (mitigating drifts in results due to changes of the diamo

Jiawei Zhang, Chengchao Bai, Wei Pan, Tianhang Liu

Constrained motion planning is a common but challenging problem in robotic manipulation. In recent years, data-driven constrained motion planning algorithms have shown impressive planning speed and success rate. Among them, the latent motion method based on manifold approximation is the most efficient planning algorithm. Due to errors in manifold approximati

Bin Chen, Pan Feng

Bitcoin derives a verifiable temporal order from probabilistic block discovery and cumulative proof-of-work rather than from a trusted global clock. We show that block arrivals exhibit stable exponential behavior across difficulty epochs, and that the proof-of-work process maintains a high-entropy search state that collapses discretely upon the discovery of

Zhe Huang, Hao Wen, Aiming Hao, Bingze Song

Multimodal Large Language Models (MLLMs) have made remarkable progress in video understanding. However, they suffer from a critical vulnerability: an over-reliance on language priors, which can lead to visual ungrounded hallucinations, especially when processing counterfactual videos that defy common sense. This limitation, stemming from the intrinsic data i

Pankayaraj Pathmanathan, Michael-Andrei Panaitescu-Liess, Cho-Yu Jason Chiang, Furong Huang

Retrieval-Augmented Generation (RAG) has emerged as a promising paradigm to enhance large language models (LLMs) with external knowledge, reducing hallucinations and compensating for outdated information. However, recent studies have exposed a critical vulnerability in RAG pipelines corpus poisoning where adversaries inject malicious documents into the retri

Lucas S. Sousa

It was previously shown that a D7 brane probe in a D3 brane background with a pure gauge constant magnetic field $\mathrm{B} = \mathrm{H}$ exhibits chiral symmetry breaking and a discrete meson spectrum with Zeeman splitting. In this work, we investigate how these features are modified by a TsT deformation of the background, which renders the Kalb Ramond fie

Alexey Talambutsa

We establish several results on the word problem for just infinite groups. First, for finitely generated just infinite groups we show that the word problem is uniformly decidable for presentations with recursively enumerable sets of relations. Our proof does not use the Wilson--Grigorchuk theorem on the classification of just infinite groups and proceeds dir

Ziqing Fan, Yuqiao Xian, Yan Sun, Li Shen

A fine-grained data recipe is crucial for pre-training large language models, as it can significantly enhance training efficiency and model performance. One important ingredient in the recipe is to select samples based on scores produced by defined rules, LLM judgment, or statistical information in embeddings, which can be roughly categorized into quality an

Partha Rana, Sriparna Bandopadhyay

A sign pattern is a matrix whose entries are from the set $\{+,-, 0\}$. A square sign pattern $A$ is called sign $k$-potent if $k$ is the smallest positive integer for which $A^{k+1}=A$, and for $k=1$, $A$ is called sign idempotent. In 1993, Eschenbach \cite{01} gave an algorithm to construct sign idempotent sign patterns. However, Huang \cite{02} constructe

Lijun Zhang, Lin Li, Wei Wei, Yajie Qi

When fine-tuning pre-trained Language Models (LMs) to exhibit desired behaviors, maintaining control over risk is critical for ensuring both safety and trustworthiness. Most existing safety alignment methods, such as Safe RLHF and SACPO, typically operate under a risk-neutral paradigm that is insufficient to address the risks arising from deviations from the

Manish Das, Sushil Sharma, Ermias Yitayew Beyene, Aleksander Bilewicz

Positronium Lifetime Imaging (PLI) extends positron emission tomography by using the lifetime of positronium atoms as a probe of tissue molecular architecture. In this work, we report the first PLI measurements performed with $^{52}$Mn and $^{55}$Co using the modular J-PET. Four samples were studied in each experiment: two Certified Reference Materials (poly

Zhi Li, Yaqi Wang, Bingtao Ma, Yifan Zhang

Metal artifacts in Dental CBCT severely obscure anatomical structures, hindering diagnosis. Current deep learning for Metal Artifact Reduction (MAR) faces limitations: supervised methods suffer from spectral blurring due to "regression-to-the-mean", while unsupervised ones risk structural hallucinations. Denoising Diffusion Models (DDPMs) offer realism but r

Michael E. Rose, Mainak Ghosh, Sebastian Erhardt, Cheng Li

We develop a language similarity model suitable for working with patents and scientific publications at the same time. In a horse race-style evaluation, we subject eight language (similarity) models to predict credible Patent-Paper Citations. We find that our Pat-SPECTER model performs best, which is the SPECTER2 model fine-tuned on patents. In two real-worl

Han Zhen Li, Yu Hu, Lai Zhang, Hong Bo Sun

Cycloidal propellers are known for their omnidirectional vectored thrust, enabling smooth transitions between hovering and forward flight, making them ideal for unmanned aerial vehicles (UAVs) and electric vertical take-off and landing (eVTOL) aircraft. However, cycloidal propellers tend to have lower hovering efficiency compared to screw propellers. Adding

J. H. Gillanders, A. Flors, R. Ferreira da Silva

Spectroscopic observations of the kilonova AT 2017gfo provide a unique opportunity to identify signatures from individual heavy elements freshly synthesised via the r-process, the nucleosynthetic channel responsible for producing $\sim$half of all trans-iron-group elements. Limitations in the available atomic data have historically hampered comprehensive lin

Dominic Batzler, Robin Größle, Philipp Haag, Elizabeth Paine

Tritium adsorption on surfaces creates a variety of issues, ranging from the fields of fusion applications to small and large-scale laboratory experiments using tritium. The extent to which tritium accumulates on surfaces is generally material-dependent and must be determined through experiments. Additionally, this surface contamination necessitates the impl

Jiping Yu, Xiaowei Zhu, Kun Chen, Guanyu Feng

Trusted processors provide a way to perform joint computations while preserving data privacy. To overcome the performance degradation caused by data-oblivious algorithms to prevent information leakage, we explore the benefits of oblivious memory (OM) integrated in processors, to which the accesses are unobservable by adversaries. We focus on graph analytics,

Alireza Rafiei, Farshid Hajati, Alireza Rezaee, Amirhossien Panahi

Sepsis, characterized by a dysregulated immune response to infection, results in significant mortality, morbidity, and healthcare costs. The timely prediction of sepsis progression is crucial for reducing adverse outcomes through early intervention. Despite the development of numerous models for Intensive Care Unit (ICU) patients, there remains a notable gap

Adrian Pastine, Victor Nicolas Schvöllner

We introduce and study a loopless multigraph associated with a split graph $S$: the factor graph of $S$, denoted by $\Phi(S)$, which encodes the combinatorial information about 2-switch transformations over $S$. This construction provides a cleaner, compact and non-redundant alternative to the graph $A_4(S)$ by Barrus and West, for the particular case of spl

Pengfu Wan, Jiawei Chen, Gangyan Xu

The Fleet Size and Mix Vehicle Routing Problem (FSMVRP) is a prominent variant of the Vehicle Routing Problem (VRP), extensively studied in operations research and computational science. FSMVRP requires simultaneous decisions on fleet composition and routing, making it highly applicable to real-world scenarios such as short-term vehicle rental and on-demand

Wenchao Li, Xuezhi Wang, Qiang Sun, Allison N. Kealy

Magnetic monitoring of maritime environments is an important problem for monitoring and optimising shipping, as well as national security. New developments in compact, fibre-coupled quantum magnetometers have led to the opportunity to critically evaluate how best to create such a sensor network. Here we explore various magnetic sensor network architectures f

Fuqiang Gu, Jiangshan Ai, Xu Lu, Xianlei Long

Unmanned Aerial Vehicles (UAVs) play an important role in various applications, where precise trajectory tracking is crucial. However, conventional control algorithms for trajectory tracking often exhibit limited performance due to the underactuated, nonlinear, and highly coupled dynamics of quadrotor systems. To address these challenges, we propose HBO-PID,

Partha Rana, Sriparna Bandopadhyay

A sign pattern is a matrix that has entries from the set $\{+,-,0\}$. An $n\times n$ sign pattern $\mathcal{P}$ is called consistent if every real matrix in its qualitative class has exactly $k$ real eigenvalues and $n-k$ nonreal eigenvalues for some integer $k$, with $1\leq k\leq n$. In the article \cite{1}, the authors established a necessary condition for

Yi-Bo Shen, Zhi-Wei Liu, Ming-Zhu Liu, Rui-Xiang Shi

Over the past two decades, numerous exotic hadron states have been discovered, yet their underlying nature remains unclear. It is widely acknowledged that understanding hadron-hadron interactions is essential to unraveling their properties. Hadron spectroscopy is a powerful tool for this endeavor, providing rich experimental data that can shed light on exoti

Jie Luo, Wenyu Zhang, Xinming Zhang, Yuan Fang

Incorporating item-side information, such as category and brand, into sequential recommendation is a well-established and effective approach for improving performance. However, despite significant advancements, current models are generally limited by three key challenges: they often overlook the fine-grained temporal dynamics inherent in timestamps, exhibit

Hoseob Seo, Sungmin Yoo, Jihun Yum

We present a new Schwarz Lemma for bounded domains with Bergman metrics. The key ingredient of our proof is the Cauchy-Schwarz inequality from probability theory.

Fuqiang Gu, Yuanke Li, Xianlei Long, Kangping Ji

Semantic segmentation is a fundamental task in computer vision with wide-ranging applications, including autonomous driving and robotics. While RGB-based methods have achieved strong performance with CNNs and Transformers, their effectiveness degrades under fast motion, low-light, or high dynamic range conditions due to limitations of frame cameras. Event ca

Jack Allsop, Ander Lamaison, Richard Lang, Silas Rathke

We study minimum vertex-degree conditions in 3-uniform hypergraphs for (tight) spanning components and (combinatorial) surfaces. Our main results show that a 3-uniform hypergraph $G$ on $n$ vertices contains a spanning component if $\delta_1(G) \gtrsim \tfrac{1}{2} \binom{n}{2}$ and a spanning copy of any surface if $\delta_1(G) \gtrsim \tfrac{5}{9} \binom{n

Zhen-Cheng Liao, Cong Xiao, Zhi Wang, Qian Niu

We develop a semiclassical theory of superconducting quasiparticles for proximity-induced superconducting systems, where spin-orbit coupling plays a critical role in shaping the quasiparticle dynamics. We reveal the structure of superconducting Berry curvatures in such systems, and derived the superconducting Berry curvature induced thermal Edelstein effect