October 2025 arXiv papers — page 150

Mohamed Essenhajy

This report investigates the main definitions and fundamental properties of the fractional two-sided quaternionic Dunkl transform in two dimensions. We present key results concerning its structure and emphasize its connections to classical harmonic analysis. Special attention is given to inversion, boundedness, spectral behavior, and explicit formulas for st

Hoang-Son Vo, Karina Kolmogortseva, Ngumimi Karen Iyortsuun, Hong-Duyen Vo

A large amount of valuable academic content is only available in its original language, creating a significant access barrier for the global student community. This is a challenge for translating in several subjects, such as history, culture, and the arts, where current automated subtitle tools fail to convey the appropriate pedagogical tone and specialized

Israel Mason-Williams, Gabryel Mason-Williams

AI policymakers are responsible for delivering effective governance mechanisms that can provide safe, aligned and trustworthy AI development. However, the information environment offered to policymakers is characterised by an unnecessarily low Signal-To-Noise Ratio, favouring regulatory capture and creating deep uncertainty and divides on which risks should

Filipe Laitenberger, Dawid Kopiczko, Cees G. M. Snoek, Yuki M. Asano

We introduce GateSkip, a simple residual-stream gating mechanism that enables token-wise layer skipping in decoder-only LMs. Each Attention/MLP branch is equipped with a sigmoid-linear gate that condenses the branch's output before it re-enters the residual stream. During inference we rank tokens by the gate values and skip low-importance ones using a per-la

Monique Spite, Beatriz Barbuy, Kefeng Tan

The light elements beryllium (Be; $Z=4$) and boron (B; $Z=5$) are mainly produced by spallation reactions between cosmic rays and carbon (C; $Z=6$), nitrogen (N; $Z=7$), and oxygen (O; $Z=8$) nuclei. Only traces of Be or B would have been produced in the Big Bang, but there could be a contribution from the $\nu$-process in type II supernovae. Their abundance

Seong-Joon Park, Hee-Youl Kwak, Yongjune Kim

For reliable large-scale quantum computation, quantum error correction (QEC) is essential to protect logical information distributed across multiple physical qubits. Taking advantage of recent advances in deep learning, neural network-based decoders have emerged as a promising approach to improve the reliability of QEC. We propose the qubit-centric transform

Shubham Chatterjee

Current neural re-rankers often struggle with complex information needs and long, content-rich documents. The fundamental issue is not computational--it is intelligent content selection: identifying what matters in lengthy, multi-faceted texts. While humans naturally anchor their understanding around key entities and concepts, neural models process text with

Juergen Hausen, Paul Weiss

We classify Q-factorial Gorenstein Fano non-degenerate complete intersection threefolds in fake weighted projective spaces.

Zihao Zhao, Christopher Yeh, Lingkai Kong, Kai Wang

Decision-focused learning (DFL) integrates predictive modeling and optimization by training predictors to optimize the downstream decision target rather than merely minimizing prediction error. To date, existing DFL methods typically rely on deterministic point predictions, which are often insufficient to capture the intrinsic stochasticity of real-world env

Shubham Chatterjee, Jeff Dalton

Neural IR has advanced through two distinct paths: entity-oriented approaches leveraging knowledge graphs and multi-vector models capturing fine-grained semantics. We introduce QDER, a neural re-ranking model that unifies these approaches by integrating knowledge graph semantics into a multi-vector model. QDER's key innovation lies in its modeling of query-d

Jiateng Liu, Zhenhailong Wang, Xiaojiang Huang, Yingjie Li

Large Language Model (LLM)-based agentic systems rely on in-context policy documents encoding diverse business rules. As requirements grow, these documents expand rapidly, causing high computational overhead. This motivates developing internalization methods that embed policy documents into model priors while preserving performance. Prior prompt compression

Qingning Zhou, Kin Yau Wong

Two-phase sampling is commonly adopted for reducing cost and improving estimation efficiency. In many two-phase studies, the outcome and some cheap covariates are observed for a large sample in Phase I, and expensive covariates are obtained for a selected subset of the sample in Phase II. As a result, the analysis of the association between the outcome and c

Dounan Du, Eden Figueroa

Quantum memories are essential components of quantum networks, enabling synchronization, quantum repeaters, and long-distance entanglement distribution. Most ensemble-based realizations rely on dark-state polaritons (DSPs) in $\Lambda$-type systems that operate at near-infrared wavelengths, such as 795 nm in $^{87}$Rb, far from the telecom band where long fi

Ting Li, Yang Yang, Yipeng Yu, Liang Yao

Adversarial attacks on knowledge graph embeddings (KGE) aim to disrupt the model's ability of link prediction by removing or inserting triples. A recent black-box method has attempted to incorporate textual and structural information to enhance attack performance. However, it is unable to generate human-readable explanations, and exhibits poor generalizabili

Siddhartha Upadhyay, Ratnangshu Das, Pushpak Jagtap

In this work, we address the issue of controller synthesis for a control-affine nonlinear system to meet prescribed time reach-avoid-stay specifications. Our goal is to improve upon previous methods based on spatiotemporal tubes (STTs) by eliminating the need for circumvent functions, which often lead to abrupt tube modifications and high control effort. We

Renato Luis Garrido Cavalcante, Noor Ul Ain, Lorenzo Miretti, Slawomir Stanczak

We introduce mathematical tools and fixed point algorithms for optimal statistical max-min power control in cellular and cell-less massive MIMO systems. Unlike previous studies that rely on the use-and-then-forget (UatF) lower bound on Shannon achievable (ergodic) rates, our proposed framework can deal with alternative bounds that explicitly consider perfect

Macarena G. del Valle-Espinosa, Matilde Mingozzi, Bethan James, Ruben Sanchez-Janssen

Polycyclic Aromatic Hydrocarbons (PAHs) are key diagnostics of the physical conditions in the interstellar medium and are widely used to trace star formation in the mid-infrared (mid-IR). The relative strengths of mid-IR PAH emission features (e.g., 6.2, 7.7, 11.3 um) are sensitive to both the size and ionization state of the molecules and can be strongly in

Navdeep Rana, Ramin Golestanian

We present the phenomenology of the one dimensional non-reciprocal Cahn Hilliard model for varying non-reciprocity $(\alpha)$ and different boundary conditions. At small $\alpha$, a perturbed uniform state evolves to a defect laden configuration that lacks global polar order. Defects are the sources and sinks of travelling waves. For a given $\alpha$, defect

Hongyu Zhu, Lin Chen, Xin Jin, Mingsheng Shang

Multimodal Sentiment Analysis (MSA) integrates complementary features from text, video, and audio for robust emotion understanding in human interactions. However, models suffer from severe data scarcity and high annotation costs, severely limiting real-world deployment in social media analytics and human-computer systems. Existing Mixup-based augmentation te

David S. Robertson, Thomas Jaki

A key aspect of patient-focused drug development is identifying and measuring outcomes that are important to patients in clinical trials. Many medical conditions affect multiple symptom domains, and a consensus approach to determine the relative importance of the associated multiple outcomes ignores the heterogeneity in individual patient preferences. Patien

Thomas Lamby, Jean-Luc Marichal, Naïm Zenaïdi

We prove that every completely monotone function defined on a right-unbounded open interval admits a Newton series expansion at every point of that interval. This result can be viewed as an analog of Bernstein's little theorem for absolutely monotone functions. As an application, we use it to study principal indefinite sums, which are constructed via a broad

Walid Elbarz, Mohamed Bourriz, Hicham Hajji, Hamd Ait Abdelali

Foundation models are transforming Earth observation, but their potential for hyperspectral crop mapping remains underexplored. This study benchmarks three foundation models for cereal crop mapping using hyperspectral imagery: HyperSigma, DOFA, and Vision Transformers pre-trained on the SpectralEarth dataset (a large multitemporal hyperspectral archive). Mod

Sean M. O'Brien, Megan E. Schwamb, Christopher A. Watson, Louise D. Nielsen

We report the identification and characterization of a new binary system composed of two near-equal mass M-dwarfs. The binary NGTS-EB-8 was identified as a planet candidate in data from the Next Generation Transit Survey (NGTS) by citizen scientists participating in the Planet Hunters NGTS project. High-resolution spectroscopic observations reveal the system

Lennart Werner, Pol Eyschen, Sean Costello, Pierluigi Micarelli

Accurate real-time estimation of end effector interaction forces in hydraulic excavators is a key enabler for advanced automation in heavy machinery. Accurate knowledge of these forces allows improved, precise grading and digging maneuvers. To address these challenges, we introduce a high-accuracy, retrofittable 2D force- and payload estimation algorithm tha

Santiago Arranz-Olmos, Gilles Barthe, Lionel Blatter, Xingyu Xie

Constant-time (CT) verification tools are commonly used for detecting potential side-channel vulnerabilities in cryptographic libraries. Recently, a new class of tools, called speculative constant-time (SCT) tools, has also been used for detecting potential Spectre vulnerabilities. In many cases, these SCT tools have emerged as liftings of CT tools. However,

Tony Liimatainen, Yi-Hsuan Lin

We extend the study of inverse boundary value problems to the setting of fully nonlinear PDEs by considering an inverse source problem for the Monge-Amp\`ere equation \[ \det D^2 u = F. \] We prove that, on a convex Euclidean domain in the plane, the associated Dirichlet-to-Neumann (DN) map uniquely determines a positive source function $F$. The proof relies

François Clément, Stefan Steinerberger

We suppose we are given a list of points $x_1, \dots, x_n \in \mathbb{R}$, a target probability measure $\mu$ and are asked to add additional points $x_{n+1}, \dots, x_{n+m}$ so that $x_1, \dots, x_{n+m}$ is as close as possible to the distribution of $\mu$; additionally, we want this to be true uniformly for all $m$. We propose a simple method that achieves

Shuo Chen, Zhen Han, Haokun Chen, Bailan He

Open-weight Large Reasoning Models (LRMs) are approaching the capabilities of their frontier counterparts but pose significant safety concerns, as they are difficult to patch or monitor post-release. To prevent misuse, reasoning-based safety guardrails, where models explicitly reason on safety justifications before answering, have become a promising primary

Sophie Leanza, Jeseung Lee, Ruike Renee Zhao

Reconfigurable mechanical systems enable precise programmable control over structural properties, opening new opportunities in architected materials, adaptive devices, and multifunctional structures. Here, we introduce elastic rod origami (RodOri), a platform that exploits remarkably simple elements (pre-stressed, naturally curved rods) into a system with an

Damjan Kalšan, Denis Zavadski, Tim Küchler, Haebom Lee

Synthetic datasets are widely used for training urban scene recognition models, but even highly realistic renderings show a noticeable gap to real imagery. This gap is particularly pronounced when adapting to a specific target domain, such as Cityscapes, where differences in architecture, vegetation, object appearance, and camera characteristics limit downst

Kuanning Wang, Yongchong Gu, Yuqian Fu, Zeyu Shangguan

Scooping items with tools such as spoons and ladles is common in daily life, ranging from assistive feeding to retrieving items from environmental disaster sites. However, developing a general and autonomous robotic scooping policy is challenging since it requires reasoning about complex tool-object interactions. Furthermore, scooping often involves manipula

Aniket Gupta, Hanhui Wang, Charles Saunders, Aruni RoyChowdhury

Interactive 3D point cloud segmentation enables efficient annotation of complex 3D scenes through user-guided prompts. However, current approaches are typically restricted in scope to a single domain (indoor or outdoor), and to a single form of user interaction (either spatial clicks or textual prompts). Moreover, training on multiple datasets often leads to

Muhammad Arslan, Ishtiaq Ahmed, Muhammad Jamil Aslam, Saba Shafaq

The Lepton Flavor Universality ratio $R_{\tau/{\mu,e}}\left(D^{(*)}\right)$ poses a challenge to the Standard Model (SM), as B-factory experiments, BaBar, Belle, and the LHCb show $3.31\sigma$ deviations from their theoretical predictions. Utilizing the latest HFLAV averages and incorporating the branching ratio constraints $60\%$, $30\%$ and $10\%$ from the

Shreya Havaldar, Sunny Rai, Young-Min Cho, Lyle Ungar

Existing benchmarks that measure cultural adaptation in LLMs are misaligned with the actual challenges these models face when interacting with users from diverse cultural backgrounds. In this work, we introduce the first framework and benchmark designed to evaluate LLMs in realistic, multicultural conversational settings. Grounded in sociocultural theory, ou

Caglar Demir, Alkid Baci, N'Dah Jean Kouagou, Leonie Nora Sieger

In this paper, we present Ontolearn-a framework for learning OWL class expressions over large knowledge graphs. Ontolearn contains efficient implementations of recent stateof-the-art symbolic and neuro-symbolic class expression learners including EvoLearner and DRILL. A learned OWL class expression can be used to classify instances in the knowledge graph. Fu

Komal Gupta, Aditya Shrivastava

Governance of data, compliance, and business privacy matters, particularly for healthcare and finance businesses. Since the recent emergence of AI enterprise AI assistants enhancing business productivity, safeguarding private data and compliance is now a priority. With the implementation of AI assistants across the enterprise, the zero data retention can be

Saurabh Khanna, Xinxu Li

Large Language Models are trained on massive multilingual corpora, yet this abundance masks a profound crisis: of the world's 7,613 living languages, approximately 2,000 languages with millions of speakers remain effectively invisible in digital ecosystems. We propose a critical framework connecting empirical measurements of language vitality (real world dem

Javed Ali Khan, Muhammad Yaqoob, Mamoona Tasadduq, Hafsa Shareef Dar

The evolving pedagogy paradigms are leading toward educational transformations. One fundamental aspect of effective learning is relevant, immediate, and constructive feedback to students. Providing constructive feedback to large cohorts in academia is an ongoing challenge. Therefore, academics are moving towards automated assessment to provide immediate feed

Yungui Gong, Qing Gao, Xuchen Lu, Zhu Yi

The $O_k$ null test can not only assess whether the cosmic curvature is zero, therefore if true reducing degeneracies between cosmic curvature and other cosmological parameters, but also provide a model-independent check of compatibility between different data sets. However, traditional implementations often require absolute distance data from Type Ia supern

Nicoló Cibrario, Michela Negro

We present a statistical method based on scDEED to assess the reliability of a 2D embedding showing a low-dimensional representation of the distribution of Gamma-Ray Bursts (GRBs) detected by the Fermi Gamma-ray Burst Monitor (GBM). The original dataset consists of 12 waterfall plots for each event, which contain key information about the prompt emission of

Ting Yi

We present a unified framework that fully represents electromagnetic potentials, fields, and sources in vacuum, based on a reinterpretation of the classical Hertz-potential formalism. In this construction, $\phi$, $A$, $E$, $B$, $\rho$, and $J$ are systematically derived from a single vector wavefield $\Gamma(x, t)$ (called the "$\Gamma$-potential"), which i

Shaoze Li, Junhao Wu, Cheng Lu, Zhibin Deng

Convex separable quadratic optimization problems occur in many practical applications. In this paper, based on an iterative resolution scheme of the KKT system, we develop an efficient method for solving a quadratic programming problem with a convex separable objective function subject to multiple convex separable constraints. We show that the proposed appro

Nikolay Nechaev, Evgeniia Przhezdzetskaia, Viktor Gombolevskiy, Dmitry Umerenkov

Chest X-ray classification is vital yet resource-intensive, typically demanding extensive annotated data for accurate diagnosis. Foundation models mitigate this reliance, but how many labeled samples are required remains unclear. We systematically evaluate the use of power-law fits to predict the training size necessary for specific ROC-AUC thresholds. Testi

Gregoire Passault, Clement Gaspard, Olivier Ly

Recent developments of low cost off-the-shelf programmable components, their modularity, and also rapid prototyping made educational robotics flourish, as it is accessible in most schools today. They allow to illustrate and embody theoretical problems in practical and tangible applications, and gather multidisciplinary skills. They also give a rich natural c

Ying Chen, Guijing Duan, Yuejiu Zhao, Ning Xi

The $S=1/2$ antiferromagnetic Heisenberg chain is a paradigmatic quantum system hosting exotic excitations such as spinons and solitons, and forming random singlet state in the presence of quenched disorder. Realizing and distinguishing these excitations in a single material remains a significant challenge. Using nuclear magnetic resonance (NMR) on a high-qu

Kristoffer Arnsfelt Hansen, Xinhao Nie

We study the problem of computing stationary Nash equilibria in discounted perfect information stochastic games from the viewpoint of computational complexity. For two-player games we prove the problem to be in PPAD, which together with a previous PPAD-hardness result precisely classifies the problem as PPAD-complete. In addition to this we give an improved

Liu Yang, Huiyu Duan, Ran Tao, Juntao Cheng

Omnidirectional images (ODIs) provide full 360x180 view which are widely adopted in VR, AR and embodied intelligence applications. While multi-modal large language models (MLLMs) have demonstrated remarkable performance on conventional 2D image and video understanding benchmarks, their ability to comprehend the immersive environments captured by ODIs remains

Thomas W. Gries, Davide Regaldo, Yanyan Duan, Florian Scheler

Photoluminescence (PL) is a ubiquitous proxy for material quality in optoelectronic devices, widely used for high-throughput materials discovery. However, we demonstrate that in the presence of charge-selective contacts, PL loses its predictive reliability and can exhibit strong quenching even in highly efficient photovoltaic devices under open-circuit condi

Pan Peng, Christian Sohler, Yi Xu

Single-linkage clustering (SLC) is a fundamental method for hierarchical data analysis. In the distance setting, a $k$-clustering produced by SLC can be obtained by computing a minimum spanning tree (MST) and deleting its $k-1$ heaviest edges. This naturally induces a cost profile for the SLC hierarchy: for each $k\in[n]$, we define $\mathrm{cost}_k$ to be t

Jiayu Ding, Lei Cui, Li Dong, Nanning Zheng

Recent advances in Large Language Models (LLMs) show that extending the length of reasoning chains significantly improves performance on complex tasks. While revealing these reasoning traces helps users better follow, verify, and learn from the model's problem-solving process, it also makes them highly vulnerable to unauthorized distillation. To mitigate thi

Jacques L. Pienaar

In this article I compare two interpretations of quantum mechanics (QM) that draw inspiration from phenomenology: the London-Bauer-French interpretation (hereafter LBF) as articulated by Steven French, and QBism. I give special attention to certain disagreements between QBism and LBF identified French's work, as well as French's related claims that QBism may

Sebastian Opper

We compute the derived Picard groups of partially wrapped Fukaya categories of surfaces in the sense of Haiden-Katzarkov-Kontsevich and the related graded gentle algebras. This includes the wrapped cases as introduced by Bocklandt. An important ingredient for our proof in characteristic zero is the exponential map from Hochschild cohomology to the derived Pi

Neil Janwani, Varun Madabushi, Maegan Tucker

Reinforcement learning (RL) has emerged as a powerful method to learn robust control policies for bipedal locomotion. Yet, it can be difficult to tune desired robot behaviors due to unintuitive and complex reward design. In comparison, trajectory optimization-based methods offer more tuneable, interpretable, and mathematically grounded motion plans for high-

Yuchen Yan, Peiyan Zhang, Zhihua Liu, Hao Wang

Retrieval-augmented generation (RAG) has demonstrated its ability to enhance Large Language Models (LLMs) by integrating external knowledge sources. However, multi-hop questions, which require the identification of multiple knowledge targets to form a synthesized answer, raise new challenges for RAG systems. Under the multi-hop settings, existing methods oft

Chaofan Gan, Zicheng Zhao, Yuanpeng Tu, Xi Chen

Diffusion Transformers (DiTs) have recently emerged as a powerful backbone for visual generation. Recent observations reveal \emph{Massive Activations} (MAs) in their internal feature maps, yet their function remains poorly understood. In this work, we systematically investigate these activations to elucidate their role in visual generation. We found that th

Ba-Quang Nguyen

We propose a novel neural architecture named TextGraphFuseGAT, which integrates a pretrained transformer encoder (PhoBERT) with Graph Attention Networks for token-level classification tasks. The proposed model constructs a fully connected graph over the token embeddings produced by PhoBERT, enabling the GAT layer to capture rich inter-token dependencies beyo

Manaal Basha, Aimeê M. Ribeiro, Jeena Javahar, Cleidson R. B. de Souza

Understanding how developers interact with code generation tools (CGTs) requires detailed, real-time data on programming behavior which is often difficult to collect without disrupting workflow. We present \textit{CodeWatcher}, a lightweight, unobtrusive client-server system designed to capture fine-grained interaction events from within the Visual Studio Co

Vincenzo Norman Vitale, Antonia Maria Tulino, Andreas F. Molisch, Jaime Llorca

Timely delivery of delay-sensitive information over dynamic, heterogeneous networks is increasingly essential for a range of interactive applications, such as industrial automation, self-driving vehicles, and augmented reality. However, most existing network control solutions target only average delay performance, falling short of providing strict End-to-End

Enli Lin, Ziyuan Yang, Qiujing Lu, Jianming Hu

Realistic traffic simulation is critical for ensuring the safety and reliability of autonomous vehicles (AVs), especially in complex and diverse urban traffic environments. However, existing data-driven simulators face two key challenges: a limited focus on modeling dense, heterogeneous interactions at urban intersections - which are prevalent, crucial, and

Qingfeng Lyu

We prove that (1,1) non-L-space knots in $S^3$ and lens spaces are persistently foliar. This verifies the L-space knot conjecture of Delman-Roberts for (1,1) knots, thus providing positive evidence for the L-space conjecture.

M. S. Lundkvist, J. R. Larsen, Y. Li, M. L. Winther

HD 140283 is a well-studied metal-poor subgiant and a Gaia benchmark star, often used for testing stellar models due to its proximity, brightness, and low metallicity ([Fe/H] = -2.3 dex). Here we present the first asteroseismic analysis of HD 140283, providing improved constraints on its fundamental properties. The star was observed by TESS in 20-second cade

Alexandra Blessing Neamţu, Mazyar Ghani Varzaneh

We provide sign information for the top Lyapunov exponent for a stochastic differential equation driven by fractional Brownian motion. To this aim we analyze the stochastic dynamical system generated by such an equation, obtain a random dynamical system and construct an appropriate invariant measure. Suitable estimates for its density together with Birkhoff'

Matthias Huemmer, Theophile Shyiramunda, Michelle J. Cummings-Koether

This paper proposes a rigorous framework to examine the two-way relationship between artificial intelligence (AI), human cognition, problem-solving, and cultural adaptation across academic and business settings. It addresses a key gap by asking how AI reshapes cognitive processes and organizational norms, and how cultural values and institutional contexts sh

Yusheng Song, Lirong Qiu, Xi Zhang, Zhihao Tang

The detection of sophisticated hallucinations in Large Language Models (LLMs) is hampered by a ``Detection Dilemma'': methods probing internal states (Internal State Probing) excel at identifying factual inconsistencies but fail on logical fallacies, while those verifying externalized reasoning (Chain-of-Thought Verification) show the opposite behavior. This

G. Dransfield, M. Timmermans, D. Sebastian, B. V. Rackham

Giant planets orbiting low-mass stars on short orbits present a conundrum, as in the most extreme cases their existence cannot be reconciled with current models of core accretion. Therefore, surveys dedicated to finding these rare planets have a key role to play by growing the sample to overcome small number statistics. In this work we present MANGOS, a prog

Junming Duan

The active flux (AF) method is a compact high-order finite volume method originally proposed for solving hyperbolic conservation laws, that evolves cell averages together with point values shared by neighboring cells. This paper develops a compact fourth-order AF method for scalar degenerate convection--diffusion equations on Cartesian meshes. Fourth-order a

Luis F. Recalde, Dhruv Agrawal, Jon Arrizabalaga, Guanrui Li

MAVs have great potential to assist humans in complex tasks, with applications ranging from logistics to emergency response. Their agility makes them ideal for operations in complex and dynamic environments. However, achieving precise control in agile flights remains a significant challenge, particularly due to the underactuated nature of quadrotors and the

Sebastián Brzovic, Cristóbal Rojas, Andrés Abeliuk

Understanding the structural complexity and predictability of complex networks is a central challenge in network science. Although recent studies have revealed a relationship between compression-based entropy and link prediction performance, existing methods focus on single-scale representations. This approach often overlooks the rich hierarchical patterns t

C. Moutou, P. Petit, P. Charpentier, P. Cristofari

One of the first exoplanet hosts discovered thirty years ago, the star 55 Cnc has been constantly observed ever since. It is now known to host at least five planets with orbital periods ranging from 17 hours to 15 years. It is also one of the most extreme metal rich stars in the neighbourhood and it has a low-mass secondary star. In this article, we present

Riz Fernando Noronha, Kunihiko Kaneko

We introduce a minimal evolutionary model to show how local cooperation and global competition can create a transition to the diversity of communities such as linguistic groups. By using a lattice model with high-dimensional state agents and evolution under a fitness that depends on an agent's local neighborhood and global dissimilarity, clusters of diverse

Pengfei Zhu, Hai Zhang, Stefano Sfarra, Dazhi Yang

This review explores non-invasive imaging (NII) methods covering the mid- and far-infrared to the terahertz spectral regions (up to approximately 1000 um) for the detection and analysis of cultural heritage artifacts. In the thermal infrared domain, where radiation follows Planck's law, the self-emission of materials reveals intrinsic properties and internal

Kedi Ying, Ruiping Liu, Chongyan Chen, Mingzhe Tao

Walking assistance in extreme or complex environments remains a significant challenge for people with blindness or low vision (BLV), largely due to the lack of a holistic scene understanding. Motivated by the real-world needs of the BLV community, we build mmWalk, a simulated multi-modal dataset that integrates multi-view sensor and accessibility-oriented fe

Sifeddine Sellami, Juba Agoun, Lamia Yessad, Louenas Bounia

Sleep disorders have a major impact on patients' health and quality of life, but their diagnosis remains complex due to the diversity of symptoms. Today, technological advances, combined with medical data analysis, are opening new perspectives for a better understanding of these disorders. In particular, explainable artificial intelligence (XAI) aims to make

Yu-Song Cao, YanXia Liu, Ding-Fang Zeng

Gravitational wave echos from the coalescence of black hole binaries are often viewed as signals beyond general relativity or standard model. In this work, we show that these echos are inevitable in the black holes coalescence described by standard general relativity. This is because it is the physical black holes formed through gravitational collapse serve

Jeena Javahar, Tanya Budhrani, Manaal Basha, Cleidson R. B. de Souza

The use of AI code-generation tools is becoming increasingly common, making it important to understand how software developers are adopting these tools. In this study, we investigate how developers engage with Amazon's CodeWhisperer, an LLM-based code-generation tool. We conducted two user studies with two groups of 10 participants each, interacting with Cod

Shanthan Kumar Padisala, Bharatkumar Hegde, Ibrahim Haskara, Satadru Dey

Batteries degrade with usage and continuous cycling. This aging is typically reflected through the resistance growth and the capacity fade of battery cells. Over the years, various charging methods have been presented in the literature that proposed current profiles in order to enable optimal, fast, and/or health-conscious charging. However, very few works h

Yinchao Yang, Yahao Ding, Zhaohui Yang, Chongwen Huang

Real-time and contactless monitoring of vital signs, such as respiration and heartbeat, alongside reliable communication, is essential for modern healthcare systems, especially in remote and privacy-sensitive environments. Traditional wireless communication and sensing networks fall short in meeting all the stringent demands of eHealth, including accurate se

Alex Elwood, Tom Deakin, Justin Lovegrove, Chris Nelson

Discrete ordinates $S_N$ transport solvers on unstructured meshes pose a challenge to scale due to complex data dependencies, memory access patterns and a high-dimensional domain. In this paper, we review the performance bottlenecks within the shared memory parallelization scheme of an existing transport solver on modern many-core architectures with high cor

Jianhao Yuan, Fabio Pizzati, Francesco Pinto, Lars Kunze

Intuitive physics understanding in video diffusion models plays an essential role in building general-purpose physically plausible world simulators, yet accurately evaluating such capacity remains a challenging task due to the difficulty in disentangling physics correctness from visual appearance in generation. To the end, we introduce LikePhys, a training-f

Erman Isik, Antonio Lei

We study the boundedness of the Mordell-Weil rank and the growth of the $v$-primary part of the Tate-Shafarevich group of $p$-supersingular abelian varieties of ${\rm GL}_2$-type with real multiplication over $\mathbb{Z}_p$-extensions of number fields, where $v$ is a prime lying above $p$. Building on the work of Iovita-Pollack in the case of elliptic curves

Dmitry Artamonov

The paper presents a construction of finite-dimensional irreducible representations of the Lie algebra $\mathfrak{g}_2$. The representation space is constructed as the space of solutions to a certain system of partial differential equations of hypergeometric type, which is closely related to the Gelfand-Kapranov-Zelevinsky systems. This connection allows for

Ruiping Liu, Junwei Zheng, Yufan Chen, Zirui Wang

Physical environments and circumstances are fundamentally dynamic, yet current 3D datasets and evaluation benchmarks tend to concentrate on either dynamic scenarios or dynamic situations in isolation, resulting in incomplete comprehension. To overcome these constraints, we introduce Situat3DChange, an extensive dataset supporting three situation-aware change

Francesco Milano, Jen Jen Chung, Lionel Ott, Roland Siegwart

Surface normal integration is a fundamental problem in computer vision, dealing with the objective of reconstructing a surface from its corresponding normal map. Existing approaches require an iterative global optimization to jointly estimate the depth of each pixel, which scales poorly to larger normal maps. In this paper, we address this problem by recasti

Alain Riou, Joan Serrà, Yuki Mitsufuji

Sampling, the technique of reusing pieces of existing audio tracks to create new music content, is a very common practice in modern music production. In this paper, we tackle the challenging task of automatic sample identification, that is, detecting such sampled content and retrieving the material from which it originates. To do so, we adopt a self-supervis

Juan Eloy Ruiz-Castro, Hugo Alaín Zapata-Ceballos

In this work, a single-unit multi-state system is considered. The system is subject to internal failures, as well as external shocks with multiple consequences. It also incorporates a preventive maintenance strategy and a Bernoulli vacation policy for the repairperson. It is algorithmically modeled in both continuous and discrete time using Marked Markovian

Aleksei Rozanov, Samikshya Subedi, Vasudha Sharma, Bryan C. Runck

Evapotranspiration (ET) plays a critical role in the land-atmosphere interactions, yet its accurate quantification across various spatiotemporal scales remains a challenge. In situ measurement approaches, like eddy covariance (EC) or weather station-based ET estimation, allow for measuring ET at a single location. Agricultural uses of ET require estimates fo

Ana Marija Kožuljević, Tomislav Bokulić, Darko Grošev, Siddharth Parashari

Positron Emission Tomography (PET) is a medical imaging modality that utilizes positron-emitting isotopes, such as Ga-68 and F-18, for many diagnostic purposes. The positron annihilates with an electron from the surrounding area, creating two photons of 511 keV energy and opposite momenta, entangled in their orthogonal polarizations. When each photon undergo

Alexis Ross, Jacob Andreas

Research on reasoning in language models (LMs) predominantly focuses on improving the correctness of their outputs. But some important applications require modeling reasoning patterns that are incorrect. For example, automated systems that can reason about and simulate student errors are useful for providing real-time feedback in the classroom or offline pra

Emran Yasser Moustafa, Ivana Dusparic

Autonomous vehicles have shown promising potential to be a groundbreaking technology for improving the safety of road users. For these vehicles, as well as many other safety-critical robotic technologies, to be deployed in real-world applications, we require algorithms that can generalize well to unseen scenarios and data. Model-based reinforcement learning

Tileuzhan Mukhamet, Katharina Kormann

We derive mixed finite element discretizations of a cold relativistics fluid model from approximations of the Poisson bracket that preserve mass, energy and the divergence constraints. For time-discretization we derive an implicit energy-conserving average-vector field method or apply an explicit strong-stability preserving Runge-Kutta scheme. We also consid

Yuhang Li, Chenchen Zhang, Ruilin Lv, Ao Liu

While Large Language Models (LLMs) excel at algorithmic code generation, they struggle with front-end development, where correctness is judged on rendered pixels and interaction. We present ReLook, an agentic, vision-grounded reinforcement learning framework that empowers an agent to close a robust generate--diagnose--refine loop by invoking a multimodal LLM

Marius Roland, Nagisa Sugishita, Alexandre Forel, Youssouf Emine

This paper investigates the a-posteriori analysis of Branch-and-Bound~(BB) trees to extract structural information about the feasible region of mixed-binary linear programs. We introduce three novel outer approximations of the feasible region, systematically constructed from a BB tree. These are: a tight formulation based on disjunctive programming, a branch

Zhiwei Jin, Xiaohui Song, Nan Wang, Yafei Liu

In recent years, while cloud-based MLLMs such as QwenVL, InternVL, GPT-4o, Gemini, and Claude Sonnet have demonstrated outstanding performance with enormous model sizes reaching hundreds of billions of parameters, they significantly surpass the limitations in memory, power consumption, and computing capacity of edge devices such as mobile phones. This paper

Nikolaos Tsilivis, Eran Malach, Karen Ullrich, Julia Kempe

Recent advances in reasoning domains with neural networks have primarily been enabled by a training recipe that optimizes Large Language Models, previously trained to predict the next-token in a sequence, with reinforcement learning algorithms. We introduce a framework to study the success of this paradigm, and we theoretically expose the optimization mechan

Matti Lassas, Tony Liimatainen, Valter Pohjola, Teemu Tyni

We study the inverse source problem for the semilinear wave equation \[ (\Box_g + q_1)u + q_2 u^2 = F, \] on a globally hyperbolic Lorentzian manifold. We demonstrate that the coefficients $q_1$ and $q_2$, as well as the source term $F$, can be recovered up to a natural gauge symmetry inherent in the problem from local measurements. Furthermore, if $q_1$ is

A. Giusti, I. Colombaro, A. Mentrelli

We discuss the propagation of harmonic and transient waves for systems governed by a wave equation with memory whose integral kernel involves ratios of modified Bessel functions of the first kind in the Laplace domain. In particular, the investigation of transient waves is carried out by means of a fully numerical approach based on the Talbot method for the

Christopher J. Fewster, Alexander Strohmaier

The Wightman two-point function of any Hadamard state of a linear quantum field theory determines a corresponding Feynman propagator. Conversely, however, a Feynman propagator determines a state only if certain positivity conditions are fulfilled. Choosing a Feynman propagator to satisfy the correct positivity conditions involves a slightly subtle point that

Murad Dawood, Usama Ahmed Siddiquie, Shahram Khorshidi, Maren Bennewitz

Safe reinforcement learning (RL) seeks to mitigate unsafe behaviors that arise from exploration during training by reducing constraint violations while maintaining task performance. Existing approaches typically rely on a single policy to jointly optimize reward and safety, which can cause instability due to conflicting objectives, or they use external safet

A. S. Bonomo, L. Naponiello, A. Sozzetti, S. Benatti

Sub-Neptunes with planetary radii of $R_{p} \simeq 2-4 R_{\oplus}$ are the most common planets around solar-type stars in short-period ($P<100$ d) orbits. It is still unclear, however, what their most likely composition is, that is whether they are predominantly gas dwarfs or water worlds. The sub-Neptunes orbiting bright host stars are very valuable because

Georgios Nousios, Thomas Christopoulos, Emmanouil E. Kriezis, Odysseas Tsilipakos

The novel combination of a strongly-resonant optical metasurface with the MoS$_2$/WSe$_2$ hetero-bilayer is proposed for efficient free-space lasing enabled by the enhanced coupling between the optical and matter (exciton) states. The metasurface comprises silicon-rich nitride meta-atoms periodically arrayed in a subdiffractive lattice and overlaid with MoS$