December 2025 arXiv papers — page 76

Tomáš Souček, Pierre Fernandez, Hady Elsahar, Sylvestre-Alvise Rebuffi

Invisible watermarking is essential for tracing the provenance of digital content. However, training state-of-the-art models remains notoriously difficult, with current approaches often struggling to balance robustness against true imperceptibility. This work introduces Pixel Seal, which sets a new state-of-the-art for image and video watermarking. We first

Otman A. Basir

Artificial intelligence systems are increasingly deployed in domains that shape human behaviour, institutional decision-making, and societal outcomes. Existing responsible AI and governance efforts provide important normative principles but often lack enforceable engineering mechanisms that operate throughout the system lifecycle. This paper introduces the S

Shayan Hundrieser, Philipp Tuchel, Insung Kong, Johannes Schmidt-Hieber

Inspired by biology, spiking neural networks (SNNs) process information via discrete spikes over time, offering an energy-efficient alternative to the classical computing paradigm and classical artificial neural networks (ANNs). In this work, we analyze the representational power of SNNs by viewing them as sequence-to-sequence processors of spikes, i.e., sys

Hesham G. Moussa, Aroosa Hameed, Arashmid Akhavain

To cope with real-world dynamics, an intelligent system needs to incrementally acquire, update, and exploit knowledge throughout its lifetime. This ability, known as Continual learning, provides a foundation for AI systems to develop themselves adaptively. Catastrophic forgetting is a major challenge to the progress of Continual Learning approaches, where le

Vakhtang Jandieri, Ramaz Khomeriki, Daniel Erni, Nicolas Tsagareli

Topological textures in magnetically ordered materials are important case studies for fundamental research with promising applications in data science. They can also serve as photonic elements to mold electromagnetic fields endowing them with features inherent to the spin order, as demonstrated analytically and numerically in this work. A self-consistent the

Adriaan J. Duivenvoorden, Kristen Surrao, Adrian E. Bayer, Alexandre E. Adler

We explore a novel analysis framework for parameter inference with large-scale CMB polarization data. Our method uses simulation-based inference combined with the needlet internal linear combination (NILC) algorithm and cross-correlation-based statistics to compress the data into a vector that is robust to model misspecification and small enough to be amenab

Jhinkyu Choi, Mohan B. Neupane, L. H. Vilela-Leão, Bishnu P. Belbase

The thermal Hall effect has emerged as a powerful probe of exotic excitations in correlated quantum materials, providing access to charge-neutral heat carriers that remain invisible to electrical transport. To directly examine how heat and charge respond in relation within a kagome metal, we investigate the ferrimagnetic rare-earth 1-6-6 compound TbCr6Ge6 us

Bineet Dash, Xinyan Xiang, Dingkun Feng, Eric Paradis

We present a non-invasive spectroscopic technique to measure electric fields in plasma, leveraging large polarizabilities and Stark shifts of Rydberg atoms. Rydberg Stark shifts are measured with high precision using narrow-linewidth lasers via Electromagnetically Induced Transparency (EIT) of rubidium vapor seeded into a continuous, inductively coupled radi

Jiabin Xue

Edge machine learning (Edge ML) enables training ML models using the vast data distributed across network edges. However, many existing approaches assume static models trained centrally and then deployed, making them ineffective against unseen data. To address this, Online Edge ML allows models to be trained directly on edge devices and updated continuously

Songhao Shen, Yufeng Zhou, Qin Lei, Zhibin Wu

The orienteering problem (OP) is a combinatorial optimization problem that seeks a path visiting a subset of locations to maximize collected rewards under a limited resource budget. This article presents a systematic PRISMA-based review of OP research published between 2017 and 2025, with a focus on models and methods that have shaped subsequent developments

Stefan Antusch, Salvador Centelles Chuliá, Miguel Levy

Gravity is generally expected to violate global symmetries, including lepton number. However, neutrino masses from the Planck-suppressed Weinberg operator are typically too small to account for oscillation data. We propose a new model-building approach to low-scale neutrino mass generation, in which an intermediate spontaneous symmetry-breaking scale generat

Emirhan Zor, Bora Bozkurt, Ferkan Yilmaz

Non-Orthogonal Multiple Access (NOMA) technology has emerged as a promising technology to enable massive connectivity and enhanced spectral efficiency in next-generation wireless networks. In this study, we propose a novel two-user downlink power-domain NOMA framework that integrates a Cyclic Redundancy Check (CRC)-aided Guessing Random Additive Noise Decodi

Han-Ze Li, Yi-Rui Zhang, Yu-Jun Zhao, Xuyang Huang

Disorder-free quantum many-body localization can strongly suppress transport while still enabling the dynamical buildup of computationally costly non-Clifford resources. In a tilted transverse-field Ising chain realizing disorder-free Stark many-body localization, we use the stabilizer R\'enyi entropy to quantify quantum magic (nonstabilizerness) and find th

Julian Talbot

We formulate a statistical-mechanical description of a recently introduced random planting model in which plants are represented by growing hard disks. Seedlings of negligible size are introduced at random positions in a field, grow at a prescribed rate, and are harvested upon reaching a fixed maturity diameter. Planting attempts that would lead to an overla

Chao Cheng, Georgia Papadogeorgou, Fan Li

Treatment noncompliance is pervasive in infectious disease cluster-randomized trials. Although all individuals within a cluster are assigned the same treatment condition, the treatment uptake status may vary across individuals due to noncompliance. We propose a semiparametric framework to evaluate the individual compliance effect and network assignment effec

Khurram Khalil, Khaza Anuarul Hoque

Large Language Models (LLMs) deliver exceptional performance across natural language tasks but demand substantial computational resources, limiting their deployment on resource-constrained edge devices. Existing compression techniques, such as quantization and pruning, often degrade critical linguistic properties and lack formal guarantees for preserving mod

Jalani Williams, Weina Wang, Mor Harchol-Balter

In many systems, servers do not turn on instantly; instead, a setup time must pass before a server can begin work. These "setup times" can wreak havoc on a system's queueing; this is especially true in modern systems, where servers are regularly turned on and off as a way to reduce operating costs (energy, labor, CO2, etc.). To design modern systems which ar

Amita Kamath, Kai-Wei Chang, Ranjay Krishna, Luke Zettlemoyer

Automating Text-to-Image (T2I) model evaluation is challenging; a judge model must be used to score correctness, and test prompts must be selected to be challenging for current T2I models but not the judge. We argue that satisfying these constraints can lead to benchmark drift over time, where the static benchmark judges fail to keep up with newer model capa

Kevin N. Ortiz Ceballos, Yvette Cendes, Edo Berger

We present the first targeted centimeter-band radio observations of two recently-discovered exoplanet systems that are prime candidates for magnetic star-planet interaction (SPI): TOI-540 and SPECULOOS-3. The targets were selected due to the small orbital separation of their known planets, as well as for indications of stellar magnetic activity, given that f

Ripan Kumar Kundu, Istiak Ahmed, Khaza Anuarul Hoque

The convergence of artificial AI and XR technologies (AI XR) promises innovative applications across many domains. However, the sensitive nature of data (e.g., eye-tracking) used in these systems raises significant privacy concerns, as adversaries can exploit these data and models to infer and leak personal information through membership inference attacks (M

Can Urgun, Mark Whitmeyer

We study continuous-time persuasion where a sender controls both how informative a signal is over time and when to stop providing information to a receiver. Given an exogenous signal process, the sender can both garble the evolving signal path and delay the receiver's decision at a convex, increasing cost of time. We show that, although both instruments are

Yifei Tong

This study examines how time delays between criminal offenses and arrests are associated with sentencing outcomes in Cook County, Illinois, during the COVID-19 era. Using administrative court records from 2020 to 2024, the analysis focuses on cases in which arrests did not occur immediately, allowing for systematic variation in procedural delay. The study as

Yulun Jiang, Liangze Jiang, Damien Teney, Michael Moor

Reinforcement learning (RL) has enabled the training of large language model (LLM) agents to interact with the environment and to solve multi-turn long-horizon tasks. However, the RL-trained agents often struggle in tasks that require active exploration and fail to efficiently adapt from trial-and-error experiences. In this paper, we present LaMer, a general

Benjamin Schwager, Theresa Appel, Jamal Berakdar

The motion of a quantum particle constrained to a two-dimensional non-compact Riemannian manifold with non-trivial metric can be described by a flat-space Schroedinger-type equation at the cost of introducing local mass and metric and geometry-induced effective potential with no classical counterpart. For a metric tensor periodically modulated along one dime

J. J. M. in 't Zand, C. Guidorzi, J. Heise, L. Amati

We performed a search for fast X-ray transients (FXTs), with durations longer than one second and less than one day, through data of the Wide Field Camera (WFC) instrument onboard the BeppoSAX X-ray observatory collected between June 1996 and April 2002. (..) We focused our search on gamma-ray bursts (GRBs), X-ray flashes (XRFs), X-ray flares from high-mass

Nianyi Chen, Yihao Zhou, Ekaterine Dadiani, Tiziana Di Matteo

Dual active galactic nuclei (DAGN) mark an observable stage of massive black hole (MBH) pairing in galaxy mergers and are precursors to the MBH binaries that generate low-frequency gravitational waves. Using the large-volume ASTRID cosmological simulation, we construct DAGN catalogs matched to current (COSMOS-Web, DESI) and forthcoming (AXIS, Roman) searches

Harsh Vardhan Bansal

Transformer-based language models have achieved remarkable performance across a wide range of tasks, yet their high inference latency poses a significant challenge for real-timeand large-scale deployment. While existing caching mechanisms,such as token-level key-value caches, offer speedups in autore-gressive decoding, they are limited in scope and applicabi

Yuxin Ray Song, Jinzhou Li, Rao Fu, Devin Murphy

The human hand is our primary interface to the physical world, yet egocentric perception rarely knows when, where, or how forcefully it makes contact. Robust wearable tactile sensors are scarce, and no existing in-the-wild datasets align first-person video with full-hand touch. To bridge the gap between visual perception and physical interaction, we present

Emmanuel D. Muñiz-De-León, Jorge A. Rosales-de-Golferichs, Ana S. Muñoz-Rodríguez, Alejandro I. Trejo-Castro

Automatic radiology report generation is a promising application of multimodal deep learning, aiming to reduce reporting workload and improve consistency. However, current state-of-the-art (SOTA) systems - such as Multimodal AI for Radiology Applications (MAIRA-2) and Medical Pathways Language Model-Multimodal (MedPaLM-M) - depend on large-scale multimodal t

Vladimir Vasilyev, Denis Tokarev

A model elliptic pseudo-differential equation in $4$-faced cone is studied in Sobolev--Slobodetskii space. The Bochner kernel for such a cone is evaluated and explicit formula for unique solution to the considered equation is presented under certain restrictions on the symbol. Boundary value problem with additional integral condition is considered and unique

Barnaby D. A. Levin, Kalani Moore, Nicolò M. Della Ventura, McLean P. Echlin

The use of highly sensitive pixelated direct detectors has dramatically improved the performance of high energy instrumentation such as transmission electron microscopy. Here, we describe a recently developed monolithic active pixel sensor designed for low energy scanning electron microscopy applications. This detector enables electron backscatter diffractio

Mateo Dutra, Marcos Abreu, Martín Monteiro, Silvia Sguilla

Kinematics is a core topic in early physics courses, yet students often struggle to interpret motion and its graphical representations. To tackle these difficulties, we developed MissionMotion, a physical-computational videogame where students reproduce target motion graphs using real-time data from their own movements or from sensors connected through micro

Arturo de Giorgi, Joerg Jaeckel, Sebastian Monath, Volodymyr Takhistov

Axions and axion-like particles generically appear in extensions of the Standard Model. While many searches assume only a single axion species, there may exist a whole spectrum of multiple such fields. We develop general formulas for axion-photon oscillations in the presence of multiple axions and analyze the implications for experimental searches, including

Debarghya Chakraborty, Dario Rosa

We develop a novel framework to build quantum many-body scar states in bipartite systems characterized by perfect correlation between the Hamiltonians governing the two sides. By means of a Krylov construction, we build an interaction term which supports a tower of equally-spaced energy eigenstates. This gives rise to finite-time revivals whenever the system

Daniel Stremmer

We present the program package ggxy, which in its first version can be used to calculate partonic and hadronic cross sections to Higgs boson pair production at NLO QCD and it offers a direct interface to POWHEG-BOX. The 2-loop virtual amplitudes are implemented using analytical approximations in different kinematic regions, while all other parts of the calcu

N. Hernandez-Cepeda, Sergio E. Ulloa

Quantum dot (QD) platforms have enabled the direct observation of Nagaoka ferromagnetism (NFM) in small arrays and non-infinite interaction strength. However, optimizing the cluster connectivity characteristics that yield a ground state with maximal spin and their robustness against magnetic fields remains unexplored. Employing exact diagonalization of the H

Xiaokang Liu, Rui Duan, Raymond J. Carroll, Yang Ning

Mixture models postulate the overall population as a mixture of finite subpopulations with unobserved membership. Fitting mixture models usually requires large sample sizes and combining data from multiple sites can be beneficial. However, sharing individual participant data across sites is often less feasible due to various types of practical constraints, s

Aditya Yadavalli, Tiago Pimentel, Tamar I Regev, Ethan Wilcox

Prosody -- the melody of speech -- conveys critical information often not captured by the words or text of a message. In this paper, we propose an information-theoretic approach to quantify how much information is expressed by prosody alone and not by text, and crucially, what that information is about. Our approach applies large speech and language models t

Nathaniel Furman, Albert Herrero-Parareda, Anthony Rapp, Ilya Vitebskiy

The dispersion engineering of periodic silicon photonic waveguides presents opportunities for significant group delay enhancement compared to uniform waveguides of comparable length. We describe the spectral response characteristics for measured devices and compare their properties to modeled data. These waveguides support the frozen mode regime (FMR) around

Francesca Pelusi, Andrea Scagliarini, Mauro Sbragaglia, Massimo Bernaschi

Thermally driven emulsions arise in a broad range of natural and industrial contexts, yet their fundamental physical understanding remains only partially established. Emulsions exhibit a complex, concentration-dependent rheology, ranging from Newtonian (dilute emulsions) to yield-stress (concentrated emulsions). In buoyancy-driven flows, the complex structur

Wen Li, Vahid Hassanzade, Maxim Dzero, Vladyslav Kozii

We study spin-triplet superconductivity with both unitary and nonunitary pairing in the presence of an external Zeeman magnetic field. Within a mean-field framework, we exactly diagonalize the Bogoliubov-de Gennes Hamiltonian and derive general expressions for the quasiparticle spectrum, superconducting gap, critical temperature, and spin magnetization, vali

Juan Sosa, Brayan Riveros, Emma J. Camargo-Díaz

The legislative output of Colombia's House of Representatives between 2014 and 2025 is analyzed using 4,083 bills. Bipartite networks are constructed between parties and bills, and between representatives and bills, along with their projections, to characterize co-sponsorship patterns, centrality, and influence, and to assess whether political polarization i

Arslan Amin, Rafia Mumtaz, Muhammad Jawad Bashir, Syed Mohammad Hassan Zaidi

In the evolving landscape of traffic management and vehicle surveillance, efficient license plate detection and recognition are indispensable. Historically, many methodologies have tackled this challenge, but consistent real-time accuracy, especially in diverse environments, remains elusive. This study examines the performance of YOLOv8 variants on License P

Amit Jain, Richard Linares

Neural network controllers increasingly demand millions of parameters, and language model approaches push into the billions. For embedded aerospace systems with strict power and latency constraints, this scaling is prohibitive. We present Tiny Recursive Control (TRC), a neural architecture based on a counterintuitive principle: capacity can emerge from itera

Mike Shubrook, Moritz Cygorek, Erik Gauger, Jake Iles-Smith

Accurately quantifying the thermodynamic work costs of quantum operations is essential for the continued development and optimisation of emerging quantum technologies. This present a significant challenge in regimes of rapid control within complex, non-equilibrium environments - conditions under which many contemporary quantum devices operate and conventiona

Qian Wang, Zahra Yousefijamarani, Morgan Lindsay Heisler, Rongzhi Gu

Modern LLM applications such as deep-research assistants, coding agents, and Retrieval-Augmented Generation (RAG) systems, repeatedly process long prompt histories containing shared document or code chunks, creating significant pressure on the Key Value (KV) cache, which must operate within limited memory while sustaining high throughput and low latency. Pre

Nathan Conger, Nathan Scollar, Kemal Davaslioglu, Yalin E. Sagduyu

We present a retrieval-augmented question answering framework for 5G/6G networks, where the Open Radio Access Network (O-RAN) has become central to disaggregated, virtualized, and AI-driven wireless systems. While O-RAN enables multi-vendor interoperability and cloud-native deployments, its fast-changing specifications and interfaces pose major challenges fo

Kazuto Nakamura, Masaki Yamada

We investigate the velocity-dependent one-scale (VOS) model to the case of one cosmic F-string and two D-strings as color flux tubes in pure Spin($4N$) gauge theory. We analytically calculate the scaling string density as a function of the reconnection probabilities, and confirm our results with numerical calculations. We also determine the timescale at whic

H. Movahedi-Lankarani

It is shown that if a compact metric space $(X, d)$ is bi-H\"older equivalent to an ultrametric space, then the logarithmic ratio $R(X,d)$ is finite. Conversely, if the logarithmic ratio $R(X,d)$ is finite and ${\A}^*_p (X) \ne \emptyset$ for some $p \in (1, \infty )$, then $(X, d)$ is bi-H\"older equivalent to an ultrametric space. It is also shown that for

Marius Dähling, Sebastian Krebs, J. Marius Zöllner

In current research, Bird's-Eye-View (BEV)-based transformers are increasingly utilized for multi-camera 3D object detection. Traditional models often employ random queries as anchors, optimizing them successively. Recent advancements complement or replace these random queries with detections from auxiliary networks. We propose a more intuitive and efficient

Alessandra Parziale, Gianmario Voria, Valeria Pontillo, Gemma Catolino

Nowadays, Large Language Models (LLMs) are foundational components of modern software systems. As their influence grows, concerns about fairness have become increasingly pressing. Prior work has proposed metamorphic testing to detect fairness issues, applying input transformations to uncover inconsistencies in model behavior. This paper introduces an alterna

Antonio Racioppi

We propose a new mechanism for inflationary model building in the framework of metric-affine gravity. Such a mechanism involves an inflaton non-minimally coupled with the Holst invariant. If the non-minimal coupling function has a zero point and it is very steep at that same point, the corresponding inflaton kinetic function will feature a quasi-pole behavio

William English, Dominic Simon, Sumit Kumar Jha, Rickard Ewetz

Translating natural language (NL) into a formal language such as temporal logic (TL) is integral for human communication with robots and autonomous systems. State-of-the-art approaches decompose the task into a lifting of atomic propositions (APs) phase and a translation phase. However, existing methods struggle with accurate lifting, the existence of co-ref

Bahman Abolhassani, Tugba Erpek, Kemal Davaslioglu, Yalin E. Sagduyu

Reactive jammers pose a severe security threat to robotic-swarm networks by selectively disrupting inter-agent communications and undermining formation integrity and mission success. Conventional countermeasures such as fixed power control or static channel hopping are largely ineffective against such adaptive adversaries. This paper presents a multi-agent r

Christoph Schönle, Davide Carbone, Marylou Gabrié, Tony Lelièvre

Monte Carlo simulations are widely used to simulate complex molecular systems, but standard approaches suffer from metastability. Lately, the use of non-local proposal updates in a collective-variable (CV) space has been proposed in several works. Here, we generalize these approaches and explicitly spell out an algorithm for non-linear CVs and underdamped La

Jingjing Qian, Boyao Han, Chen Shi, Lei Xiao

Vision-Language-Action (VLA) models achieve strong generalization in robotic manipulation but remain largely reactive and 2D-centric, making them unreliable in tasks that require precise 3D reasoning. We propose GeoPredict, a geometry-aware VLA framework that augments a continuous-action policy with predictive kinematic and geometric priors. GeoPredict intro

Davide Racco, Alfredo Stanzione

An interesting feature of a cosmological phase transition can be a stage of exponential expansion (supercooling). The modified expansion history and the entropy injection at reheating, can affect the final energy fraction of dark matter. In this paper, we revisit the calculation of the freeze-out and freeze-in dynamics, showing additional effects on top of t

Frederik Ritter, Andrej Rode, Laurent Schmalen

A non-uniform channel input distribution is key for achieving the capacity of arbitrary channels. However, message bits are generally assumed to follow a uniform distribution which must first be transformed to a non-uniform distribution by using a distribution matching algorithm. One such algorithm is enumerative sphere shaping (ESS). Compared to algorithms

Simone Ingrid Monteiro Gama, Rosiane de Freitas Rodrigues

This work investigates structural and computational aspects of list-based graph coloring under interval constraints. Building on the framework of analogous and p-analogous problems, we show that classical List Coloring, $\mu$-coloring, and $(\gamma,\mu)$-coloring share strong complexity-preserving correspondences on graph classes closed under pendant-vertex

Nicolás Blampied, Alessia Cafferata, Marwil J. Davila-Fernandez

Can constantly comparing ourselves to others lead to overconsumption, ultimately increasing the ecological footprint? How do social comparisons shape green preferences over time? To answer these questions, we develop an environmental Overlapping Generations (OLG) model that explicitly accounts for Veblen effects and allows green preferences to be updated asy

Wooil Yang, Iurii Timrov, Francesco Aquilante, Young-Woo Son

Density-functional theory with on-site $U$ and inter-site $V$ Hubbard corrections (DFT+$U$+$V$) is a powerful and accurate method for predicting various properties of transition-metal compounds. However, its accuracy depends critically on the values of these Hubbard parameters. Although they can be determined empirically, first-principles methods provide a m

Primož Kocbek, Azra Frkatović-Hodžić, Dora Lalić, Vivian Hui

Multi-modal retrieval-augmented generation (MM-RAG) promises grounded biomedical QA, but it is unclear when to (i) convert figures/tables into text versus (ii) use optical character recognition (OCR)-free visual retrieval that returns page images and leaves interpretation to the generator. We study this trade-off in glycobiology, a visually dense domain. We

Patrice Bouchet, René Gastaud, Alain Coulais, Richard G. Arendt

An excess emission has been observed by Spitzer in the [3, 5] micron range of the SNR 1987A spectrum. It is generally argued that this excess could be due to the presence of warm amorphous carbon dust in the equatorial ring (ER) around the supernova, but the proposed models all have problems. This prompted us to present an alternative view on the interpretat

Nicholas Laws, Elaine Petro

Electrospray thrusters promise compact, high specific impulse propulsion for small spacecraft, yet ground characterization remains confounded by secondary species emission and incomplete diagnostics of neutral products. To address these limitations, we perform energy-resolved mixed quantum/classical (QM/MM) ab initio molecular dynamics (MD) of neutral 1-ethy

Devin Hymers, Sebastian Schroeder, Olga Bertini, Johann Heuser

Objective Interaction vertex imaging (IVI) is used for range monitoring in carbon ion radiotherapy, detecting depth differences between Bragg peak positions. Online range monitoring, which provides feedback during beam delivery, is particularly desirable, creating an opportunity to detect range errors before the treatment fraction is completed. Incorporating

Alexey Pokrovskiy, Leo Versteegen, Ella Williams

A variant of the Erd\H{o}s-S\'os conjecture, posed by Havet, Reed, Stein and Wood, states that every graph with minimum degree at least $\lfloor 2k/3 \rfloor$ and maximum degree at least $k$ contains a copy of every tree with $k$ edges. Both degree bounds are best possible. We confirm this conjecture for large trees with bounded maximum degree, by proving th

Devin Hymers, Sebastian Schroeder, Olga Bertini, Stephan Brons

Interaction Vertex Imaging (IVI) is used for range monitoring (RM) in carbon ion radiotherapy. The purpose of RM is to measure the Bragg peak (BP) position for each contributing beam, and detect any changes. Currently, there is no consensus on a clinical RM method, the use of which would improve the safety and consistency of treatment. The prototype filtered

Lorenzo Gavassino, Alexander Soloviev

Landau's two-fluid model of superfluidity ceases to apply in regions where the condensate amplitude exhibits rapid spatial variation, such as vortex cores or in the vicinity of container walls. A recently proposed relativistic Gross-Pitaevskii-type framework treats the condensate as an independent scalar degree of freedom, enabling a controlled analysis of s

M. Wissmann, L. Fanfarillo, X. -C. Hong, S. Caprara

FeSe stands out among iron-based superconductors due to its extended nematic phase without the onset of long-range magnetic order. While strain-dependent electrical resistivity has been extensively explored to probe nematicity, its influence on magneto-transport properties remains less understood. In this work, we present measurements of the magneto-elasto-r

Shubham Mishra, Samyek Jain, Gorang Mehrishi, Shiv Tiwari

Retrieval-Augmented Generation (RAG) grounds large language models (LLMs) in external evidence, but fails when retrieved sources conflict or contain outdated or subjective information. Prior work address these issues independently but lack unified reasoning supervision. We propose a reasoning-trace-augmented RAG framework that adds structured, interpretable

A. Arokiaraj, M. B. Latif, R. Raabe, D. Thisse

Active targets such as ACTAR TPC are well suited for studying giant resonances in unstable nuclei via inelastic scattering in inverse kinematics. A key challenge in such measurements is the detection of low-energy ejectiles emitted at small angles relative to the beam direction. Accurate reconstruction of these tracks is essential for disentangling different

Xiaopeng Lin, Shijie Lian, Bin Yu, Ruoqi Yang

Robotic generalization relies on physical intelligence: the ability to reason about state changes, contact-rich interactions, and long-horizon planning under egocentric perception and action. Vision Language Models (VLMs) are essential to Vision-Language-Action (VLA) systems, but the reliance on third-person training data creates a viewpoint gap for humanoid

Endar Suprih Wihidayat, Sieteng Soh, Kwan-Wu Chin, Duc-son Pham

In this paper, the Multi-stage Edge Server Upgrade (M-ESU) is proposed as a new network planning problem, involving the upgrading of an existing multi-access edge computing (MEC) system through multiple stages (e.g., over several years). More precisely, the problem considers two key decisions: (i) whether to deploy additional edge servers or upgrade those al

Shuting Zhao, Zeyu Xiao, Xinrong Chen

Full-body motion tracking plays an essential role in AR/VR applications, bridging physical and virtual interactions. However, it is challenging to reconstruct realistic and diverse full-body poses based on sparse signals obtained by head-mounted displays, which are the main devices in AR/VR scenarios. Existing methods for pose reconstruction often incur high

Zhexiang Li

Inductive cold-start recommendation remains the "Achilles' Heel" of industrial academic platforms, where thousands of new scholars join daily without historical interaction records. While recent Generative Graph Models (e.g., HiGPT, OFA) demonstrate promising semantic capabilities, their prohibitive inference latency (often exceeding 13 minutes per 1,000 req

Aaron Imani, Mohammad Moshirpour, Iftekhar Ahmed

While comments are non-functional elements of source code, Large Language Models (LLM) frequently rely on them to perform Software Engineering (SE) tasks. Yet, where in the model this reliance resides, and how it affects performance, remains poorly understood. We present the first concept-level interpretability study of LLMs in SE, analyzing three tasks - co

Devin Hymers, Sebastian Schroeder, Olga Bertini, Johann Heuser

Designed to provide quality assurance for ion-beam radiotherapy, the prototype fIVI (filtered Interaction Vertex Imaging) Range Monitoring System is a two-layer tracker which employs double-sided strip-segmented silicon detectors. To meet the high demands of a clinical environment, a large sensitive area is required, along with a fast and compact readout. As

Tolga Altinoluk, Guillaume Beuf, Jules Favrel, Michael Fucilla

We compute next-to-leading order (NLO) corrections to next-to-eikonal (NEik) quark background contributions to DIS structure functions. Among NEik corrections, $t$-channel quark exchanges provide the lowest order contributions in $\alpha_s$, and can be represented as insertions of the quark background field of the target. At NLO, we compute NEik corrections

Nathan Albin, Vincenzo Nesi, Mariapia Palombaro

We prove the stability under lamination of a set of real, symmetric 3$\times$3 matrices that can be viewed as a subset of the effective conductivities of a polycrystal. Constructed in a companion paper, such set in combination with several previous constructions provides the best inner bound known so far on the $G$-closure of a three dimensional polycrystal.

Chenyu Zhu, Zeyang Li, Ziyi Xie, Jie Zhang

Specific emitter identification (SEI) utilizes passive hardware characteristics to authenticate transmitters, providing a robust physical-layer security solution. However, most deep-learning-based methods rely on extensive data or require prior information, which poses challenges in real-world scenarios with limited labeled data. We propose an integrated com

MA Ortiz-Ferreyro, J. Sumaya-Martinez, A. Esquivel-Navarrete

We analyze enhanced optical transmission through subwavelength apertures using a modal formulation for the two fundamental polarizations, transverse electric (TE) and transverse magnetic (TM). Within this framework, the fields inside the aperture are described in terms of guided modes whose excitation and interference govern the transmission process. By exam

Simone Teglia, Claudia Melis Tonti, Francesco Pro, Leonardo Russo

Datasets are essential to train and evaluate computer vision models used for traffic analysis and to enhance road safety. Existing real datasets fit real-world scenarios, capturing authentic road object behaviors, however, they typically lack precise ground-truth annotations. In contrast, synthetic datasets play a crucial role, allowing for the annotation of

Emanuele Bagnaschi, Manimala Chakraborti, Sven Heinemeyer, Ipsita Saha

The search for supersymmetric models remains one of the main items on the BSM search program at the LHC, with EW SUSY partners still allowed with masses as low as a few hundred GeV. Over the last years, searches for the "golden channel", $pp \to \tilde{\chi}^0_2 \tilde{\chi}^{\pm}_1 \to \tilde{\chi}^0_1 Z^{(*)} \tilde{\chi}^0_1 W^{\pm (*)}$ show consistent e

Olga Varghese

By definition, a group $G$ is quasi-perfect, if $G$ is perfect or the commutator subgroup of $G$ is perfect. In this note we give a description of quasi-perfect Dyer groups by properties of the corresponding Dyer graphs.

Pietro Ghedini, Rasmi Hajjar, Olga Mena

Recent cosmological measurements are hinting that dark energy may evolve, with its equation of state, $w_\mathrm{DE}$, even showing oscillatory patterns. In this work, we employ a model-independent approach to jointly reconstruct $w_\mathrm{DE}$ and the sum of neutrino masses, $\sum m_\nu$, adopting the PCHIP method with seven fixed nodes in which we allow t

Haotian Ye, Qiyuan He, Jiaqi Han, Puheng Li

Accurate and efficient discrete video tokenization is essential for long video sequences processing. Yet, the inherent complexity and variable information density of videos present a significant bottleneck for current tokenizers, which rigidly compress all content at a fixed rate, leading to redundancy or information loss. Drawing inspiration from Shannon's

Nils Küchenmeister, Alex Ivliev, Markus Krötzsch

We present a new use of Answer Set Programming (ASP) to discover the molecular structure of chemical samples based on the relative abundance of elements and structural fragments, as measured in mass spectrometry. To constrain the exponential search space for this combinatorial problem, we develop canonical representations of molecular structures and an ASP i

Qinwen Tang, Ran Yan, Nan Zhou, Minda Ma

Climate change and rising thermal comfort demand make residential heating and cooling central to building-sector decarbonization. This study presents the first bottom-up modeling framework to estimate residential heating and cooling loads across 30 Chinese provinces. The model, developed using EnergyPlus simulations of representative building prototypes, cap

Theshani Nuradha, Ian George, Christoph Hirche

Data-processing is a desired property of classical and quantum divergences and information measures. In information theory, the contraction coefficient measures how much the distinguishability of quantum states decreases when they are transmitted through a quantum channel, establishing linear strong data-processing inequalities (SDPI). However, these linear

Zhenhuan Liu, Tobias Haug, Qi Ye, Zi-Wen Liu

We introduce a mixed-state magic criterion, the Triangle Criterion, which plays a role for magic analogous to the Positive Partial Transposition (PPT) Criterion for entanglement: it combines strong detection capability, a clear geometric interpretation, and an operational link to magic distillation. Using this criterion, we uncover several new features of mu

Kling Team, Jialu Chen, Yuanzheng Ci, Xiangyu Du

We present Kling-Omni, a generalist generative framework designed to synthesize high-fidelity videos directly from multimodal visual language inputs. Adopting an end-to-end perspective, Kling-Omni bridges the functional separation among diverse video generation, editing, and intelligent reasoning tasks, integrating them into a holistic system. Unlike disjoin

Nicolás Medina Sánchez, Borivoje Dakić

One of the traditional ways of introducing bosons and fermions is through creation-annihilation algebras. Historically, these have been associated with emission and absorption processes at the quantum level and are characteristic of the language of second quantization. In this work, we formulate the transition from first to second quantization by taking quot

Marcel Mittenbuehler, Lukas Sturm, Malte Schlosser, Gerhard Birkl

Acousto-optic deflectors (AOD) enable spatiotemporal control of laser beams through diffraction at an ultrasonic grating that is controllable by radio-frequency (rf) waveforms. These devices are a widely used tool for high-bandwidth random-access scanning applications, such as optical tweezers in quantum technology. A single AOD can generate multiple optical

R. J. Charity, G. H. Sargsyan, K. D. Launey, T. B. Webb

Levels in 8B have been investigated experimentally using the invariant-mass technique and compared to ab initio calculations. Data sets obtained using E/A=69-MeV 9C and 13O beams on a Be target have been further analyzed to extend the level scheme of 8B for Ex<10 MeV. New levels were observed in the 2p+6Li, p+3He+alpha, and the p+7Be+gamma exit channels. Mom

Enis Baty, C. P. Bridges, Simon Hadfield

We present FlowDet, the first formulation of object detection using modern Conditional Flow Matching techniques. This work follows from DiffusionDet, which originally framed detection as a generative denoising problem in the bounding box space via diffusion. We revisit and generalise this formulation to a broader class of generative transport problems, while

William English, Chase Walker, Dominic Simon, Rickard Ewetz

Natural language (NL) to temporal logic (TL) translation enables engineers to specify, verify, and enforce system behaviors without manually crafting formal specifications-an essential capability for building trustworthy autonomous systems. While existing NL-to-TL translation frameworks have demonstrated encouraging initial results, these systems either expl

DMC Collaboration, A. Kemp, S. Autti, E. Bloomfield

We report the characterisation of a FBK NUV-HD-cryo silicon photomultiplier (SiPM) sensor operated in a 9.4 $\pm$ 0.2 mK environment inside a dilution refrigerator, towards the development of a cryogenic cosmic ray muon veto system to be operated internal to a dilution refrigerator required for low background experiments such as the QUEST-DMC dark matter sea

Gonzalo Rodríguez-Pajares, Diego Ruano, Flavio Salizzoni

We prove that the set of points associated to a self-dual code with no proportional columns is arithmetically Gorenstein if and only if the code is indecomposable. This answers a question asked by Toh{\u{a}}neanu. We do so by providing a combinatorial way to compute the dimension of the Schur square of a self-dual code through a zero-one symmetrization of it

Sudip Mandal, Mihir Ranjan Sahoo, Kalpataru Pradhan

Epitaxial strain provides a powerful, non-chemical route to tune the properties of functional materials by manipulating the coupling between spin, charge, and lattice degrees of freedom. Using density functional theory (DFT) calculations and $\rm BiFeO_3$ as a model system, we first demonstrate how epitaxial strain exactly leads to anisotropic magnetic inter

Emma Godden, Katherine M. Blundell

Accurate modelling of the effective point spread function (ePSF) is essential for high-precision photometry and astrometry, particularly in undersampled imaging regimes. In this work, we build on a well-established ePSF modelling framework and its commonly used open-source Python implementation and demonstrate that several simple but effective modifications