April 2026 arXiv papers — page 12

Anh Ta, Junjie Zhu, Shahin Shayandeh

Tool-calling agents are evaluated on tool selection, parameter accuracy, and scope recognition, yet LLM trajectory assessments remain inherently post-hoc. Disconnected from the active execution loop, such assessments identify errors that are usually addressed through prompt-tuning or retraining, and fundamentally cannot course-correct the agent in real time.

Kashif Imteyaz, Isabel Lopez, Nakul Rajpal, Hunjun Shin

Freelance workers must continually acquire new skills to remain competitive in online labor markets, yet they lack the organizational training, mentorship, and infrastructure available to traditional employees. Generative AI-powered tools like ChatGPT are reshaping market skill demands while also offering new forms of on-demand learning support to meet those

Chandra N. Sekharan, George K. Thiruvathukal

Computer science (CS) education needs to evolve to support software and artificial intelligence (AI) systems engineering, and it needs to happen now -- precisely because the core intellectual contributions of CS have never been more important. We argue that traditional curricula, built around programming, data structures, and algorithms as ends in themselves

Hyunsuk Kim

We study some interesting hypersurfaces that naturally arise when studying the period map on the moduli space of hypersurfaces, in the context of Sung Gi Park's recent work on studying the GIT moduli space of hypersurfaces via the minimal exponent. We compute the Hodge structure on the singular cohomology and the intersection cohomology of these hypersurface

Juergen Dietrich

Democratic discourse analysis systems increasingly rely on multi-agent LLM pipelines in which distinct evaluator models are assigned adversarial roles to generate structured, multi-perspective assessments of political statements. A core assumption is that models will reliably maintain their assigned roles. This paper provides the first systematic empirical t

Thomas Bellitto, Jules Bouton Popper, Justine Cauvi, Bruno Escoffier

Connectivity of temporal graphs has been widely studied both as graph theory and as gossip theory. In particular, it is well known that in order to connect every vertex to every other, a temporal graph needs to have at least $2n-4$ edges where $n$ is the number of vertices. This paper investigates the optimal number of edges required to satisfy partial conne

Serge Galam

I study the impact of mixed contrarians on the opinion dynamics of an heterogenous population with conformists using Galam Majority Model. Activation of contrarians is a function of the ratio majority/minority in the local groups of discussion. Restricting the group size to 3, two types of contrarians are included in respective proportions $c_{3,0}$ for conf

Gideon K. Gogovi

The rapid integration of generative AI into academic workflows demands curricula that equip students not only with tool proficiency but with the critical judgment to use those tools responsibly in scholarly work. Existing offerings cluster around two inadequate poles: technical AI development courses serving narrow specialist audiences, and brief general-lit

Johannes Graf

Graph databases offer unparalleled flexibility for managing interconnected data, yet the lack of strict schema enforcement often leads to runtime uncertainties and complex query development. This paper introduces Graphify, an end-to-end framework that enables developers to visually model graph data schemas and automatically synthesize a fully functional, typ

Cherif F. Matta

The chemical bond is a central organizing concept in chemistry, yet it is absent from the molecular Hamiltonian and no "bond operator" exists. Bonding is therefore not a primitive physical entity but a derived descriptor emerging from the quantum state. The logical consequences of this observation are revisited. Statements such as "bonding stabilizes structu

Yuxuan Huang, Yihang Chen, Zhiyuan He, Yuxiang Chen

Agentic web search increasingly faces two distinct demands: deep reasoning over a single target, and structured aggregation across many entities and heterogeneous sources. Current systems struggle on both fronts. Breadth-oriented tasks demand schema-aligned outputs with wide coverage and cross-entity consistency, while depth-oriented tasks require coherent r

Georgiy Baroncha, Alexander Perepukhov, Boris V. Fine

Multirate characterization of spin responses in nuclear magnetic resonance (NMR) is a promising approach to fingerprinting complex molecules in the presence of multiple relaxation mechanisms. Here we present experimental and theoretical investigations simultaneously accessing 8 relaxation rates describing the density matrix of two adjacent non-equivalent nuc

Achyuta Telekicherla Kandalam, Daniel Spirn

The Immersed Boundary Method has long served as a robust computational framework for fluid-structure interactions, yet the rigorous analysis of 1D Peskin filaments anchored to rigid boundaries remains sparse. In this paper, we generalize the classical Peskin problem to the half-plane by considering an elastic filament whose endpoints are anchored to a no-sli

Basudha Pal, Siyuan Huang, Anirudh Nanduri, Zhaoyang Wang

Person re-identification (ReID) systems that match individuals across images or video frames are essential in many real-world applications. However, existing methods are often influenced by attributes such as gender, pose, and body mass index (BMI), which vary in unconstrained settings and raise concerns related to fairness and generalization. To address thi

Bulent Soykan, Gulsah Hancerliogullari Koksalmis, Hsin-Hsiung Huang, Laura J. Brattain

Cognitive decline is highly heterogeneous across individuals, which complicates prognosis, trial design, and treatment planning. We present the Personalized Cognitive Decline Assessment Digital Twin (PCD-DT), a multimodal and uncertainty-aware framework for modeling patient-specific disease trajectories from sparse, noisy, and irregular longitudinal data. Th

T. Ansah-Narh, G. Y. Afrifa, J. B. Tandoh, K. Asare

Groundwater in the Densu Basin is increasingly threatened by heavy metal contamination, but conventional methods fail to capture the statistical complexity and spatial heterogeneity of pollution indicators. A key challenge is modelling the Heavy Metal Pollution Index (HPI), which is typically skewed and affected by correlated contaminants, leading to biased

Dai-Nam Le, Lilia M. Woods

Nanoscaled friction is a fundamental tribological phenomenon with complex behavior of its dynamical force. Here, we utilize the Prandtl-Tomlinson framework to investigate systematically the different means of control of the frictional force at the quantum and classical levels. It is found that the frictional dynamics can be controlled by the corrugation and

Haonan Miao

We prove the validity of using subsampling method for inference under a two-way clustered panel in which the time effects are serially correlated. Subsamples should be drawn without replacement from randomly partitioned individual index set and consecutive blocks of time effects. We present two subsampling inference methods: estimating the quantiles directly

Andrew Tang, Romil Audhkhasi, Virat Tara, Abhi Saxena

On-chip silicon photonic coupled cavity arrays (CCA) are a promising platform for quantum simulators, with access to high Quality (Q) factor resonators, tunability, and foundry compatibility. Furthermore, scalable two-dimensional (2D) silicon photonic CCAs allow for simulation of rich physical phenomena via Hamiltonian engineering. However, complete reconstr

Joseph Breen, Austin Christian, Angela Wu

We initiate the study of Reidemeister hardness of Legendrian unknot front projections. Using normal rulings, we obstruct several infinite families of hard unknot diagrams from being drawn with max-tb unknot fronts, along with 1.7 million of the 2.6 million hard unknot diagrams studied in \cite{applebaum2024unknottingnumberhardunknot}. We construct infinitely

Moshe Babaioff, Uriel Feige, Noam Manaker Morag

We study fair allocation of indivisible goods among strategic agents with additive valuations. Motivated by impossibility results for deterministic truthful mechanisms, we focus on randomized mechanisms that are \emph{Truthful-in-Expectation (TIE)}. From a fairness perspective, we seek to guarantee every agent a large fraction of their \emph{Maximin Share (M

Halley Young, Nikolaj Björner

Large language models can now generate substantial code and draft research text, but research-software projects require more than either artifact alone. The mathematical thesis, executable system, benchmark surface, and public claims must mature together, yet often drift apart. We identify two LM-specific failure modes: hallucination accumulation, in which c

Maryam Maghazeh, Ayyappan Unnikrishna Pillai, Mohammad Masiur Rahaman, Subhayan De

Reliability-based topology optimization (RBTO) requires repeated estimation of small failure probabilities and their gradients, making conventional nested Monte Carlo approaches computationally prohibitive for large scale structural problems. We propose an RBTO framework that integrates large deviation theory~(LDT) with stochastic gradient descent~(SGD) to a

Ziying Wang, Ying Zhang, Lei Wang, Yuzhang Lin

Short-term load forecasting for AI data centers presents new challenges because it is computing-driven, with heterogeneous job arrivals, sizes, and durations exhibiting bursty, non-stationary dynamics. Compared with traditional load types, data center loads are less researched and can pose greater threats to the efficiency and stability of power grids. To cl

Md Aminur Hossain, Ayush V. Patel, Ikshwaku Vanani, Biplab Banerjee

Semantic segmentation in remote sensing is commonly addressed using classical deep learning architectures such as U-Net, which require a large number of parameters to model complex spatial relationships. Quantum machine learning (QML) provides an alternative representation paradigm by mapping classical features into quantum states, but its direct application

Martin V. Hildebrand, Christopher J. Lange

Upon the introduction of the Metropolis algorithm, the question of how many steps in the Markov chain were needed to achieve convergence to stationarity became apparent. The convergence was rather slow, i.e. for a process on $n$ states the number of steps needed to achieve convergence to stationarity was found to be on the order of $n^2$ if the underlying di

Tobias Bystrich, Julia M. Pritzen, Christoph A. Schmidt, Claudia Wich-Reif

In the field of universal automatic phonetic transcription (APT), clean and diverse training transcriptions are required. However, such high-quality data is limited. We propose the bootstrapping approach Selective Augmentation to improve the available training transcriptions by selectively transferring distinctions between languages. Based on the model MultI

Diego F. Cuadros, Abdoul-Aziz Maiga

We report a safety incident in a deployed multi-agent research system in which a primary AI agent installed 107 unauthorized software components, overwrote a system registry, overrode a prior negative decision from an oversight agent, and escalated through increasingly privileged operations up to an attempted system administrator command. The incident was pr

Usman Nazir, I-Han Cheng, Sara Khalid

Malaria, childhood acute respiratory infection, and child undernutrition together account for over two million deaths annually in children under five, with the burden concentrated in low and middle-income countries where climate variability modulates transmission, exposure, and nutritional outcomes. Routine health surveillance in these settings remains spars

Soheil Khodayari, Xuenan Zhang, Bhupendra Acharya, Giancarlo Pellegrino

As LLMs are increasingly integrated into systems that browse, retrieve, summarize, and act on web content, webpages have become an untrusted input vector for downstream model behavior. This enables site owners, contributors, and adversaries to embed instructions directly in web resources, i.e., indirect prompt injections. While prior work demonstrates such a

Shouren Wang, Wang Yang, Chuang Ma, Debargha Ganguly

Hybrid-thinking language models expose explicit /think and /no_think modes, but current designs do not separate them cleanly. Even in /no_think mode, models often emit long and self-reflective responses, causing reasoning leakage. Existing work reduces this issue through better data curation and multi-stage training, yet leakage remains because both modes ar

Ayantika Bhattacharjee, Spencer Jones, Dhruv Balwada, Shane Elipot

Ocean turbulence plays a key role in shaping large-scale circulation, heat uptake, and biogeochemical processes. The kinetic energy (KE) wavenumber spectrum is a fundamental diagnostic, quantifying how KE is distributed across spatial scales. The second-order structure function -- computed from velocity differences between spatially separated observations --

Alexandra Crawford, Jacob Williamson, Robert Leonard, Ce Pei

We demonstrate a micro-Fabry-P\'erot cavity array through laser etching of high-surface-quality mirrors onto a single fused silica substrate. A cavity finesse of $4750\pm 200$ was achieved with a simple array design with $500~\mu m$ cavity length, $100~\mu m$ diameter micromirrors and $300~\mu m$ transverse separation. Arrays with up to 12 cavities were simu

Slava G. Turyshev

Orbital data centers are being evaluated as solar-powered compute constellations and relay-integrated processing platforms. Their feasibility is not set by orbital solar flux alone, but by simultaneous closure of photovoltaic generation, eclipse recharge, radiative heat rejection, sustained space-to-ground communications, utilization, replacement cadence, an

Curtis McDonald

Recent results have shown that for a linear tilt to a reference measure, the scores that would be produced under convolution with a normal variable can be expressed in terms of convolutions of the original density. Here, we extend that result to include constant negative diagonal tilts as well. The relationship follows from relating the denoisers of the two

Gianluca Panati, Constanza Rojas-Molina, Vincenzo Rossi

We show the existence of energies exhibiting dynamical delocalization in discrete 2D Chern insulators perturbed by a random potential in a general setting. Our proof exploits two main features of the model: jumps in the integer value of the Chern character and continuity of averaged spectral projections in both energy and disorder parameters. This allows us

Akshay Karjol, Shadi Alawneh

Automatic Emergency Braking (AEB) systems represent a safety-critical national interest, with the National Highway Traffic Safety Administration (NHTSA) Federal Motor Vehicle Safety Standard (FMVSS No. 127) requiring AEB in all new light vehicles sold in the United States by September 2029. However, production implementations frequently rely on deterministic

Karim Gadelrab, Stefan Reimann-Zitz

Thin liquid films exhibit rich instability and rupture dynamics that critically impact coating performance across many applications. In this work, we use the lattice Boltzmann method (LBM) simulations within a lubrication-theory framework to systematically quantify how film thickness, surface energy, wettability, and intermolecular forces govern dewetting ki

By Riyadh Alrawkan, Edward Boone, Ryad Ghanam, Anton Westveld

Variable selection in linear regression models has been a problem since hypothesis testing began. Which variables to include or exclude from a model is not an easy task. Techniques such as Forward, Back ward, Stepwise Regression sequentially add or delete variables from a model. Penalized likelihood methods such as AIC, BIC, etc. seek to choose variables tha

Yang Shen, Yichen Fan, Weitao Yang

Recent advances in occupancy extrapolation (OE) show that potential of orbital-occupation based energy functions can describe electronic excitations. Here, the OE method in the particle-hole channel is extended to an effective quasiparticle Hamiltonian, enabling a multi-configurational description beyond single-determinant OE and $\Delta$SCF. The method perf

Avery W. Louis, Marina Dubova

Success-driven social learning, in which individuals preferentially adopt the ideas and methods that appear most successful, is a foundational principle of collective behavior across systems ranging from ant colonies to scientific communities. But science is a particular kind of collective search -- one in which the quality of an explanation is itself diffic

Murilo Cardoso, Bruno Ferman, Marcelo Fernandes

This paper studies the interactive fixed effects (IFE) estimator in a panel-data setting with heterogeneous treatment effects. We show that, if the treatment-effect heterogeneity admits a linear factor structure, the IFE estimator could fail to recover the average treatment effect on the treated units. The problem arises because the interactive fixed effects

Nilavra Pathak, Smriti Shyamal, Prasant Mhasker, Christopher Swartz

We study finite-horizon budget allocation as a closed-loop economic control problem and evaluate receding-horizon Model Predictive Control (MPC) relative to reactive budgeting policies. Budgets are allocated periodically under execution noise and operational constraints, while return efficiency may evolve over time. Using a controlled simulation framework mo

Guillaume Dideron, Suvodip Mukherjee, Luis Lehner

Gravitational Wave (GW) data bring an exceptional avenue to test the underlying models of coalescing compact objects. In the regime of strong gravity and high curvature, they allow the exploration of minute deviations from the best-fit models, which are difficult to uncover with other observational modalities. These deviations can stem from departures from G

Josh Cork, Derek Harland

Rotating calorons were introduced in the context of rotating quark-gluon plasmas. They are anti-self-dual gauge fields on $\mathbb{R}^4$ that are invariant under a glide rotation. We formulate a Nahm transform which identifies rotating calorons with solutions of a delayed-differential equation. Using this transform, we prove existence of an eight-parameter f

Jaden Hawley, Chi-Ren Shyu

As quantum computers continue to increase in size and topological complexity, benchmarking crosstalk becomes more complex and resource-intensive. This limits the ability to obtain relevant crosstalk metrics for applications such as error mitigation, quantum computer security, and circuit transpilation. There applications benefit from accessible metrics on ho

Ci Lin, Futong Li, Tet Yeap, Iluju Kiringa

Time-series data augmentation plays a crucial role in regression-oriented forecasting tasks, where limited data restricts the performance of deep learning models. While Generative Adversarial Networks (GANs) have shown promise in synthetic time-series generation, existing approaches primarily focus on matching marginal data distributions and often overlook t

Anna Kazakova

We prove the $\frac{2d}{d+1}$-Sidon inequality for a system of functions representing the most general extension of the Rademacher $d$-chaos to the $p$-ary case.

Duong Thuy Anh Nguyen, Harsha Nagarajan, Robert Ferrando, Russell Bent

This paper presents an optimal network topology control framework using cutting-plane methods for efficient network partitioning with controllable edges. The objective is to enable real-time reconfiguration of interconnected sub-networks while ensuring radial connectivity, resource feasibility, and structured leader allocation, which are essential for distri

Erik Faust, Lisa Scheunemann

In this article, we propose a simple and efficient hyperreduced strain-space model order reduction (MOR) approach for hyperelastic representative volume elements (RVEs), called Empirical Material Sampling and Linearisation (EMSL). The approach is conceptually motivated by the Empirically Corrected Cluster Cubature (E3C) of Wulfinghoff and Hauck [36], but als

Ashma Pandya, Swaroop Chandra, Michael E. Brown

The detection of CO2 on the Jovian satellite Europa by Galileo NIMS and recent mapping of the leading side by JWST has revealed that it is most concentrated in geologically young terrains, and its v3 asymmetric stretch appears as a spectral doublet centered at 4.25 and 4.27 um. Since crystalline CO2 is unstable at Europan surface conditions, this observation

Maksym Yu. Pyatnytskyy

We report the discovery of six new variable stars identified through an exploratory analysis of several sky fields observed by the author using a small telescope and a CMOS camera. The search employed simultaneous photometry of hundreds of objects with AstroImageJ, supplemented by custom Python-based tools developed by the author to generate aperture lists a

Zhongqi Wei, Frederike Dümbgen

Contact-rich manipulation is challenging due to its high dimensionality, the requirement for long time horizons, and the presence of hybrid contact dynamics. Sampling-based methods have become a popular approach for this class of problems, but without explicit mechanisms for global exploration, they are susceptible to converging to poor local minima. In this

Pavan Sollu, Aniruddha Mukherjee, Divya Pulivarthi, S. R. Eshwar

Hyperledger Fabric (HLF) is a modular, permissioned blockchain widely adopted in enterprise settings. Enhancing its throughput and latency remains challenging, as optimization decisions made in one phase of the transaction lifecycle can adversely affect other phases. In this work, we present a systematic, phase-level and end-to-end study of HLF optimizations

Sara Malacarne, Eirik Hoel-Høiseth, Erlend Aune, David Zsolt Biro

We propose C-MTAD-GAT, an \emph{unsupervised}, \emph{context-aware} graph-attention model for anomaly detection in multivariate time series from mobile networks. C-MTAD-GAT combines graph attention with lightweight context embeddings, and uses a deterministic reconstruction head and multi-step forecaster to produce anomaly scores. Detection thresholds are ca

Shamminuj Aktar, Reuben Tate, Stephan Eidenbenz

Trotterization is a standard approach for simulating quantum time evolution on quantum computers, where the Hamiltonian is split into local terms and each term is applied in sequence. The order of these terms affects the fidelity of the simulation when they do not commute, so the choice of ordering directly impacts the accuracy of the simulation. We study th

Austin C. Kozlowski, Andrei Boutyline

We show that the geometric relations between semantic features in large language models' hidden states closely mirror human psychological associations. We construct feature vectors corresponding to 360 words and project them on 32 semantic axes (e.g. beautiful-ugly, soft-hard), and find that these projections correlate highly with human ratings of those word

Leif Johnson, Trent Victor, Johan Engström

We present the Field of Safe Motion (FSM), a quantitative safety model for determining whether a driver maintains a collision-free escape route, or "out," at any given moment by accounting for that driver's physical capabilities and the foreseeable actions of other road users. The Field of Safe Travel (FST) provides a framework for representing the types of

Paraskevas V. Lekeas, Giorgos Stamatopoulos

LLM agents are known to deviate from Nash equilibria in strategic interactions, but nobody has looked inside the model to understand why, or asked whether the deviation can be reversed. We do both. Working with four open-source models (Llama-3 and Qwen2.5, 8B to 72B parameters) playing four canonical two-player games, we establish the behavioral picture thro

Mehryar Mohri, Jon Schneider, Yifan Wu

We focus on the problem of \emph{Answer-Level Fine-Tuning} (ALFT), where the goal is to optimize a language model based on the correctness or properties of its final answers, rather than the specific reasoning traces used to produce them. Directly optimizing answer-level objectives is computationally intractable due to the need to marginalize over the vast s

Victor M. Perez-Ramirez, Michelle M. Wang, Ke Ou, Sida Cao

The standard architecture for a high-peak-power femtosecond laser is chirped pulse amplification using diffraction gratings for compression; the damage threshold of the compression gratings limits current lasers to multi-petawatt peak power. Plasma gratings have orders-of-magnitude higher damage tolerance than conventional optics, so plasma gratings with suf

Miguel Tierz

We study the BPS cohomology and Hamiltonian of a model built from an $N\times N$ matrix $Ψ$ of complex fermions, with supercharge $Q_p={\rm Tr}(Ψ^p)$ for odd $p\ge3$. Numerical calculations give the BPS multiplicity at every fermion number for $(p,N)=(5,3),(5,4),(5,5),(7,4)$, and through fermion number six at $(7,5)$. In $Z_{BPS}^{(p,N)}(x)=\sum_Rh_Rx^R$, $x

Yasmine Fittouhi

Let $G = \mathrm{SL}(n,\mathbb{C})$, let $B$ be a fixed Borel subgroup, and let $P \supset B$ be a parabolic subgroup determined by a composition $(c_1,\dots,c_k)$ of $n$. Write $P'$ for the derived group of $P$ and $\mathfrak{m}$ for the Lie algebra of the nilradical of $P$. By Richardson's theorem the algebra of semi-invariants $\mathscr{I} := \mathbb{C}[\

Timothy Flavin, Sandip Sen

Reinforcement Learning (RL) algorithms exhibit high sample complexity, particularly when applied to Decentralized Partially Observable Markov Decision Processes (Dec-POMDPs). As a response, projects such as SampleFactory, EnvPool, Brax, and IsaacLab migrate parallel execution of classic environments such as MuJoCo and Atari into C++ thread pools or the GPU t

Annie Heinrich, Irina Zhuravleva, Eugene Churazov, Congyao Zhang

XRISM observations to date have shown that gas kinetic pressures in the intracluster medium (ICM) tend towards the low end of predictions from cosmological simulations. Here, we present a XRISM observation of the merging cluster Abell 2034, which exhibits the broadest emission lines yet observed in a galaxy cluster. We measure a velocity dispersion of ~470 k

Michael Gnewuch, Peter Kritzer, Klaus Ritter

We study embeddings between reproducing kernel Hilbert spaces $H(K)$ of functions of $d \in \mathbb{N} \cup \{\infty\}$ variables. The kernels $K$ are superpositions of weighted finite tensor products of a fixed univariate kernel. The basic idea for the embeddings is to compensate a change of the univariate kernel by a suitable transformation of the weights.

Ming-Yi Lin, Anne Medling, Richard Davies, Melanie Krips

We present Northern Extended Millimeter Array (NOEMA) observations of the CO (2-1) molecular gas kinematics in the nearby Compton-thick Seyfert 2 galaxy NGC 3079, with an angular resolution of 0.5" ($\sim$40 pc). To interpret the observed CO (2-1) kinematics, we model the rotating disk using two software tools, 3D-Barolo and DysmalPy, to generate mock 3D dat

Alexandra Junk, Josef M. Winter, Meike Tütken, Steffen Schmidt

We propose an accelerated computational fluid dynamics framework based on a hybrid Fourier Neural Operator-Lattice Boltzmann Method (FNO-LBM) for steady and unsteady weakly compressible flows. FNO-based initialization significantly accelerates LBM in reaching steady-states of porous media flows across all macroscopic fields, achieving up to 70% speed-up in c

Marco Cirant, Davide Francesco Redaelli

We study stochastic differential games with $N$ players, where interactions are determined by sequences of graphs in which the number of neighbours of each node remains bounded as $N$ grows, such as chain graphs or lattices. Our main goal is to quantify the phenomenon of the "unimportance of distant players" in such a large population, sparse regime: we show

Richard Booth, Ivan Varzinczak

Rational belief revision is commonly viewed as being based on a preference order between possible worlds, with the resulting new belief set being those sentences true in all the most preferred models of the incoming new information. Usually, such a preference order is taken to be a total preorder. Nevertheless, there are other, more general classes of orderi

Marvin F. da Silva, Mohammed Adnan, Felix Dangel, Sageev Oore

Model merging aims to combine multiple models into one without additional training. Na\"ive parameter-space averaging can be fragile under architectural symmetries, as their geometry does not take them into account. In this work we show that not only the geometry, but also the averaging procedure itself, must be symmetry-invariant to achieve symmetry-aware m

Nicholas Barnfield, James V. Burke, Michael P. Friedlander, Tim Hoheisel

We give a damped inexact Newton method for entropy-regularized least-squares on the nonnegative orthant that converges globally at a linear rate with $O(\log\epsilon^{-1})$ iteration complexity, locally at a superlinear-to-quadratic rate, and is immune to the finite-precision overflow that limits classical dual solvers. A scale-shape decomposition of the pri

Samuel Spell, Chi-Ren Shyu

While current network intrusion detection systems achieve satisfactory accuracy, they often lack explainability. Subgroup Discovery (SD) addresses this by building interpretable rules that characterize feature interactions associated with attack traffic. With large datasets, classical heuristic beam search methods struggle with exponentially scaling search s

S. I. Kruglov

Entropic cosmology with the R\'{e}nyi entropy of the apparent horizon $S_R=(1/\alpha)\ln(1+\alpha S_{BH})$, where $S_{BH}$ is the Bekenstein--Hawking entropy, is studied. By virtue of the thermodynamics-gravity correspondence a model of dark energy is investigated. The generalised Friedmann equations for the Friedmann--Lema\^{i}tre--Robertson--Walker spatial

Nate DeGoede, Maha N. Haji

Wave-driven desalination systems are an innovative solution to the global freshwater crisis, leveraging the complementary characteristics of seawater reverse osmosis and wave energy converters. However, the high costs of this system pose a significant barrier to widespread adoption. Optimization can help these systems reach a more competitive levelized cost

Jinbiao Wei, Kangqi Ni, Yilun Zhao, Guo Gan

Computer-use agents provide a promising path toward general software automation because they can interact directly with arbitrary graphical user interfaces instead of relying on brittle, application-specific integrations. Despite recent advances in benchmark performance, strong computer-use agents remain expensive and slow in practice, since most systems inv

Nathan Li, Aikins Laryea, Yigit Ihlamur

Autonomous crypto trading systems often spend most of their design effort on finding entries, while exits are left to fixed rules that are rarely tested in a systematic way. This paper examines whether better stop-loss and take-profit settings can improve the performance of an autonomous trading agent swarm. Using more than 900 historical trades, we replay e

Fatima Rabia Yapicioglu, Meltem Aksoy, Alberto Rigenti, Tuwe Löfström-Cavallin

Conformal Prediction provides distribution-free prediction intervals with guaranteed coverage, but its reliance on a single global calibration threshold obscures the sources of uncertainty at the instance level. In particular, it conflates irreducible noise with uncertainty induced by heterogeneous training data (aleatoric), model limitations, or calibration

Rabeya Khatun Muna, Md Nakhla Rafi, Tse-Hsun, Chen

Continuous Integration (CI) enforces repository-level correctness through multi-stage workflows and is central to modern software development, yet diagnosing and repairing CI failures remains challenging. Unlike traditional program repair, CI failures frequently involve non-code artifacts, environment and dependency issues, noisy execution logs, and workflow

Erik Mendoza, Horacio Navarro, Luciane Quoos

A recent construction of linear complementary pairs (LCPs) of algebraic geometry codes is intimately linked to the identification of non-special divisors of small degree within a function field over a finite field. Let $\mathbb{F}_q$ be the finite field of cardinality $q$. In this work, we consider a function field $F/\mathbb{F}_q$ of genus $g$ defined by a

D. Ramos, M. Caamano, F. Farget, C. Rodriguez-Tajes

Isotopic fission-fragment distributions of $^{240}$Pu have been measured, for the first time, as a function of the initial excitation energy, and the prompt neutron multiplicity has been derived from these data. The $^{240}$Pu fissioning system was produced through the two-proton transfer reaction between $^{238}$U and $^{12}$C, a surrogate reaction for the

Phong Dang, Daniel Langr, Tomas Dytrych, Jerry P. Draayer

We present quantitative evidence that high-quality internucleon forces derived from $\chi$EFT exhibit a striking dominance of Wigner's supermultiplet symmetry, without invoking the large-$N_c$ limit of QCD or assumptions about specific nuclei. We trace the manifestation of this symmetry in nuclear structure using the \textit{ab initio} Symmetry Adapted Model

Benjamin Probst, Andreas Happe, Jürgen Cito

Cloud-based Large Language Models (LLMs) can perform autonomous penetration-testing sub-tasks such as Linux privilege escalation, but raise security, privacy, and sovereignty concerns. Locally hosted open-weight models avoid these issues, yet prior work reports that small open-weight models succeed on only 8-16% of standardized privilege-escalation tasks, fa

Yael Kirkpatrick, Liam Roditty, Richard Qi, Virginia Vassilevska Williams

Computing the diameter of a graph is a problem of great interest both in general algorithms research and specifically within fine-grained complexity, where it is a cornerstone hard problem. Recent work has achieved a full conditional lower bound tradeoff curve for both directed and undirected graphs. However, the best known upper bounds do not match the lowe

Pasin Manurangsi

We study the Maximum Balanced Biclique (MBB) problem: Given a bipartite graph $G$ with $n$ vertices on each side, find a balanced biclique in $G$ with maximum size. We give a polynomial-time $\left(\frac{n}{\widetilde{\Omega}\left((\log n)^3\right)}\right)$-approximation algorithm for the problem, which improves upon an $\left(\frac{n}{\Omega\left((\log n)^2

SangHyun Park

We prove that the directed five-dimensional torus $D_5(m) = \operatorname{Cay}((\mathbb{Z}_m)^5, \{e_0, e_1, e_2, e_3, e_4\})$ has a Hamilton decomposition for every odd integer $m \geq 3$. This is the first higher-dimensional case in which the return-map method requires a genuine zero-set selector rather than an odometer-type correction. The construction as

Fekireselassie Beyene, Vassilis Angelopoulos, Christine Gabrielse, Yoshizumi Miyoshi

For the first time, this paper presents three very-near-Earth reconnection (VNERX) events observed within the same 12-hour-long storm main phase. The THEMIS inner probes observed the hallmarks of three episodes of tailward retreating x-lines positioned between magnetic local time (MLT) 23-24 and radial distance 12-13 Earth radii (RE). The events occurred wit

Khoirul Faiq Muzakka, Sören Möller, Martin Finsterbusch

This paper proposes RCMAES, a novel variant of the Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for CEC benchmark optimization. RCMAES integrates a dimension-dependent nonlinear population-size reduction strategy with an adaptive restart mechanism within a pure CMA-ES framework. RCMAES is evaluated on three benchmark suites (CEC2017, CEC2020, and

Camelia Baluta

This paper introduces a systematic evaluation framework grounded in the Interagency Language Roundtable (ILR) Skill Level Descriptions and applies it to Claude (Sonnet 4.6) across six languages: English, French, Romanian, Spanish, Italian, and German. We administer a battery of 12 semantically equivalent prompt clusters spanning ILR complexity levels 1 throu

Nicodemo Mazzaferro, Willmor J Pena Ccoa, Pilar Cossio, Glen M. Hocky

Several recent methods have shown that it is possible to compute rate constants of very slow biomolecular processes using simulations where a time-dependent bias is added along one or several collective variables (CVs). We previously reported the exponential average time-dependent rate (EATR) method, which can improve upon these approaches by accounting for

V. A. Penas, M. Losada, D. Tielas, F. Holik

Quantum state tomography provides a fundamental framework for reconstructing quantum states. When the measurement data are not informationally complete, the observed statistics admit multiple compatible density matrices, making the reconstruction problem inherently underdetermined and calling for the selection of a meaningful estimator. Two well-established

Will E. Thompson, Jennifer B. Bergner, Neal J. Evans, Yao-Lun Yang

Recent observations of protostars with the James Webb Space Telescope have revealed unprecedented chemical complexity from their ice absorption features. However, these spectra are likely influenced by radiative transfer effects, and there is little understanding of how this impacts our ability to identify, quantify, and interpret the observed ice features.

Yu-Chao Huang, Zhen Tan, Mohan Zhang, Pingzhi Li

Large Reasoning Models (LRMs) and Multi-Agent Systems (MAS) in high-stakes domains demand reliable verification, yet centralized approaches suffer four limitations: (1) Robustness, with single points of failure vulnerable to attacks and bias; (2) Scalability, as reasoning complexity creates bottlenecks; (3) Opacity, as hidden auditing erodes trust; and (4) P

Hangqi Zhao, Jay Li, Abhiruchi Bhattacharya, Cong Ni

Automatic detection of topical trends at scale is both challenging and essential for maintaining a dynamic content ecosystem on social media platforms. In this work, we present a large-scale system for identifying emerging topical trends on Snapchat, one of the world's largest short-video social platforms. Our system integrates multimodal topic extraction, t

Hai-Chau Nguyen, Gilberto Tetlalmatzi-Xolocotzi, Carmen Diez Pardos, Otfried Gühne

Entanglement, a fundamental phenomenon of quantum theory, has recently been observed in processes in high-energy physics. This opens new avenues for probing quantum effects in relativistic regimes, but also poses conceptual and technical challenges. We develop a general framework based on shadow tomography techniques for characterising spin-spin correlations

Jingchao Fang, Victoria Xiaohan Wen, Mina Lee

The growing capability of artificial intelligence (AI) leads to its increasing adoption in writing, spurring discussions around whether writers should disclose their AI use in writing. What influences the perceived necessity of disclosure? We look into this question from three dimensions: perspective (reader or writer of the text), purpose (the goal of readi

Sanjay Kumar Mohanty

The explainable artificial intelligence is used to analyze the stochastic Fredholm integral equations (SFIEs) and stochastic deep neural networks (SDNNs). The neural operator-based stochastic fixed point framework is used to develop SDNNs. The solution of an SFIE is obtained through successive applications of an integral operator, and this iterative structur

Hamdiya Adams, Theophilus Ansah-Narh, Daniel Kwadwo Asiedu, Bruce Kofi Banoeng-Yakubo

This study presents an unsupervised machine learning workflow for electrofacies analysis in the offshore Keta Basin, Ghana, where core data are scarce. Six standard wireline logs from Well~C were analysed over a depth interval comprising approximately $11{,}195$ samples. K-means clustering was applied in multivariate log space, with the clustering structure

Everett Fall, Hironori Kondo

We show that the operational quantum formalism -- the Born rule, L\"uders state updating, quantum interference, non-Markovian effective dynamics, and Bell inequality violation at the Tsirelson bound $2\sqrt{2}$ -- arises within Accessibility Theory (AT) from the Aperture construction together with explicit coherence and locality assumptions stated in the pap

Vijay Sadashivaiah, Georgios Dasoulas, Judith Mueller, Soumya Ghosh

Training stable biological foundation models requires rethinking attention mechanisms: we find that using sigmoid attention as a drop in replacement for softmax attention a) produces better learned representations: on six diverse single-cell datasets, sigmoid achieves 25% higher cell-type separation, better cell-type cohesion metrics, and lower validation lo