March 2025 arXiv papers — page 167

Alejandro Tlaie, Jimmy Farrell

This paper examines the critical challenges and potential solutions for conducting secure and effective external evaluations of general-purpose AI (GPAI) models. With the exponential growth in size, capability, reach and accompanying risk of these models, ensuring accountability, safety, and public trust requires frameworks that go beyond traditional black-b

M. Ceglie, G. Violano, L. Afferrante, N. Menga

Since Hertz's pioneering work in 1882, contact mechanics traditionally grounds on linear elasticity, assuming small strains and displacements. However, recent experiments clearly highlighted linear elasticity limitations in accurately predicting the contact behaviour of rubbers and elastomers, particularly during frictional slip, which is governed by geometr

Rene Alvarez-Donado, Matias Sepulveda-Macias, Anne Tanguy

We employed molecular dynamics simulations to explore comparatively the thermo-mechanical behavior of two glass materials-an oxide silica glass (SiO2) and a binary Cu-Zr-based metallic alloy (Cu50Zr50)-during shear and elongation deformation cycles. By calculating the energy balance and tracking the temperature evolution of both glasses under deformation cyc

Guiwei Zhang, Tianyu Zhang, Mohan Zhou, Yalong Bai

We propose V2Flow, a novel tokenizer that produces discrete visual tokens capable of high-fidelity reconstruction, while ensuring structural and latent distribution alignment with the vocabulary space of large language models (LLMs). Leveraging this tight visual-vocabulary coupling, V2Flow enables autoregressive visual generation on top of existing LLMs. Our

Yanran Xu, Klaus-Peter Zauner, Danesh Tarapore

Navigating autonomous robots through dense forests and rugged terrains is especially daunting when exteroceptive sensors -- such as cameras and LiDAR sensors -- fail under occlusions, low-light conditions, or sensor noise. We present Blind-Wayfarer, a probing-driven navigation framework inspired by maze-solving algorithms that relies primarily on a compass t

Chengrui Zhu, Ryoichi Ishikawa, Masataka Kagesawa, Tomohisa Yuzawa

Reconstructing three-dimensional (3D) structures from two-dimensional (2D) X-ray images is a valuable and efficient technique in medical applications that requires less radiation exposure than computed tomography scans. Recent approaches that use implicit neural representations have enabled the synthesis of novel views from sparse X-ray images. However, alth

Radek Novotný, Jan Chochol, Vladimír Kafka, Adam Klimsza

This contribution will delve into the design and performance of the newly produced Silicon Carbide Low Gain Avalanche Detectors (4H-SiC LGADs) and provide a comprehensive summary of their measured characteristics. This includes an analysis of the detector's performance, temperature stability, and the effectiveness of the internal gain layer in improving sign

Thomas Bagrel, Arnaud Spiwack

Destination passing -- aka. out parameters -- is taking a parameter to fill rather than returning a result from a function. Due to its apparently imperative nature, destination passing has struggled to find its way to pure functional programming. In this paper, we present a pure functional calculus with destinations at its core. Our calculus subsumes all the

Comlan Edmond Koudjinan, Rafael Ramírez-Ros

We find necessary and sufficient conditions for high-order persistence of resonant caustics in perturbed circular billiards. The main tool is a perturbation theory based on the Bialy-Mironov generating function for convex billiards. All resonant caustics with period $q$ persist up to order $\lceil q/n \rceil -1$ under any polynomial deformation of the circle

Bangyan Li, Wenxuan Huang, Zhenkun Gao, Yeqiang Wang

Recently, Multimodal Large Language Models (MLLMs) have demonstrated exceptional capabilities in visual understanding and reasoning across various vision-language tasks. However, we found that MLLMs cannot process effectively from fine-grained medical image data in the traditional Visual Question Answering (VQA) pipeline, as they do not exploit the captured

Mahmoud Kalash, Aditya Sudharsanam, M. H. M. Passos, Valentina Parigi

Multimode squeezed light is a key resource for high-dimensional quantum technologies, enhancing metrological sensitivity, boosting communication security, and enabling parallel processing in computation. Its practical potential, however, remains constrained by the inherent single-mode operation of homodyne detection, necessitating post-processing for multimo

Zongzheng Zhang, Xinrun Li, Sizhe Zou, Guoxuan Chi

Lane topology extraction involves detecting lanes and traffic elements and determining their relationships, a key perception task for mapless autonomous driving. This task requires complex reasoning, such as determining whether it is possible to turn left into a specific lane. To address this challenge, we introduce neuro-symbolic methods powered by vision-l

A. Ellien, M. Montes, S. L. Ahad, P. Dimauro

Intracluster light (ICL) provides a record of the dynamical interactions undergone by clusters, giving clues on cluster formation and evolution. Here, we analyse the properties of ICL in the massive cluster Abell 2390 at redshift z=0.228. Our analysis is based on the deep images obtained by the Euclid mission as part of the Early Release Observations in the

Géry de Saxcé

In this work, we revisit Kaluza-Klein theory from the perspective of the classification of elementary particles based on the coadjoint orbit method. We propose a symmetry group for which the electric charge is invariant and, on this basis, a cosmological scenario in which the three former spatial dimensions inflate quickly while the fifth one shrinks, leadin

Yitang Li, Mingxian Lin, Zhuo Lin, Yipeng Deng

Existing motion generation methods based on mocap data are often limited by data quality and coverage. In this work, we propose a framework that generates diverse, physically feasible full-body human reaching and grasping motions using only brief walking mocap data. Base on the observation that walking data captures valuable movement patterns transferable ac

Prabhash Kumar, Anu V. S. Nath, Mahesh Panchagnula, Anubhab Roy

We investigate the dynamics of small inertial particles in a two-dimensional, steady Taylor-Green vortex flow. A classic study by Taylor (2022) showed that heavy inertial point particles (having density parameter R = 1) are trapped by the flow separatrices when the particle Stokes number St, which measures the particle's inertia, is less than 1/4. Here, we c

Constantin Schempp, Yongzhou Zhang, Christian Friedrich, Bjorn Hein

Insertion tasks are fundamental yet challenging for robots, particularly in autonomous operations, due to their continuous interaction with the environment. AI-based approaches appear to be up to the challenge, but in production they must not only achieve high success rates. They must also ensure insertion quality and reliability. To address this, we introdu

Jiacheng Ruan, Wenzhen Yuan, Xian Gao, Ye Guo

Although large visual-language models (LVLMs) have demonstrated strong performance in multimodal tasks, errors may occasionally arise due to biases during the reasoning process. Recently, reward models (RMs) have become increasingly pivotal in the reasoning process. Specifically, process RMs evaluate each reasoning step, outcome RMs focus on the assessment o

Amber H. B. Fijn, Casper H. Stiekema, Stijn Boere, Marijan Višić

Limited availability of inorganic phosphate (Pi) in soil is an important constraint to plant growth. In order to understand better the underlying mechanism of plant response to Pi, the response to phosphate starvation in Arabidopsis thaliana was investigated through use of Petri Nets, a formal language suitable for bio-modeling. A. thaliana displays a range

Juan Carlos Acosta Matos, Panos Giannakeas, Matteo Ciardi, Thomas Pohl

$^4$He nanodroplets doped with an alkali ion feature a snowball of crystallized layers surrounded by superfluid helium. For large droplets, we predict that a transitional supersolid layer can form, bridging between the solid core and the liquid bulk, where the $^4$He density displays modulations of icosahedral group symmetry. To identify the different phases

Jiahui Zhang, Fangneng Zhan, Ling Shao, Shijian Lu

Anchor-based 3D Gaussian splatting (3D-GS) exploits anchor features in 3D Gaussian prediction, which has achieved impressive 3D rendering quality with reduced Gaussian redundancy. On the other hand, it often encounters the dilemma among anchor features, model size, and rendering quality - large anchor features lead to large 3D models and high-quality renderi

Fateme Jamshidi, Sina Akbari, Negar Kiyavash

We study the problem of closeness testing for continuous distributions and its implications for causal discovery. Specifically, we analyze the sample complexity of distinguishing whether two multidimensional continuous distributions are identical or differ by at least $\epsilon$ in terms of Kullback-Leibler (KL) divergence under non-parametric assumptions. T

Qinwen Deng, Hengxin Tan, Brenden R. Ortiz, Stephen D. Wilson

The recently discovered Kagome superconductor AV$_3$Sb$_5$ (where A refers to K, Rb, Cs) has stimulated widespread research interest due to its interplay of non-trivial topology and unconventional correlated physics including charge-density waves (CDW) and superconductivity. The essential prerequisite to understanding the microscopic mechanisms of this compl

Andrea Settimi, Julien Gamerro, Yves Weinand

Ordinary electric woodworking tools are integrated into a multiple-object-aware augmented framework to assist operators in fabrication tasks. This study presents an advanced evaluation of the developed open-source fabrication software Augmented Carpentry (AC), focusing on the technical challenges, potential bottlenecks, and precision of the proposed system,

K. Mawas, M. Maboudi, M. Gerke

Given the substantial growth in the use of additive manufacturing in construction (AMC), it is necessary to ensure the quality of printed specimens which can be much more complex than conventionally manufactured parts. This study explores the various aspects of geometry and surface quality control for 3D concrete printing (3DCP), with a particular emphasis o

Agrim Gupta, Shenggang Dong, Mehmet Mert Sahin, Younghan Nam

In the past decade, $>$1 Gsps ADCs have become commonplace and are used in many modern 5G base station chips. A major driving force behind this adoption is the benefits of digital up/down-conversion and improved digital filtering. Recent works have also advocated for utilizing this high sampling bandwidth to fit-in multiple MIMO streams, and reduce the numbe

Phu-Vinh Nguyen, Minh-Nam Tran, Long Nguyen, Dien Dinh

With the rapid development of natural language processing, many language models have been invented for multiple tasks. One important task is information retrieval (IR), which requires models to retrieve relevant documents. Despite its importance in many real-life applications, especially in retrieval augmented generation (RAG) systems, this task lacks Vietna

I. Y. Park, P. Y. Wui

We explore the implications of finite-temperature quantum field theory effects on cosmological parameters within the framework of the $\L$CDM model and its modification. By incorporating temperature-dependent corrections to the cosmological constant, we extend the standard cosmological model to include additional density parameters, $\Omega_{\L_2}$ and $\Ome

Pedro R. Nicácio Falcão, Piotr Sierant, Jakub Zakrzewski, Emanuele Tirrito

Nonstabilizerness, also known as ``magic'', quantifies the deviation of quantum states from stabilizer states, capturing the complexity necessary for quantum computational advantage. In this study, we investigate the dynamics of nonstabilizerness in disordered many-body localized (MBL) systems using the stabilizer R\'enyi entropy (SRE). Leveraging a phenomen

Zetao Cheng, Haoyu Li, Lei Zhang

We study the following Liouville system defined on a flat torus \begin{equation} \left\{ \begin{array}{lr} -\Delta u_i=\sum_{j=1}^n a_{ij}\rho_j\Big(\frac{h_j e^{u_j}}{\int_\Omega h_j e^{u_j}}-1\Big),\nonumber \\ u_j\in H_{per}^1(\Omega)\mbox{ for }i\in I=\{1,\cdots,n\}\nonumber, \end{array} \right. \end{equation} where $h_j\in C^3(\Omega)$, $h_j>0$, $\rho_j

Monika Feldmann, Michael Blanc, Killian P. Brennan, Iris Thurnherr

Supercell thunderstorms are the most hazardous thunderstorm category and particularly impactful to society. Their monitoring is challenging and often confined to the radar networks of single countries. By exploiting kilometer-scale climate simulations, a first-of-its-kind characterization of supercell occurrence in Europe is derived for the current and a war

Ao Wang, Lihao Liu, Hui Chen, Zijia Lin

Object detection and segmentation are widely employed in computer vision applications, yet conventional models like YOLO series, while efficient and accurate, are limited by predefined categories, hindering adaptability in open scenarios. Recent open-set methods leverage text prompts, visual cues, or prompt-free paradigm to overcome this, but often compromis

Jimmy Gammell, Anand Raghunathan, Abolfazl Hashemi, Kaushik Roy

While cryptographic algorithms such as the ubiquitous Advanced Encryption Standard (AES) are secure, *physical implementations* of these algorithms in hardware inevitably 'leak' sensitive data such as cryptographic keys. A particularly insidious form of leakage arises from the fact that hardware consumes power and emits radiation in a manner that is statisti

Ryugo Morita, Ko Watanabe, Jinjia Zhou, Andreas Dengel

Cognitive augmentation is a cornerstone in advancing education, particularly through personalized learning. However, personalizing extensive textual materials, such as narratives and academic textbooks, remains challenging due to their heavy use, which can hinder learner engagement and understanding. Building on cognitive theories like Dual Coding Theory --

P. Peralta-Braz, M. M. Alamdari, C. T. Chou, M. Hassan

Bearings are critical components in industrial machinery, yet their vulnerability to faults often leads to costly breakdowns. Conventional fault detection methods depend on continuous, high-frequency vibration sensing, digitising, and wireless transmission to the cloud-an approach that significantly drains the limited energy reserves of battery-powered senso

Almendra Awerkin, Elena De Giuli, Tiziano Vargiolu

We study the optimal management of a photovoltaic system's battery owned by a self-consumption group that aims to minimize energy consumption costs. We assume that the photovoltaic system is composed of a photovoltaic panel and a battery, where the photovoltaic panel produces energy according to a certain stochastic process. The management of the battery is

Matteo Rinaldi, Matthias Kick, Karsten Reuter, Christian Carbogno

Optoionics, a promising new field that aims at controlling ion dynamics using light, links photovoltaic power generation with electrochemical charge storage. This has the potential to drive and accelerate the energy revolution by utilizing materials that integrate the functionality of batteriesand photovoltaic cells. Finding, optimizing, and customizing thes

Lajos Diósi

We quote a definitive simple proof that neither classical stochastic dynamics nor quantum dynamics can be nonlinear if we stick to their standard statistical interpretations. A recently proposed optomechanical test of gravity's classicality versus quantumness is based on the nonlinear Schr\"odinger-Newton equation (SNE) which is the nonrelativistic limit of

Florian Kandra, Vera Demberg, Alexander Koller

It has been frequently observed that human speakers align their language use with each other during conversations. In this paper, we study empirically whether large language models (LLMs) exhibit the same behavior of conversational adaptation. We construct a corpus of conversations between LLMs and find that two LLM agents end up making more similar syntacti

Meng Zheng, Jiajin Zhang, Benjamin Planche, Zhongpai Gao

Image-Text Retrieval (ITR) finds broad applications in healthcare, aiding clinicians and radiologists by automatically retrieving relevant patient cases in the database given the query image and/or report, for more efficient clinical diagnosis and treatment, especially for rare diseases. However conventional ITR systems typically only rely on global image or

Andrea Mammola, Quentin Schaeverbeke, Matthieu M. Desjardins

Quantum processors operated through long range interaction mediated by a microwave resonator have been envisioned to allow for high connectivity. The ability to selectively operate qubits rely on the possibility to dynamically suppress the coupling between each qubit and the resonator, however there always remains a residual coupling. In this article, we inv

Antonio De Felice, Anamaria Hell

We study Proca theory with non-minimal coupling to gravity through the Ricci tensor and Ricci scalar interactions. We show that in the homogeneous and isotropic Universe together with cosmological constant, the temporal component of the vector field acquires a background value. As a result, we show that the theory propagates an additional degree of freedom,

Dylan J. Foster, Zakaria Mhammedi, Dhruv Rohatgi

Language model alignment (or, reinforcement learning) techniques that leverage active exploration -- deliberately encouraging the model to produce diverse, informative responses -- offer the promise of super-human capabilities. However, current understanding of algorithm design primitives for computationally efficient exploration with language models is limi

Karlo Jakac, Luka Lanča, Ante Sikirica, Stefan Ivić

Knowing the sea surface velocity field is essential for various applications, such as search and rescue operations and oil spill monitoring, where understanding the movement of objects or substances is critical. However, obtaining an accurate approximation of these advection processes is challenging, even with modern measuring equipment, such as high-frequen

Viktor Gilin, Sanne Laauwen, Yuying Xia, Noria Yousufi

Oxygen concentration in tumor micro-environment is a well-established signal that can induce aggressive cancer behaviour. In particular, low oxygen levels (hypoxia) activate the Hypoxia-Inducible Factor(HIF) pathway which has an array of target systems. One of these systems is Integrin-Linked Kinase (ILK) pathway, which influences key signaling pathways for

Sargam Yadav, Asifa Mehmood Qureshi, Abhishek Kaushik, Shubham Sharma

The introduction of transformer architecture was a turning point in Natural Language Processing (NLP). Models based on the transformer architecture such as Bidirectional Encoder Representations from Transformers (BERT) and Generative Pre-Trained Transformer (GPT) have gained widespread popularity in various applications such as software development and educa

Donát M. Takács, Tamás Fülöp, Róbert Kovács, Mátyás Szücs

In the vicinity of the liquid--vapor critical point, supercritical fluids behave strongly compressibly and, in parallel, thermophysical properties have strong state dependence. These lead to various peculiar phenomena, one of which being the piston effect where a sudden heating induces a mechanical pulse. The coupling between thermal and mechanical processes

James Davies, Meike Hatzel, Robert Hickingbotham

This paper investigates quasi-isometries between graphs with variable edge lengths. A quasi-isometry is a mapping between metric spaces that approximately preserves distances, allowing for a bounded amount of additive and multiplicative distortion. Recently, Nguyen, Scott, and Seymour conjectured that, by appropriately adjusting the edge lengths of the targe

Jeong Han Kim, BaoLinh Tran

Majority dynamics is a process on a simple, undirected graph $G$ with an initial Red/Blue color for every vertex of $G$. Each day, each vertex updates its color following the majority among its neighbors, using its previous color for tie-breaking. The dynamics achieves \textit{unanimity} if every vertex has the same color after finitely many days, and such c

Lo-Wei Tai, Ching-En Li, Cheng-Lin Chen, Chih-Jung Tsai

Principal Component Analysis (PCA), a classical dimensionality reduction technique, and 2D Gaussian representation, an adaptation of 3D Gaussian Splatting for image representation, offer distinct approaches to modeling visual data. We present EigenGS, a novel method that bridges these paradigms through an efficient transformation pipeline connecting eigenspa

Laura Johnson, Lorenzo Mella, Anita Pasotti

In this paper, we introduce the concept of a relative Heffter space which simultaneously generalizes those of relative Heffter arrays and Heffter spaces. Given a subgroup $J$ of an abelian group $G$, a relative Heffter space is a resolvable configuration whose points form a half-set of $G\setminus{J}$ and whose blocks are all zero-sum in $G$. Here we present

Lucas Farndale, Paul Henderson, Edward W Roberts, Ke Yuan

Self-supervised representation learning methods often fail to learn subtle or complex features, which can be dominated by simpler patterns which are much easier to learn. This limitation is particularly problematic in applications to science and engineering, as complex features can be critical for discovery and analysis. To address this, we introduce Split C

Steven A. H. de Rooij, Jochem J. A. Baselmans, Juan Bueno, Vignesh Murugesan

The presence of quasiparticles typically degrades the performance of superconducting microwave circuits. The readout signal can generate non-equilibrium quasiparticles, which lead to excess microwave loss and decoherence. To understand this effect quantitatively, we measure quasiparticle fluctuations and extract the quasiparticle density across different tem

Qinwen Deng, Hengxin Tan, Brenden R. Ortiz, Andrea Capa Salinas

In this work, we perform ultrafast time-resolved reflectivity measurements to study the symmetry breaking in the charge-density wave (CDW) phase of CsV$_3$Sb$_5$. By extracting the coherent phonon spectrum in the CDW phase of CsV$_3$Sb$_5$, we discover close phonon pairs near 1.3 THz and 3.1 THz, as well as a new mode at 1.84 THz. The 1.3 THz phonon pair and

Yasha Savelyev

We give a construction of ``quantum Maslov characteristic classes'', generalizing to higher dimensional cycles the Hu-Lalonde-Seidel morphism. We also state a conjecture extending this to an $A _{\infty}$ functor from the exact path category of the space of monotone Lagrangian branes to the Fukaya category. Quantum Maslov classes are used here for the study

Bo Cao, Yu Song, Jin Yang, Lei Li

Stuck pipe incidents are one of the major challenges in drilling engineering,leading to massive time loss and additional costs.To address the limitations of insufficient long sequence modeling capability,the difficulty in accurately establishing warning threshold,and the lack of model interpretability in existing methods,we utilize Crossformer for early sign

Zenny Wettersten, Olivier Mattelaer, Stefan Roiser, Andrea Valassi

As the quality of experimental measurements increases, so does the need for Monte Carlo-generated simulated events - both with respect to the total amount and to their precision. In perturbative methods, this involves the evaluation of higher order corrections to the leading order (LO) scattering amplitudes, including real emissions and loop corrections. Alt

Hamza El-Kebir, Melkior Ornik

This work presents a computationally efficient approach to data-driven robust contracting controller synthesis for polynomial control-affine systems based on a sum-of-squares program. In particular, we consider the case in which a system alternates between periods of high-quality sensor data and low-quality sensor data. In the high-quality sensor data regime

Tzu-Tao Chang, Shivaram Venkataraman

Cloud computing offers flexibility in resource provisioning, allowing an organization to host its batch processing workloads cost-efficiently by dynamically scaling the size and composition of a cloud-based cluster -- a collection of instances provisioned from the cloud. However, existing schedulers fail to minimize total cost due to suboptimal task and inst

Anoop Mutneja, Kenneth S. Schweizer

Yielding of amorphous glasses and gels is a mechanically driven transformation of a material from the solid to liquid state on the experimental timescale. It is a ubiquitous fundamental problem of nonequilibrium physics of high importance in material science, biology, and engineering applications such as processing, ink printing, and manufacturing. However,

Riccardo Mazzieri, Jacopo Pegoraro, Michele Rossi

The adoption of Millimeter-Wave (mmWave) radar devices for human sensing, particularly gait recognition, has recently gathered significant attention due to their efficiency, resilience to environmental conditions, and privacy-preserving nature. In this work, we tackle the challenging problem of Open-set Gait Recognition (OSGR) from sparse mmWave radar point

Kolja Klett, Benjamin Lindner

Neurons display spontaneous spiking (in the absence of stimulus signals) as well as a characteristic response to time-dependent external stimuli. In a simple but important class of stochastic neuron models, the integrate-and-fire model with Gaussian current noise, both aspects can mathematically be related via fluctuation-response relations (FRRs) as has bee

Feiran You, Hongyang Du, Xiangwang Hou, Yong Ren

Network optimization remains fundamental in wireless communications, with Artificial Intelligence (AI)-based solutions gaining widespread adoption. As Sixth-Generation (6G) communication networks pursue full-scenario coverage, optimization in complex extreme environments presents unprecedented challenges. The dynamic nature of these environments, combined wi

Patrick Bourg, Rodrigo Panosso Macedo, Andrew Spiers, Benjamin Leather

The ringdown of perturbed black holes has been studied since the 1970s, but until recently, studies have focused on linear perturbations. There is now burgeoning interest in nonlinear perturbative effects during ringdown. Here, using a hyperboloidal framework, we provide a complete treatment of linear and quadratic quasinormal modes (QNMs and QQNMs) in secon

Christian Schlager, Romain Albert, Gerhard Kirchmair

In traveling-wave parametric amplifiers (TWPAs) low-loss capacitors are necessary to provide 50 $\Omega$ impedance matching to the increased inductance that is brought in by the nonlinear elements used for amplification, be it Josephson junctions or high kinetic inductance materials. Here we report on the development of a fabrication process for vacuum-gap m

Rhys Taylor

[Edited for arXiv] Source extraction in HI radio surveys is still often performed using visual inspection, but the efficacy of such procedures lacks rigorous quantitative assessment due to their laborious nature. Algorithmic methods are often preferred due to their repeatable results and speed. I here quantitatively assess visual source extraction using a la

Jaewook Lee, Jeongah Lee, Wanyong Feng, Andrew Lan

Advances in large language models (LLMs) offer new possibilities for enhancing math education by automating support for both teachers and students. While prior work has focused on generating math problems and high-quality distractors, the role of visualization in math learning remains under-explored. Diagrams are essential for mathematical thinking and probl

Koustav Roy, Gourab Paul, Debika Debnath, Kuntal Bhattacharyya

We study nonreciprocal signatures of Josephson current (JC) in a quantum dot (QD)-based Josephson junction (JJ) that comprises of two periodically driven Kitaev chains (KCs) coupled with an intervening QD. The simultaneous breaking of the inversion symmetry ($\mathcal{IS}$) and the time-reversal symmetry ($\mathcal{TRS}$), indispensable for the Josephson dio

Lan Gao, Elana B Blinder, Abigail Barnes, Kevin Song

The growing use of technology in K--8 classrooms highlights a parallel need for formal learning opportunities aimed at helping children use technology safely and protect their personal information. Even the youngest students are now using tablets, laptops, and apps to support their learning; however, there are limited curricular materials available for eleme

Junkang Wu, Kexin Huang, Xue Wang, Jinyang Gao

Aligning large language models (LLMs) with human preferences is critical for real-world deployment, yet existing methods like RLHF face computational and stability challenges. While DPO establishes an offline paradigm with single hyperparameter $\beta$, subsequent methods like SimPO reintroduce complexity through dual parameters ($\beta$, $\gamma$). We propo

Ziliang Xiong, Shipeng Liu, Nathaniel Helgesen, Hongwei Li

Collision risk estimation and avoidance play central roles in the safety of autonomous driving (AD) systems. Recently emerged end-to-end AD systems gain collision avoidance ability by minimizing losses to penalize planning trajectories that are too close to other objects. Despite a significant collision rate during testing, most end-to-end planners do not ex

Zhangdi Liu, Ling An, Mengke Song, Zhuohang Yu

The design of inorganic catalysts and the prediction of their catalytic efficiency are fundamental challenges in chemistry and materials science. Traditional catalyst evaluation methods primarily rely on machine learning techniques; however, these methods often struggle to process multi-source heterogeneous data, limiting both predictive accuracy and general

Ryan Poon, Ian Hunter

This paper explores the design strategies for hybrid pole- or trunk-climbing robots, focusing on methods to inform design decisions and assess metrics such as adaptability and performance. A wheeled-grasping hybrid robot with modular, tendon-driven grasping arms and a wheeled drive system mounted on a turret was developed to climb columns of varying diameter

Fu-Tsun Wei

We establish Kronecker-type first and second limit formulas for "non-holomorphic" and "Jacobi-type" Eisenstein series over global function fields in the several-variable setting. Our main theorem demonstrates that the derivatives of these Eisenstein series can be understood as averaged integrals of certain period quantities along the associated "Heegner cycl

Ke Feng, Huabin Ge, Yunpeng Meng

Thurston's triangulation conjecture asserts that every hyperbolic 3-manifold admits a geometric triangulation into hyper-ideal hyperbolic tetrahedra. So far, this conjecture had only been proven for a few special 3-manifolds. In this article, we confirm this conjecture for a class of 3-manifolds. To be precise, let $M$ be an oriented compact 3-manifold with

Syed Danial Ali Shah, Zeinab Nezami, Maryam Hafeez, Syed Ali Raza Zaidi

The concept of AI-RAN as specified by the AI-RAN alliance is geared to explore a converged 6G platform that can support management, orchestration, and deployment of both AI and RAN workloads. This concept is central to the development of a 6G architecture that aims to exploit the accelerated compute capabilities for supporting both real-time signal processin

Tijs Konijn, Imaan Bijl, Lu Cao, Fons Verbeek

Due to the climate change, hay fever becomes a pressing healthcare problem with an increasing number of affected population, prolonged period of affect and severer symptoms. A precise pollen classification could help monitor the trend of allergic pollen in the air throughout the year and guide preventive strategies launched by municipalities. Most of the pol

Mingzhen Sun, Weining Wang, Gen Li, Jiawei Liu

The task of video generation requires synthesizing visually realistic and temporally coherent video frames. Existing methods primarily use asynchronous auto-regressive models or synchronous diffusion models to address this challenge. However, asynchronous auto-regressive models often suffer from inconsistencies between training and inference, leading to issu

Minwen Liao, Hao Bo Dong, Xinyi Wang, Kurban Ubul

Low-light enhancement has wide applications in autonomous driving, 3D reconstruction, remote sensing, surveillance, and so on, which can significantly improve information utilization. However, most existing methods lack generalization and are limited to specific tasks such as image recovery. To address these issues, we propose Gated-Mechanism Mixture-of-Expe

Shaobin Zhuang, Yiwei Guo, Yanbo Ding, Kunchang Li

Diffusion models have driven the advancement of vision generation over the past years. However, it is often difficult to apply these large models in downstream tasks, due to massive fine-tuning cost. Recently, Low-Rank Adaptation (LoRA) has been applied for efficient tuning of diffusion models. Unfortunately, the capabilities of LoRA-tuned diffusion models a

Omar Khan, JooYoung Seo

The proliferation of digital mental health (DMH) tracking services promises personalized support, yet accessibility barriers limit equal access. This study investigates blind community experiences with DMH tracking services across the United States as a step toward inclusive health technology design. Working with blind advocacy organizations, we distributed

Raffaele Resta

The adiabatic theorem states that when the time evolution of the Hamiltonian is "infinitely slow", a system, when started in the ground state, remains in the instantaneous ground state at all times. This, however, does not mean that the adiabatic evolution of a generic observable obtains simply as its expectation value over the instantaneous eigenstate. As a

Yan Tai, Luhao Zhu, Yunan Ding, Yiying Dong

Multimodal Large Language Models (MLLMs) demonstrate robust zero-shot capabilities across diverse vision-language tasks after training on mega-scale datasets. However, dense prediction tasks, such as semantic segmentation and keypoint detection, pose significant challenges for MLLMs when represented solely as text outputs. Simultaneously, current MLLMs utili

J. T. Gleeson, S. N. Sprunt, A. Jákli, P. Guragain

The remarkable material DIO presents fascinating behaviors. It has been extensively studied as one of the first materials exhibiting a ferroelectric nematic phase. However, at higher temperatures it exhibits what has been termed the Smectic ZA: identified as an orientationally ordered, antiferroelectric phase with a density modulation in direction perpendicu

Junzhe Wang

Autonomous navigation in intelligent mobile systems represents a core research focus within artificial intelligence-driven robotics. Contemporary path planning approaches face constraints in dynamic environmental responsiveness and multi-objective task scalability, limiting their capacity to address growing intelligent operation requirements. Decision-centri

Larry Guth

We survey large value problems, including the large value problem for Dirichlet polynomials, the restriction problem, and problems from computer science. We describe known techniques and open problems, drawing on perspectives from all three fields.

Jan Bok, Santiago Guzmán-Pro, Nikola Jedličková, César Hernández-Cruz

Given a finite set of $2$-edge-coloured graphs $\mathcal F$ and a hereditary property of graphs $\mathcal{P}$, we say that $\mathcal F$ expresses $\mathcal{P}$ if a graph $G$ has the property $\mathcal{P}$ if and only if it admits a $2$-edge-colouring not having any graph in $\mathcal F$ as an induced $2$-edge-coloured subgraph. We show that certain classic

Ankush Thakur, Renu Bala, H. S. Nataraj

We report electronic, vibrational, and rotational spectroscopic parameters for the ground state, X$^2\Sigma^{+}$, of singly charged aluminium monohalides, employing single-reference coupled-cluster theory with single and double excitations (CCSD) together with the relativistic basis sets. Higher order correlation effects coming from triple excitations are tr

Keshab Kauchha, Peifan Liu, Paresh Pradhan, Yuri Shvyd'ko

Cavity-based x-ray free-electron lasers (CBXFELs) represent a possible realization of fully coherent hard x-ray sources having high spectral brilliance along with a narrow spectral bandwidth of $\simeq 1 - 50$~meV, a high repetition pulse rate of $\simeq 1$~MHz, and good stability. A diagnostic tool is required to measure CBXFEL spectra with meV resolution a

Fadwa Hamdi Barakat

This paper presents a distinctive prime detection approach. This method use GM-(n+1) sequences to effectively eliminate complex numbers. The sequences, which consist of odd a number of (n+1), exclude all components except for the initial prime integer. Only the first prime number is presented. This research proposes an approach using this model to identify e

Xiaoping Sun, Sirui Zhuge, Hai Zhuge

The ability of tracing states of logistic transportations requires an efficient storage and retrieval of the state of logistic transportations and locations of logistic objects. However, the restriction of sharing states and locations of logistic objects across organizations from different countries makes it hard to deploy a centralized database for implemen

Athul Kunjipurayil, Marc Salinas, J. Piekarewicz

Pioneering electroweak measurements of the neutron skin thickness in lead-208 and calcium-48 are challenging our understanding of nuclear dynamics. Many theoretical models suggest that the slope of the symmetry energy controls the development of a neutron skin in neutron-rich nuclei. This led to the expectation that if lead-208 exhibits a large neutron skin,

Maximilian Tölle, Theo Gruner, Daniel Palenicek, Jonas Günster

Robot foundation models hold the potential for deployment across diverse environments, from industrial applications to household tasks. While current research focuses primarily on the policies' generalization capabilities across a variety of tasks, it fails to address safety, a critical requirement for deployment on real-world systems. In this paper, we intr

Nicolas Loizeau, Berislav Buča, Dries Sels

Solving short and long time dynamics of closed quantum many-body systems is one of the main challenges of both atomic and condensed matter physics. For locally interacting closed systems, the dynamics of local observables can always be expanded into (pseudolocal) eigenmodes of the Liouvillian, so called dynamical symmetries. They come in two classes - transi

Jan Rais, Hendrik van Hees, Carsten Greiner

The Lindblad master equation is a frequently used Markovian approach to describe open quantum systems in terms of the temporal evolution of a reduced density matrix. Here, the thermal environment is traced out to obtain an expression to describe the evolution of what is called a system: one particle or a chain of interacting particles, which is/are surrounde

Jonas Ney, Norbert Wehn

Industrial pumps are essential components in various sectors, such as manufacturing, energy production, and water treatment, where their failures can cause significant financial and safety risks. Anomaly detection can be used to reduce those risks and increase reliability. In this work, we propose a novel enhanced convolutional neural network (ECNN) to predi

Robert Lukoťka, Edita Máčajová, Jozef Rajník

A graph $G$ is cyclically $c$-edge-connected if there is no set of fewer than $c$ edges that disconnects $G$ into at least two cyclic components. We prove that if a $(k, g)$-cage $G$ has at most $2M(k, g) - g^2$ vertices, where $M(k, g)$ is the Moore bound, then $G$ is cyclically $(k - 2)g$-edge-connected, which equals the number of edges separating a $g$-cy

Qizhi Zheng, Ayang Zhao, Xinzhu Wang, Yanhong Bai

Participants: This study employed a combination of Vector Autoregression (VAR) model and Graph Neural Networks (GNN) to systematically construct dynamic causal inference. Multiple classic classification algorithms were compared, including Random Forest, Logistic Regression, XGBoost, Support Vector Machine (SVM), K-Nearest Neighbor (KNN), Gradient Boosting, a

Wenqiang Zu, Shenghao Xie, Hao Chen, Zhiqiang Chen

Foundation models pretrained on large-scale natural images are widely adapted to various cross-domain low-resource downstream tasks, benefiting from generalizable and transferable patterns captured by their representations. However, these representations are later found to gradually vanish during finetuning, accompanied by a degradation of model's original g

Kostyantyn Krutoy

We demonstrate that any full and faithful $*$-functor between approximable categories of locally finite coarse spaces induces a coarse embedding between the underlying spaces. Furthermore, we establish a general characterisation of such $*$-functors between approximable categories and prove that the functor associating each locally finite coarse space with i