March 2026 arXiv papers — page 100

Hong Jiang, Carlos Barahona-Pascual, Juan José García-Ripoll

The short quantum link regime, where the photon travel time $\tau$ is comparable to the emitter lifetime $1/\gamma$, is experimentally relevant but theoretically underexplored: existing few-mode descriptions lose validity as retardation and multimode effects become significant. Using a Delay Differential Equation (DDE) framework that admits exact analytical

Aayam Bansal, Ishaan Gangwani

Cooperative perception among autonomous agents overcomes the limitations of single-agent sensing, but bandwidth constraints in vehicle-to-everything (V2X) networks require efficient communication policies. Existing approaches rely on reactive mechanisms, such as confidence maps, learned gating, or sparse masks, to decide what to transmit, without reasoning a

Tushar Pandey

Fair threshold estimation for bivariate bicycle (BB) codes on the quantum erasure channel runs into two recurring problems: decoder-baseline unfairness and the conflation of finite-size pseudo-thresholds with true asymptotic thresholds. We run both uninformed and \emph{erasure-aware} minimum-weight perfect matching (MWPM) toric code baselines alongside BP-OS

Alexander Munteanu, Simon Omlor, Jeff M. Phillips

We establish new exponential in dimension lower bounds for the Maximum Halfspace Discrepancy problem, which models linear classification. Both are fundamental problems in computational geometry and machine learning in their exact and approximate forms. However, only $O(n^d)$ and respectively $\tilde O(1/\varepsilon^d)$ upper bounds are known and complemented

Jacob T. Willson, Henrik J. Heelweg, Adam P. Willard

Statistical mechanics reveals that the properties of a macroscopic physical system emerge as an average over an ensemble of statistically independent microscopic subsystems, each occupying a specific microstate. In the study of quantum systems, these microstates can be chosen to correspond to the pure state wavefunctions of individual quantum systems. Howeve

Oliver Cory, Ozge Mercanoglu Sincan, Richard Bowden

This paper introduces SignAgent, a novel agentic framework that utilises Large Language Models (LLMs) for scalable, linguistically-grounded Sign Language (SL) annotation and dataset curation. Traditional computational methods for SLs often operate at the gloss level, overlooking crucial linguistic nuances, while manual linguistic annotation remains a signifi

Berent Å. S. Lunde, Maximilian Ramgraber

Non-Gaussian statistics are a challenge for data assimilation. Linear methods oversimplify the problem, yet fully nonlinear methods are often too expensive to use in practice. The best solution usually lies between these extremes. Triangular measure transport offers a flexible framework for nonlinear data assimilation. Its success, however, depends on how th

Qunyou Liu, Marina Zapater, David Atienza

Transformers have revolutionized AI in natural language processing and computer vision, but their large computation and memory demands pose major challenges for hardware acceleration. In practice, end-to-end throughput is often limited by paged data movement and interconnect bandwidth rather than raw MAC count. This work proposes a unified system-accelerator

Johnny Corbino

We present a mimetic finite-difference approach for solving Maxwell's equations in one and two spatial dimensions. After introducing the governing equations and the classical Finite-Difference Time-Domain (FDTD) method, we describe mimetic operators that satisfy a discrete analogue of the extended Gauss divergence theorem and show how they lead to a compact,

Zina-Sabrina Duma, Victoria Jorry, Ayesha Safraz, Maria Paola di Crosta

Kernel-based multivariate statistical process control (K-MSPC) extends classical monitoring to nonlinear industrial processes. Its performance depends critically on kernel parameters such as lengthscales and variance terms. In current practice these parameters are typically selected by heuristics or deterministic optimisation, and then treated as fixed, desp

Phuc Pham, Uy Dieu Tran, Binh-Son Hua, Phong Nguyen

Realistic and efficient 3D garment generation remains a longstanding challenge in computer vision and digital fashion. Existing methods typically rely on large vision- language models to produce serialized representations of 2D sewing patterns, which are then transformed into simulation-ready 3D meshes using garment modeling framework such as GarmentCode. Al

Hao Wang, Jingxia Liu, Drew B. Cameron, Jiaqi Tong

Longitudinal cluster randomized trials (L-CRTs) are increasingly used to evaluate the cost-effectiveness of healthcare interventions across multiple assessment periods, yet design methods for powering these trials remain underdeveloped. Existing methods for cost-effectiveness analyses in cluster settings are limited to simple parallel-arm cluster randomized

Chunyan Li, Ce Shang, Boris A. Malomed

Topological Bloch oscillations are a hallmark of quantum transport phenomenon in which wavepackets undergo oscillatory motion driven by the interplay between an external force and topological edge states and serve as a powerful dynamical probe for the geometric properties of topological bands. Spin-orbit coupling (SOC) has also emerged as a crucial ingredien

S. I. Chastain, G. E. Anderson, A. J. van der Horst, L. Rhodes

Here we present broadband radio modeling of GRB 240205B, using observations with the Australia Telescope Compact Array (ATCA) and the South African MeerKAT radio telescope. Our observations include an automatically triggered early-time ATCA observation that began approximately 13 minutes after the gamma-ray signal and continued for 12 hours, resulting in the

Weisong Dong, Ruijia Zhang

In this paper, we establish an a priori second-order estimate for admissible solutions satisfying a dynamic plurisubharmonic condition to equations involving sums of Hessian operators on compact Hermitian manifolds. The estimate is derived using a concavity inequality for complex sum-of-Hessian operators.

Chenyang Gu, Jiahao Cheng, Meicong Zhang, Pujun Zheng

Scientific ideation aims to propose novel solutions within a given scientific context. Existing LLM-based agentic approaches emulate human research workflows, yet inadequately model scientific reasoning, resulting in surface-level conceptual recombinations that lack technical depth and scientific grounding. To address this issue, we propose \textbf{MoRI} (\t

Benjamin Dörich, Roland Maier, Lukas Ullmer

We derive upper bounds on the complexity of ReLU neural networks approximating the solution of a linear system given the matrix and the right-hand side. We focus on matrices which are symmetric positive definite and sparse, as they appear in the context of finite difference and finite element methods. For such matrices, we extend available results for the ma

Arthur Dyevre, Ahmad Shahvaroughi

The integration of artificial intelligence (AI) technologies into judicial decision-making, particularly in pretrial, sentencing, and parole contexts, has generated substantial concerns about transparency, reliability, and accountability. At the same time, these developments have brought the limitations of human judgment into sharper relief and underscored t

Anaísa Lucena, Ana Martins, Armando J. Pinho, Sónia Gouveia

Autoregressive (AR) models remain widely used in time series analysis due to their interpretability, but convencional parameter estimation methods can be computationally expensive and prone to convergence issues. This paper proposes a Neural Network (NN) formulation of AR estimation by embedding the autoregressive structure directly into a feedforward NN, en

Yan Shu, Bin Ren, Zhitong Xiong, Xiao Xiang Zhu

Vision-language models (VLMs) have shown promise in earth observation (EO), yet they struggle with tasks that require grounding complex spatial reasoning in precise pixel-level visual representations. To address this problem, we introduce TerraScope, a unified VLM that delivers pixel-grounded geospatial reasoning with two key capabilities: (1) modality-flexi

Sahar Diskin, Michael Krivelevich, Itay Markbreit

We consider site (vertex) percolation on $d$-regular graphs, for both constant-degree and growing-degree cases. We give sufficient, and relatively tight, conditions for the emergence of the ``Erd\H{o}s-R\'enyi component phenomenon" in the supercritical regime $p=\frac{1+\epsilon}{d-1}$: namely, the appearance of a unique giant component of order $n/d$ in the

Yan Wang, Jiasheng Zeng

Let $f^{(r)}(n;s,k)$ denote the maximum number of edges in an $r$-graph on $n$ vertices in which every $k$ edges span more than $s$ vertices. Brown, Erd\H{o}s and S\'{o}s in 1973 conjectured that for every $k\geq 2$, the limit $\lim_{n\to\infty} n^{-2} f^{(3)}(n;k+2,k)$ exists and verified the conjecture for $k=2$ by showing that $\lim_{n\to\infty} n^{-2} f^

Rodney Gomes

Neptune's present axial tilt of approximately 28 deg. with respect to its orbital plane can be explained by collisions that its primordial core may have experienced with surrounding planetary embryos during the final stages of its formation. Alternatively, Neptune could have attained its present mass solely through pebble accretion, without the formation of

Faizuddin Ahmed, Edilberto O. Silva

We investigate the thermodynamic properties of charged anti-de Sitter black holes surrounded by a cloud of strings in bumblebee gravity. In this framework, the cloud-of-strings parameter $\alpha$ and the Lorentz-violating parameter $\ell$ modify the horizon structure, the Hawking temperature, the free energies, the specific heat, and the critical behavior in

Berke Deniz Bozyigit

Weighted summation has remained the default input aggregation mechanism in artificial neurons since the earliest neural network models. While computationally efficient, this design implicitly behaves like a mean-based estimator and is therefore sensitive to noisy or extreme inputs. This paper investigates whether replacing fixed linear aggregation with learn

Federica Donnini, Pierluigi Mansueto

This paper addresses smooth convexly constrained optimization problems where the Euclidean projection onto the feasible set is computationally tractable. Although momentum techniques like Polyak's heavy-ball are known for accelerating optimization algorithms, their use in constrained settings remains limited due to challenges in preserving feasibility and en

N. V. Shinde, S. A. Mane

Codes are crucial in many areas of applications. Different types of codes are designed to meet specific needs, which makes them more effective and useful. Linear codes are extensively used in data storage systems. Identifying codes are essential for locating malfunctioning processors. To combine these benefits, researchers have looked into a type of code cal

Kim Zierahn, Cristina Cachero, Anna Korhonen, Nuria Oliver

A growing body of research examines personality traits in Large Language Models (LLMs), particularly in human-agent collaboration. Prior work has frequently applied the Big Five inventory to assess LLM behavior analogous to human personality, without questioning the underlying assumptions. This paper critically evaluates whether LLM responses to personality

Weihang Huang, Chaoran Zhang, Xiaoxin Deng, Hao Zhou

Flexible manufacturing requires robot systems that can adapt to constantly changing tasks, objects, and environments. However, traditional robot programming is labor-intensive and inflexible, while existing learning-based assembly methods often suffer from weak positional generalization, complex multi-stage designs, and limited multi-skill integration capabi

Quentin Guimard, Federico Bartsch, Simone Caldarella, Rahaf Aljundi

Models that bridge vision and language, such as CLIP, are key components of multimodal AI, yet their large-scale, uncurated training data introduce severe social and spurious biases. Existing post-hoc debiasing methods often operate directly in the dense CLIP embedding space, where bias and task-relevant information are highly entangled. This entanglement li

Pablo Vidal García, Andrea Alimenti, Dorothea Fonnesu, Davide Ford

In this work, microwave measurements carried out in dielectric-loaded resonators exposed to high magnetic fields are exploited to yield the surface impedance of Nb$_3$Sn superconducting coatings deposited via two different techniques: vapor tin diffusion, and DC magnetron sputtering. The obtained data lead to qualitative interpretations on both the Nb$_3$Sn

Anqi Zhang, Xiaokang Ji, Guangyu Gao, Jianbo Jiao

Recent segmentation methods leveraging Multi-modal Large Language Models (MLLMs) have shown reliable object-level segmentation and enhanced spatial perception. However, almost all previous methods predominantly rely on specialist mask decoders to interpret masks from generated segmentation-related embeddings and visual features, or incorporate multiple addit

Pranay Anchuri, Matteo Campanelli, Paul Cesaretti, Rosario Gennaro

When large AI models are deployed as cloud-based services, clients have no guarantee that responses are correct or were produced by the intended model. Rerunning inference locally is infeasible for large models, and existing cryptographic proof systems -- while providing strong correctness guarantees -- introduce prohibitive prover overhead (e.g., hundreds o

Ammar Fayad

Classical reverse diffusion is generated by changing the drift at fixed noise. We show that the quantum version of this principle obeys an exact law with a sharp phase boundary. For Gaussian pure-loss dynamics -- the canonical model of continuous-variable decoherence in optical attenuation channels, squeezed-light interferometric sensing, and superconducting

Jonah Leshin, Manish Shah, Ian Timmis, Daniel Kang

The consistency of AI-native applications depends on the behavioral consistency of the model endpoints that power them. Traditional reliability metrics such as uptime, latency and throughput do not capture behavioral change, and an endpoint can remain "healthy" while its effective model identity changes due to updates to weights, tokenizers, quantization, in

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac

This is the third paper of the set recording the results of the suite of tests of general relativity (GR) performed on the signals from the fourth Gravitational-Wave Transient Catalog (GWTC-4.0), where we focus on the remnants of the binary mergers. We examine for the first time 42 events from the first part of the fourth observing run of the LIGO-Virgo-KAGR

The LIGO Scientific Collaboration, the Virgo Collaboration, the KAGRA Collaboration, A. G. Abac

The worldwide LIGO-Virgo-KAGRA network of gravitational-wave (GW) detectors continues to increase in sensitivity, thus increasing the quantity and quality of the detected GW signals from compact binary coalescences. These signals allow us to perform ever-more sensitive tests of general relativity (GR) in the dynamical and strong-field regime of gravity. This

Ruolin Wang, Takanobu Amano

We investigate the mechanism of whistler-mode wave generation by shock-reflected electrons at quasi-perpendicular collisionless shocks. By employing Liouville mapping to construct the electron velocity distribution function in the shock and performing linear instability analysis, we explore whistler wave generation by the mirror-reflected electrons near the

Gagan Bhatia, Ahmad Muhammad Isa, Maxime Peyrard, Wei Zhao

We present MultiTempBench, a multilingual temporal reasoning benchmark spanning three tasks, date arithmetic, time zone conversion, and temporal relation extraction across five languages (English, German, Chinese, Arabic, and Hausa) and multiple calendar conventions (Gregorian, Hijri, and Chinese Lunar). MultiTempBench contains $15,000$ examples built by tra

Cao Tram Anh Hoang

This study investigates the adoption and effectiveness of AI-based anomaly detection in cross-provider electronic health record (EHR) environments. It aims to (1) identify the organisational and digital capabilities required for successful implementation and (2) evaluate the performance and interpretability of lightweight anomaly detection approaches using c

Shekhar Suman, Xiaoyu Chu, Alexandru Iosup

By 2025, there are zettabytes of data generated every year. The size and complexity of modern large-scale computing infrastructures like High-Performance Computing (HPC) systems continue to evolve and become complex, leaving us wondering about their manageability and sustainability concerns. Because of this reason, those complex systems are provided with fin

Francesco G. Schiavone, Guillaume Daviller, Davide Laera

The impact of thermodiffusive effects on combustion noise in turbulent premixed slot jet flames is investigated using Direct Numerical Simulations. Two thermodiffusively unstable lean hydrogen-air flames are compared with a thermodiffusively stable stoichiometric methane-air flame with comparable laminar properties and same turbulence intensity. The hydrogen

Yongzheng Dai

The alternating-current unit commitment problem provides a realistic representation of power system operations, which is a nonconvex mixed-integer nonlinear programming problem and hence is computationally intractable. A common relaxation to the alternating-current unit commitment problem is based on the second-order cone, which results in a mixed-integer se

Enrico Bottazzi, Pia Park

NDAI zones let inventor and investor agents negotiate inside a Trusted Execution Environment (TEE) where any disclosed information is deleted if no deal is reached. This makes full IP disclosure the rational strategy for the inventor's agent. Leveraging this infrastructure, however, requires agents to distinguish a secure environment from an insecure one, a

Omar Bachain, Mohamed Amazioug, Rachid Ahl Laamara

We investigate the multiparameter quantum estimation and quantum thermodynamics properties of a gravitational cat state (gravcat) system composed of two interacting massive particles confined in double-well potentials. The system is described by an effective Hamiltonian involving the energy splitting parameter $\omega$ and the gravitational coupling strength

Hangeol Chang, Changsun Lee, Seungjoon Rho, Junho Yeo

Retrieval-Augmented Generation (RAG) improves Large Language Models (LLMs) by grounding generation in external, non-parametric knowledge. However, when a task requires choosing among competing options, simply grounding generation in broadly relevant context is often insufficient to drive the final decision. Existing RAG methods typically rely on a single ini

Yuzhe Weng, Haotian Wang, Yuanhong Yu, Jun Du

Audio-driven talking head generation aims to create vivid and realistic videos from a static portrait and speech. Existing AR-based methods rely on intermediate facial representations, which limit their expressiveness and realism. Meanwhile, diffusion-based methods generate clip-by-clip, lacking fine-grained control and causing inherent latency due to overal

Elliot C. Eklund, Arkin Tikku, Patrick Sinnott, William J. Huggins

Simulations of chemical dynamics are a powerful means for understanding chemistry. However, classical computers struggle to simulate many chemical processes, especially non-adiabatic ones, where the Born-Oppenheimer approximation breaks down. Quantum computers could simulate quantum-chemical dynamics more efficiently than classical computers, but there is cu

Raffaele Cappelli

Fingerprint recognition systems, which rely on the unique characteristics of human fingerprints, are essential in modern security and verification applications. Accurate minutiae extraction, a critical step in these systems, depends on the quality of fingerprint images. Despite recent improvements in fingerprint enhancement techniques, state-of-the-art metho

Weronika Łajewska, Paul Missault, George Davidson, Saab Mansour

Simulation of surveys using LLMs is emerging as a powerful application for generating human-like responses at scale. Prior work evaluates survey simulation using metrics borrowed from other domains, which are often ad hoc, fragmented, and non-standardized, leading to results that are difficult to compare. Moreover, existing metrics focus mainly on accuracy o

Philipp Gohlke, Georgios Lamprinakis, Jörg Schmeling

We consider the family of singular potentials $\psi_c = 2 \log(|\sin(\pi(x-c))|)$, $c\in \mathbb{T}$ over the doubling map and we examine the dependence of several thermodynamic and multifractal characteristics on the position of the singularity $c$. This includes the pressure functions $\mathcal P(t \psi_c)$, the Birkhoff spectrum of $\psi_c$, and the $L^q$

Patrick Phuoc Do, Kaiyuan Tang, Kuangshi Ai, Chaoli Wang

Scientific visualization (SciVis) has become an essential means for exploring, understanding, and communicating complex scientific phenomena. However, the field still lacks a validated instrument assessing how well people read, understand, and interpret them. We present a scientific visualization literacy assessment test (SVLAT) that measures the general pub

Rui Chai

We study online resource allocation among N interacting modules over T rounds. Unlike standard online optimization, costs are endogenous: they depend on the full allocation vector through an interaction matrix W encoding pairwise cooperation and competition. We analyze three paradigms: (I) uniform allocation (cost-ignorant), (II) gated allocation (cost-estim

Yu-Feng Song, Youjin Deng, Yuan-Yao He

We develop a highly efficient framework for computing the thermal entropy in the doped Fermi-Hubbard model within the grand-canonical ensemble. The framework comprises four calculation schemes that express the entropy as path integrals in the parameter space of temperature, interaction strength, and chemical potential. The integrands involve only fundamental

Thomas Bläsius, Emil Dohse, Deborah Haun, Laura Merker

Hyperbolic uniform disk graphs (HUDGs) are intersection graphs of disks with some radius $r$ in the hyperbolic plane, where $r$ may be constant or depend on the number of vertices in a family of HUDGs. We show that HUDGs with constant clique number do not admit \emph{product structure}, i.e., that there is no constant $c$ such that every such graph is a subg

Shuanger Ma, Sabine Tornow, Eli Barkai

We study non-equilibrium steady states and recurrence times in noisy, stroboscopically monitored qubit systems using complete measurements. In the noiseless limit, recurrence times are integer-quantized, with dips to lower integers when sampling approaches revival conditions associated with ergodicity breaking. Using an IBM quantum platform, we find that qua

P. Meena, Y. A. Rouzoumka, J. Pinsolle, C. Ren

Radar target detection in the presence of a mixture of non-Gaussian clutter and white thermal noise is a challenging problem. This paper proposes a Rectified Flow Matching-based method for radar detection, termed D-RFM. Unlike existing detectors, D-RFM learns a mapping from a standard Gaussian distribution to radar observations by capturing the underlying ve

Chun-Jui Wang, Jian-Ting Guo, Hung Guei, Chung-Chin Shih

Tetris Block Puzzle is a single player stochastic puzzle in which a player places blocks on an 8 x 8 grid to complete lines; its popular variants have amassed tens of millions of downloads. Despite this reach, there is little principled assessment of which rule sets are more difficult. Inspired by prior work that uses AlphaZero as a strong evaluator for ches

Fabricio Alcalde Bessia, Claudio Chavez, Troy England, Hongzhi Sun

The MIDNA application specific integrated circuits (ASICs) are a series of skipper-CCD readout chips fabricated in a 65 nm low-power CMOS process that implement a correlated double sampling signal processing chain based on dual-slope integrators. They are capable of working from room to cryogenic temperatures, down to 84 K. The present iteration of the ASIC

Sophia Tang

At the core of modern generative modeling frameworks, including diffusion models, score-based models, and flow matching, is the task of transforming a simple prior distribution into a complex target distribution through stochastic paths in probability space. Schr\"odinger bridges provide a unifying principle underlying these approaches, framing the problem a

Zening Sun, Zhengpeng Xie, Lichen Bai, Shitong Shao

Aligning Diffusion models has achieved remarkable breakthroughs in generating high-quality, human preference-aligned images. Existing techniques, such as supervised fine-tuning (SFT) and DPO-style preference optimization, have become principled tools for fine-tuning diffusion models. However, SFT relies on high-quality images that are costly to obtain, while

A. Yadav, U. Jena, A. Pradhan, Satish K.

The intriguing interplay between competing degrees of freedom in frustrated magnets can lead to non-trivial magnetic phenomena with exotic low-energy excitations that are highly relevant for addressing some of the fundamental questions in quantum condensed matter as well as potential technological applications. Herein, we report the synthesis and thermodynam

Joerg Deigmoeller, Nakul Agarwal, Stephan Hasler, Daniel Tanneberg

We introduce MERGE, a system for situational grounding of actors, objects, and events in dynamic human-robot group interactions. Effective collaboration in such settings requires consistent situational awareness, built on persistent representations of people and objects and an episodic abstraction of events. MERGE achieves this by uniquely identifying physic

Pronob Kumar Barman, Pronoy Kumar Barman

Predictive policing systems that direct patrol resources based on algorithmically generated crime forecasts have been widely deployed across US cities, yet their tendency to encode and amplify racial disparities remains poorly understood in quantitative terms. We present a reproducible simulation framework that couples a Generative Adversarial Network GAN wi

Bolin Fan, Anthony Bilodeau, Frederic Beaupre, Theresa Wiesner

Fluorescence-based Ca$^{2+}$-imaging is a powerful tool for studying localized neuronal activity, including miniature Synaptic Calcium Transients, providing real-time insights into synaptic activity. These transients induce only subtle changes in the fluorescence signal, often barely above baseline, which poses a significant challenge for automated synaptic

Domenico Sapone, Savvas Nesseris

Baryon acoustic oscillation (BAO) analyses usually report the anisotropic shift parameters $\alpha_\perp(z)$ and $\alpha_\parallel(z)$ relative to a fiducial cosmology, and these quantities are primarily used for cosmological parameter inference. Here we show that they can also be used to construct a direct internal consistency test of the background geometr

Alessandro Carbotti, Simone Cito, Domenico Angelo La Manna, Aldo Pratelli

We prove that if $\Omega\subseteq\mathbb{R}^N$ is a set with finite perimeter with $\mathscr{H}^{N-1}(\partial \Omega\setminus\partial^* \Omega)=0$, then any set of finite perimeter $E\subseteq\mathbb{R}^N$ can be approximated by a polyhedral or smooth bounded set $F$ in such a way that both the total perimeter of $E$ and the perimeter of $E$ inside $\Omega$

Mohammad Hosseini, Sadia Afrin, Anthony Yosick, Hani Awad

Osteoporosis, a major global epidemic, often goes undetected until a fracture occurs, largely due to poor access to screening using gold standard methods, such as dual-energy X-ray absorptiometry (DXA). As a potential nonionizing radiation alternative, we present a transcutaneous spatially offset Raman spectroscopy (SORS) approach combined with machine learn

Jiayi Hong, Yixuan Wang, Petra Isenberg, Ross Maciejewski

We present a review and analysis of scientific paper embellishments -- simple visual elements that are deeply integrated into the text of scientific publications. These embellishments are increasingly used in research papers, which have the potential to enhance textual descriptions, strengthen connections between figures and content, and improve internal tex

Clément Mallet, Ana-Maria Raimond

We face a unprecedented amount of geospatial data, describing directly or indirectly the Earth Surface at multiple spatial, temporal, and semantic scales, and stemming from numerous contributors, from satellites to citizens. The main challenge in all the geospatial-related communities lies in suitably leveraging a combination of some of the sources for eithe

Christian Di Maio, Tommaso Guidi, Luigi Quarantiello, Jack Bell

In this paper, we report our experience with ``TuringHotel'', a novel extension of the Turing Test based on interactions within mixed communities of Large Language Models (LLMs) and human participants. The classical one-to-one interaction of the Turing Test is reinterpreted in a group setting, where both human and artificial agents engage in time-bounded dis

Aada Hakula, Pauliina Hirvi, Nuutti Hyvönen

Linear inverse problems are highly common in practical real-world applications from industry to medical imaging. The forward operator is often built on some approximations of the studied system. Handling inaccuracies in the forward operator in the context of inverse problems is a relatively unstudied problem. In this work, we assume that we have a set of can

Chenxi Han, Shilu He, Yi Cheng, Linqi Ye

Training perceptive humanoid locomotion policies that traverse complex terrains with natural gaits remains an open challenge, typically demanding multi-stage training pipelines, adversarial objectives, or extensive real-world calibration. We present PRIOR, an efficient and reproducible framework built on Isaac Lab that achieves robust terrain traversal with

Marco Artiano, Hendrik Ranocha

Many entropy-conservative and entropy-stable (summarized as entropy-preserving) methods for hyperbolic conservation laws rely on Tadmor's theory for two-point entropy-preserving numerical fluxes and its higher-order extension via flux differencing using summation-by-parts (SBP) operators, e.g., in discontinuous Galerkin spectral element methods (DGSEMs). The

Diego Martin, Luis H. Arnaldi, Kenneth Treptow, Neal Wilcer

Quantum computing experiments and testbeds with large qubit counts have until recently been a privilege afforded only to large companies or quantum technologies where scaling to hundreds or thousands of qubits does not require a substantial increase in quantum control hardware (neutral atoms, trapped ions, or spin defects). Superconducting and spin qubit tes

Peng Gang

Natural language prompts often suffer from intent transmission loss: the gap between what users actually need and what they communicate to AI systems. We evaluate PPS (Prompt Protocol Specification), a 5W3H-based framework for structured intent representation in human-AI interaction. In a controlled three-condition study across 60 tasks in three domains (bus

Michael Cuntz, Thorsten Holm, Peter Jorgensen

A classic result of Conway and Coxeter on frieze patterns has been generalized to a bijection between $p$-angulations of regular polygons and frieze patterns of type $\Lambda_p$. One of the features of Conway-Coxeter theory is a combinatorial procedure to obtain from the triangulation all entries of the corresponding frieze pattern. We first present a combin

Borys Kuca

Recent years have seen dramatic progress in the study of joint ergodicity, i.e. a scenario in which a multiple ergodic average converges in norm to the product of integrals of individual functions. This survey, accompanying the talk given by the author in the Perspectives on Ergodic Theory and its Interactions conference to celebrate Vitaly Bergelson's 75th

Laura Congreve Hunter, Burçin Mutlu-Pakdil, Michael B. Farnell, David J. Sand

We present results from our ongoing campaign to follow up the satellite candidates from the Identifying Dwarfs of MC Analog GalaxiEs (ID-MAGE) survey. Previously, we published a list of 355 unresolved satellite candidates identified around 36~nearby LMC- and SMC-mass hosts (D$=$4$-$10~Mpc). We present the velocities of 83 satellite candidates from new Green

Khomesh R. Patle, G. P. Singh

In this paper, the dynamical behavior of the accelerated expansion of the universe is studied within the framework of $f(T)$ gravity by considering a well-motivated functional form of $f(T)$. A specific form of the Hubble parameter is assumed, which under two different cases, leads to two distinct cosmological models expressed in terms of the redshift parame

E. Kyritsis, A. Zezas, K. Kovlakas, C. Daoutis

We present HECATEv2, the second release of the Heraklion Extragalactic Catalogue (HECATE), an all-sky, value-added galaxy catalogue comprising 204733 galaxies from the HyperLEDA database with recession velocity <14000 km/s (D~200 Mpc). This release focuses on qualitative upgrades of the provided information while maintaining the same parent galaxy sample as

Shunzhi Pang

As insurers increasingly behave like financial intermediaries and actively participate in capital markets, understanding the dependence structure between insurance and financial risks becomes crucial for insurers' operations. This paper studies dynamic equilibrium insurance pricing when insurers face ambiguity about the correlation between insurance and fina

Dario Compagno, Fabio Massimo Zennaro

Structural causal models (SCMs) were conceived to formulate and answer causal questions. This paper shows that SCMs can also be used to formulate and answer teleological questions, concerning the intentions of a state-aware, goal-directed agent intervening in a causal system. We review limitations of previous approaches to modeling such agents, and then intr

Ricardo V. M. de Almeida Filho, Joao C. de Aquino Carvalho, Thierry Passerat de Silans, Marcio H. G. de Miranda

Multiple scattering of light by resonant vapor is characterized by Levy-type superdiffusion with a step size distribution $P(x) \propto 1/x^{1+{\alpha}}$, with $0 < {\alpha} < 2$. The Levy parameter ${\alpha}$ was measured from $P(x)$, steady fluorescence, frequency-dependent fluorescence and time-resolved transmission, all of them in the forward direction.

ALICE Collaboration

The ALICE collaboration reports the azimuthal-anisotropy coefficient $v_2$ of prompt D$^0$, D$^+$, D$^+_{\rm s}$ mesons and the first measurement of $v_2$ of prompt $\Lambda_{\rm c}$ baryons in semicentral Pb$-$Pb collisions at a center-of-mass energy per nucleon pair of $\sqrt{s_{\rm NN}} = 5.36$ TeV. The D mesons and $\Lambda_{\rm c}$ baryons are reconstru

Haichuan Hu, Ye Shang, Quanjun Zhang

Skill ecosystems have emerged as an increasingly important layer in Large Language Model (LLM) agent systems, enabling reusable task packaging, public distribution, and community-driven capability sharing. However, despite their rapid growth, the functionality, ecosystem structure, and security risks of public skill registries remain underexplored. In this p

Adrien Bolland, Gaspard Lambrechts, Damien Ernst

Maximum entropy reinforcement learning motivates agents to explore states and actions to maximize the entropy of some distribution, typically by providing additional intrinsic rewards proportional to that entropy function. In this paper, we study intrinsic rewards proportional to the entropy of the discounted distribution of state-action features visited dur

Harshvardhan J. Pandit, Dick A. H. Blankvoort, Adel Shaaban, Sasha Luccioni

Generative AI services like ChatGPT and Gemini are some of the fastest-growing consumer services. Individuals using such services must accept their terms of use before access, and conform to these terms for continued use of the service. Established literature has shown that despite their status as legally-binding agreements, terms of use are not actually wel

Daniel Barrera Salazar, Andrew Graham, Chris Williams

Let $G$ be a reductive group quasi-split at $p$. Using arguments of Hansen--Thorne, we show that under the non-abelian Leopoldt conjecture (NALC), Hansen&#39;s $p$-adic overconvergent cohomology eigenvariety for $G$ is étale over its image in weight space at any non-critical classical tempered cuspidal point of `cohomological multiplicity one&#39;. This appl

Shuyue Feng, Cedric Caremel, Yoshihiro Kawahara

Topology optimization (TO) is employed in engineering to optimize structural performance while maximizing material efficiency. However, traditional TO methods incur significant computational and time costs. Although research has leveraged generative AI to predict TO outcomes and validated feasibility and accuracy, existing approaches still suffer from limite

Umberto Filippi, Alexander Schleusener, Simone Lauciello, Roman Krahne

Semiconductor heterostructures that combine components with different dimensionality provide an interesting way to manipulate the physical properties of the resulting material. Two-dimensional lead halide perovskites crystallize as flat microcrystals and have efficient in-plane exciton mobility, while perovskite nanocrystals are efficient emitters with a tun

Andrzej Kaczmarczyk, Šimon Schierreich, Nicholas Axel Tanujaya, Haifeng Xu

Coordinating agents through hazardous environments, such as aid-delivering drones navigating conflict zones or field robots traversing deployment areas filled with obstacles, poses fundamental planning challenges. We introduce and analyze the computational complexity of a new multi-agent path planning problem that captures this setting. A group of identical

Sijian Fan, Liyan Xiong, Dayuan Wang, Guoshuai Cai

Recent advances in drug discovery have demonstrated that incorporating side information (e.g., chemical properties about drugs and genomic information about diseases) often greatly improves prediction performance. However, these side features can vary widely in relevance and are often noisy and high-dimensional. We propose Bayesian Variable Selection-Guided

J. -G. Ducoin, C. Pellouin, V. Aivazyan, D. Akl

Gamma-Ray Burst GRB 241030A (z = 1.411) exhibited a bright afterglow (similar to GRB 221009A), detected across gamma-ray, X-ray, UV, and optical bands, providing a probe of GRB afterglow physics. We compiled multi-wavelength observations spanning from a minute to a week after the prompt emission, processing the data through a unified photometry pipeline. We

Corneille Niyonkuru, Marcellin Atemkeng, Gabin Maxime Nguegnang, Arnaud Nguembang Fadja

Reliable anomaly detection in distributed power plant monitoring systems is essential for ensuring operational continuity and reducing maintenance costs, particularly in regions where telecom operators heavily rely on diesel generators. However, this task is challenged by extreme class imbalance, lack of interpretability, and potential fairness issues across

Saaket Agashe, Jayanth Srinivasa, Gaowen Liu, Ramana Kompella

Reinforcement Learning from Verifiable Rewards (RLVR) suffers from exploration inefficiency, where models struggle to generate successful rollouts, resulting in minimal learning signal. This challenge is particularly severe for tasks that require the acquisition of novel reasoning patterns or domain-specific knowledge. To address this, we propose Context Boo

Matija Bucic, Kaizhe Chen, Jie Ma

Given a graph $H$, the maximal anti-Ramsey function $f(n,e,H)$ denotes the minimum integer $f$ for which there exists an $n$-vertex graph $G$ with at least $e$ edges admitting an edge-coloring with $f$ colors in which each copy of $H$ in $G$ is rainbow. In the late 1980s, Burr, Erd\H{o}s, Graham, and S\'os conjectured that for every odd cycle $C_{2k+1}$ with

Xin-Kai Wen, Bin Yan, Zhite Yu, C. -P. Yuan

In this talk, we present novel methods to investigate light-quark dipole interactions at colliders. Our approach includes: (1) measuring azimuthal asymmetries of a collinear dihadron in semi-inclusive deep inelastic lepton scattering off an unpolarized proton target at the Electron-Ion Collider, and (2) utilizing azimuthal asymmetries of dihadron $(h_1 h_2)$

Shitao Fang, Koji Yatani, Kasper Hornbæk

In HCI, frameworks function as a type of theoretical contribution, often supporting ideation, design, and evaluation. Yet, little is known about how they are actually used, what functions they serve, and which scholarly practices that shape them. To address this gap, we conducted a systematic review of 615 papers from a decade of CHI proceedings (2015-2024)

Gennian Ge, Jialuo Wang, Zixiang Xu

In 1974, Erd\H{o}s and Kleitman conjectured that if a family $\mathcal{F}\subseteq 2^{[n]}$ contains no matching of size \(s\) and is maximal with respect to this property, then $ |\mathcal{F}|\ge \left(1-2^{-(s-1)}\right)\cdot 2^{n}. $ For decades, the best general lower bound remained the trivial $2^{n-1}$. About a decade ago, Frankl and Tokushige emphasiz