April 2026 arXiv papers — page 68

Bob Wilson

We consider minimax (saddle-point) problems of the form max_{c \in C} min_{\beta \in S} g(c; \beta), where C and S are compact convex sets, and g is concave-convex. Applying the Alternating Direction Method of Multipliers (ADMM) requires evaluating a proximal operator that is, in general, as hard as the original problem. We show that when the outcome functio

Sergei Igonin

Semi-discrete (differential-difference) matrix Lax representations (Lax pairs) play an essential role in the theory of integrable differential-difference equations. Fix a (1+1)-dimensional evolutionary differential-difference (semi-discrete) equation and consider matrix Lax representations (MLRs) of this equation. Two MLRs are said to be gauge equivalent if

Sarvesh K. Upadhyay, Trifce Sandev, Sanjay Kumar, R. K. Singh

We study exploration properties of a random walk on a network. For a fully connected network we find that the problem can be mapped to the well known coupon collector problem, thus allowing us to estimate form of $P(S,t)$: the distribution of number of distinct nodes $S$ visited by the random walk upto time $t$. From a practical point of view, however, both

Nitay Hurvitz, Alon Kochol, Victor Fleurov, Eran Sela

Measurement-induced phase transitions (MIPTs) in monitored quantum systems are typically diagnosed using entanglement-based measures. Here, we develop a complementary thermodynamic perspective based on the arrow of time (AoT), which arises from the intrinsic irreversibility of the quantum measurements driving these transitions. We study the AoT - defined as

Maja Gwozdz

Large-deviation upper bounds on compact sets do not, in general, extend to arbitrary closed sets without additional tightness. We show that this obstruction already occurs in static entropic optimal transport. More precisely, we construct a fixed-cost model with continuous cost and nonatomic marginals for which the entropic minimisers converge in total varia

Alexander Berladskyy, Andreas Aßmuth

Phishing attacks remain one of the most prevalent threats to online security, with the Anti-Phishing Working Group reporting over 890,000 attacks in Q3 2025 alone. Traditional password-based authentication is particularly vulnerable to such attacks, prompting the development of more secure alternatives. This paper examines passkeys, also known as FIDO2, whic

Sina Gholami, Abdulmoneam Ali, Tania Haghighi, Ahmed Arafa

Federated learning (FL) enables collaborative model training without sharing raw data; however, the presence of noisy labels across distributed clients can severely degrade the learning performance. In this paper, we propose FedSIR, a multi-stage framework for robust FL under noisy labels. Different from existing approaches that mainly rely on designing nois

Carl Angelo Angcana, Jamlech Iram Gojo Cruz

The internet folklore of the Cat Distribution System (CDS) humorously suggests that cats are "assigned" to people rather than intentionally sought. Beyond its playful origins, CDS reflects a culturally resonant way people perceive and engage in adoption, and this user context can guide the redesign and improvement of adoption systems. In the Philippines, whe

Prakul Sunil Hiremath, Vruksha Arun Hiremath

Limit order books can transition rapidly from stable to stressed conditions, yet standard early-warning signals such as order flow imbalance and short-term volatility are inherently reactive. We formalise this limitation via a three-regime causal data-generating process (stable $\to$ latent build-up $\to$ stress) in which a latent deterioration phase creates

Sachin Sarode, Chetan Patil, Vinayak Joshi

In this paper, we introduce $S$-prime elements in $V$-lattices, where $S$ is a multiplicatively closed subset of a $V$-lattice $L$. In addition, we introduce the $S$-Prime Element Principle to prove that certain elements in $V$-lattices are $S$-prime elements. This principle leads to a direct and uniform approach to the results on the existence of prime elem

Yiming Bian, Joshua M. Akey

Long-context large language models are limited not only by attention cost but also by out-of-memory (OOM) failures. A selected attention call may not fit in available device memory even when the kernel is optimized. Exact and approximate attention methods reduce memory use, but every fixed implementation still has a device-specific capacity boundary. We intr

Yannick de Bruijn, Erik Orvehed Hiltunen

Tridiagonal $k$-Toeplitz operators provide a natural framework for modelling one-dimensional $k$-periodic lattice systems. A fundamental connection is obtained between Coburn's lemma for tridiagonal $k$-Toeplitz operators and the existence of edge modes. We reveal that topological edge modes are characterised by the eigenvalues of the leading principal subma

Deqing Fu, Tianyi Zhou, Mikhail Belkin, Vatsal Sharan

Language models trained on natural text learn to represent numbers using periodic features with dominant periods at $T=2, 5, 10$. In this paper, we identify a two-tiered hierarchy of these features: while Transformers, Linear RNNs, LSTMs, and classical word embeddings trained in different ways all learn features that have period-$T$ spikes in the Fourier dom

Shelly Golan, Michael Finkelson, Ariel Bereslavsky, Yotam Nitzan

Reinforcement Learning (RL) post-training has become the standard for aligning generative models with human preferences, yet most methods rely on a single scalar reward. When multiple criteria matter, the prevailing practice of ``early scalarization'' collapses rewards into a fixed weighted sum. This commits the model to a single trade-off point at training

Ting-Wei Chao, Zichao Dong, Hong Liu, Xichao Shu

We study the Zarankiewicz problem for $r$-partite, $r$-uniform intersection hypergraphs arising from $r$ families of axis-parallel boxes in $\mathbb{R}^d$ with prescribed directions $F_1, \dots, F_r \subseteq \{1, \dots, d\}$. This extends the problems studied by Chan and Har-Peled on points and $d$-dimensional boxes in $\mathbb{R}^d$, corresponding to $(F_1

Ye Li

Fast radio bursts (FRBs) are millisecond-duration extragalactic radio transients of unknown origin. Rotation measures (RMs) probe their local magneto-ionic environments and provide important clues to their nature. While RM variability has been observed in several repeating FRBs, it is typically gradual or stochastic. Recently, observations of FRB~20220529 re

Yonatan Haile Medhanie, Yuanhua Ni

Transformer-based OCR models have shown strong performance on Latin and CJK scripts, but their application to African syllabic writing systems remains limited. We present the first adaptation of TrOCR for printed Tigrinya using the Ge'ez script. Starting from a pre-trained model, we extend the byte-level BPE tokenizer to cover 230 Ge'ez characters and introd

Jacob Brown

We develop a method for the rigorous estimation of Hausdorff dimensions of limit sets produced by continued fraction iterated function systems. Our method is based on the approximation of a Perron-Frobenius operator using the finite element method with B-splines as the choice of basis functions. This choice provides key numerical advantages including higher-

Hanqi Li, Lu Chen, Kai Yu

As LLMs are increasingly integrated into agentic systems, they must adhere to dynamically defined, machine-interpretable interfaces. We evaluate LLMs as in-context interpreters: given a novel context-free grammar, can LLMs generate syntactically valid, behaviorally functional, and semantically faithful outputs? We introduce RoboGrid, a framework that disenta

Truong Le Minh Toan, Dieu Bang Mach, Tan Duy Le, Nguyen Tan Viet Tuyen

Mental health challenges are rising globally, while traditional support services face limited availability and high costs. Large language models offer potential for conversational support, but often lack personalization, empathy, and factual grounding. A virtual agent framework is introduced to provide empathetic, personalized, and reliable wellbeing support

James L. Banal

Synthetic DNA approaches 227.5 exabytes per gram of storage density with stability over millennial timescales. Realising this capacity requires error-correction codes that recover data from substantial synthesis and sequencing errors. Existing codecs convert noisy sequencer output into discrete base calls before error correction, discarding probabilistic inf

William H. Kinney

The well-known Borde-Guth-Vilenkin Theorem shows that inflationary spacetimes are generically geodesically past-incomplete, necessitating the existence of a pre-inflationary boundary of some sort, possibly singular. I discuss the generalization of the BGV theorem to spacetimes beyond inflation, including inhomogeneous and cyclic models. As an example, I show

Steven Amelotte, Vladimir Gorchakov

We construct models for the classifying spaces of coabelian subgroups of right-angled Coxeter groups as homotopy orbit spaces of real moment-angle complexes, generalizing well-known models for the classifying space of a right-angled Coxeter group and its commutator subgroup. This identifies the cohomology of these groups with the Borel equivariant cohomology

Mohammad Abdulaziz, Thomas Ammer, Christoph Madlener

We present an ongoing effort to build a framework and a library in Isabelle/HOL for formalising primal-dual arguments for the analysis of algorithms. We discuss a number of example formalisations from the theory of matching algorithms, covering classical algorithms like the Hungarian Method, widely considered the first primal-dual algorithm, and modern algor

Qiguang Chen, Chengyu Luan, Jiajun Wu, Qiming Yu

Large vision-language models (LVLMs) have made substantial advances in reasoning tasks at the Olympiad level. Nevertheless, current Olympiad-level multimodal reasoning benchmarks for these models often emphasize single-image analysis and fail to exploit contextual information across multiple images. We present OMIBench, a benchmark designed to evaluate Olymp

Travis LaCroix

The value alignment problem for artificial intelligence (AI) is often framed as a purely technical or normative challenge, sometimes focused on hypothetical future systems. I argue that the problem is better understood as a structural question about governance: not whether an AI system is aligned in the abstract, but whether it is aligned enough, for whom, a

Ryo Sakai, Yu Yamashiro

We present a method for learning quantum hardware noise from a measurement distribution of a single device experiment. Each noise channel is represented by automatically differentiable Kraus operators obtained from a Stinespring-based parameterization that is completely positive and trace preserving by construction, and circuits are simulated with a matrix p

Andreas Metzger

Introductory Software Engineering (SE) courses face rapidly increasing student enrollment numbers, participants with diverse backgrounds and the influence of Generative AI (GenAI) solutions. High teacher-to-student ratios often challenge providing timely, high-quality, and personalized feedback a significant challenge for educators. To address these challeng

Rekha Jain, Akash Kumar, Sushanta C. Tripathy

The solar interior is probed by the properties of the Sun's acoustic oscillations (p-modes) observed on the solar surface. The frequencies of these p-modes measured in the last three decades show long term variation similar to the 11 year cyclic behaviour exhibited by 10.7 cm radio flux, sunspot numbers and other solar activity indices. It is also now establ

Sota Asai, Osamu Iyama, Kaveh Mousavand, Charles Paquette

For some important families of complete infinite lattices, we study some generalizations of two fundamental notions which are mostly treated for finite lattices. Specifically, for well-separated $\kappa$-lattices, and also for weakly atomic completely semidistributive lattices, we generalize the notions of left modularity and extremality. These two families

Hanzhi Liu, Chaofan Shou, Xiaonan Liu, Hongbo Wen

LLM agents have begun to find real security vulnerabilities that human auditors and automated fuzzers missed for decades, in source-available targets where the analyst can build and instrument the code. In practice the work is split among several agents, wired together by a harness: the program that fixes which roles exist, how they pass information, which t

Dimitrije Antić, Alvaro Budria, George Paschalidis, Sai Kumar Dwivedi

Reconstructing 3D Human-Object Interaction from an RGB image is essential for perceptive systems. Yet, this remains challenging as it requires capturing the subtle physical coupling between the body and objects. While current methods rely on sparse, binary contact cues, these fail to model the continuous proximity and dense spatial relationships that charact

Muzaffar Qureshi, Trivikram Satharasi, Tochukwu E. Ogri, Kyle Volle

This paper presents a framework for mapping unknown scalar fields using a sensor-equipped autonomous robot operating in unsafe environments. The unsafe regions are defined as regions of high-intensity, where the field value exceeds a predefined safety threshold. For safe and efficient mapping of the scalar field, the sensor-equipped robot must avoid high-int

Charles L. Epstein, Yoichiro Mori, Han Zhou

We study a bulk-surface coupled Laplace system involving an embedded open boundary. The problem is reformulated as an integro-differential equation using boundary integral representations, for which we establish existence and uniqueness of the solution. A Wiener-Hopf technique is employed to study the solution regularity and derive asymptotic expressions for

Ali Rayat, Yaohang Li, Gia-Wei Chern

Local gauge symmetry underlies fundamental interactions and strongly correlated quantum matter, yet existing machine-learning approaches lack a general, principled framework for learning under site-dependent symmetries, particularly for intrinsically nonlocal observables. Here we introduce a gauge-equivariant graph neural network that embeds non-Abelian symm

Inclusion AI, Tiwei Bie, Haoxing Chen, Tieyuan Chen

We present LLaDA2.0-Uni, a unified discrete diffusion large language model (dLLM) that supports multimodal understanding and generation within a natively integrated framework. Its architecture combines a fully semantic discrete tokenizer, a MoE-based dLLM backbone, and a diffusion decoder. By discretizing continuous visual inputs via SigLIP-VQ, the model ena

Pavel Salovskii, Iuliia Gorshkova

This paper presents a hybrid architecture for intelligent systems in which large language models (LLMs) are extended with an external ontological memory layer. Instead of relying solely on parametric knowledge and vector-based retrieval (RAG), the proposed approach constructs and maintains a structured knowledge graph using RDF/OWL representations, enabling

Luca Fanelli, Yilin Song, Ying Wang, Jiqiang Zheng

In this paper, we study Hardy-type uncertainty principles and unique continuation properties for linear covariant Schrodinger equations with variable coefficients in the presence of bounded electric and magnetic potentials. Under suitable smallness assumptions on the leading coefficients, we prove that any solution exhibiting super-quadratic exponential deca

Ray Iskander, Khaled Kirah

Post-quantum cryptographic (PQC) accelerators for ML-KEM (FIPS 203) and ML-DSA (FIPS 204) rely on pipelined Number Theoretic Transform (NTT) stages over $\mathbb{Z}_q$. Our prior work established structural dependency analysis at scale [1] and quantified the security margin of partial NTT masking [2]. Whether per-stage arithmetic masking guarantees pipeline-

Mariano Barone, Francesco Di Serio, Roberto Moio, Marco Postiglione

Large Language Models (LLMs) are increasingly deployed in healthcare, yet their communicative alignment with clinical standards remains insufficiently quantified. We conduct a multidimensional evaluation of general-purpose and domain-specialized LLMs across structured medical explanations and real-world physician-patient interactions, analyzing semantic fide

O. Yu. Kitsenko, S. N. Shevchenko, L. Peri, Franco Nori

When a quantum electronic device is coupled to an electrical resonator, admittance changes of the quantum subsystem may be detected. The effective reactance may include capacitive and inductive terms that incorporate geometric, quantum, and tunneling components; while the effective resistance may be composed of Sisyphus and Hermes terms linked to relaxation

Pranava Madhyastha, Dagmar Adamcova

We investigate the integration of human-like working memory constraints into the Transformer architecture and implement several cognitively inspired attention variants, including fixed-width windows based and temporal decay based attention mechanisms. Our modified GPT-2 models are trained from scratch on developmentally plausible datasets (10M and 100M words

Nick W. Koning

We introduce the E-measure: a measure-like generalization of the E-value to a class of hypotheses. Unlike classical measures, E-measures are closed under infimums instead of addition. They arise from a compatibility axiom with logical implications, that there should be at least as much evidence against more specific hypotheses. We show that E-measures are th

Revathy S. Nair, Bijo S. Anand, Julliano R. Nascimento

Given a graph $G$, a subset $S \subseteq V(G)$ is \textit{cycle convex}, if for any vertex $v \in V(G) \setminus S$, the induced subgraph, $G[S \cup \{v\}]$ cannot form a cycle containing the vertex $v$. The \textit{exchange number} of $G$, denoted by $e_{cc}(G)$ is the maximum cardinality of an $\textit{$E$-independent}$ set of $G$. This paper studies the c

Leon Kellerhals, Mitja Krebs, André Nichterlein, Stefan Schmid

We study the following problem that is motivated by demand-aware network design: Given a tree~$G$, the task is to find a binary tree~$H$ on the same vertex set. The objective is to minimize the sum of distances in~$H$ between vertex pairs that are adjacent in~$G$. We present a linear-time factor-4 approximation for this problem.

Brian Sun

Let $Y_-$ and $Y_+$ be two compact 3-manifolds with empty or toroidal boundary. A 4-dimensional ribbon homology cobordism is a homologically trivial cobordism built with 1-handles and 2-handles. In this note, following the work of Friedl and collaborators, we apply twisted Alexander polynomials to show that the fibered classes of $Y_+$ map to those of $Y_-$.

Zhenlong Wu, Zihan Zheng, Xuanxuan Wang, Lei Huang

Reconstructing dynamic 3D scenes from sparse multi-view videos is highly ill-posed, often leading to geometric collapse, trajectory drift, and floating artifacts. Recent attempts introduce generative priors to hallucinate missing content, yet naive integration frequently causes structural drift and temporal inconsistency due to the mismatch between stochasti

Zesheng Liu, Maryam Rahnemoonfar

Internal ice layers imaged by radar provide key evidence of snow accumulation and ice dynamics, but radar-derived layer boundary observations are often incomplete, with discontinuous traces and sometimes entirely missing layers, due to limited resolution, sensor noise, and signal loss. Existing graph-based models for ice stratigraphy generally assume suffici

Sayak Guin, Swagatam Tah, Nihar Ranjan Sahoo, Sayantan Sharma

Discovery of instantons in colliders will provide experimental evidence for the topological properties of the QCD vacuum. In this work, we propose jet correlation observables that can unambiguously discriminate between instanton-induced processes and perturbative hard scattering events in $pp$ collisions at the LHC for a specific range of center-of-mass ener

Joachim Baumann, Vishakh Padmakumar, Xiang Li, John Yang

AI coding agents are being adopted at scale, yet we lack empirical evidence on how people actually use them and how much of their output is useful in practice. We present SWE-chat, the first large-scale dataset of real coding agent sessions collected from open-source developers in the wild. The dataset currently contains 6,000 sessions, comprising more than

Mattias Ehatamm, Peter Nelson, Fernanda Rivera Omana

We generalize the well-studied notion of a modular pair of a finite matroid to arbitrary families of sets in infinite matroids, and use it to develop the theory of infinite matroids in several as-yet-unexplored areas. Our results include a complete theory of single-element extensions, a description of the relationship between quotients and projections, a pro

Dario Simionato, Andrea Tonon, Mingxue Wang, Weiguo Wang

In streaming platforms churn is extremely costly, yet A/B tests are typically evaluated using outcomes observed within a limited experimental horizon. Even when both short- and predicted long-term engagement metrics are considered, they may fail to capture how a treatment affects users' retention. Consequently, an intervention may appear beneficial in the sh

Chao Wang, Luca Nepote, Giulio Franzese, Pietro Michiardi

Trajectory Inference (TI) seeks to recover latent dynamical processes from snapshot data, where only independent samples from time-indexed marginals are observed. In applications such as single-cell genomics, destructive measurements make path-space laws non-identifiable from finitely many marginals, leaving held-out marginal prediction as the dominant but l

Jong Ha Woo, Qi Xiao, Yu Ma, Zishuo Yang

The large-scale integration of inverter-based resources (IBRs), particularly distributed photovoltaics (DPVs), into distribution networks increases the need for integrated transmission and distribution (T&D) co-simulation. A key challenge in such co-simulation lies in accurately modeling system frequency across two asynchronous simulation environments. For e

Adam Shaw

This thesis studies general relativity (GR) using chiral formulations, which take advantage of the decomposition of the four-dimensional Lorentz group into self-dual and anti-self-dual sectors. Within this framework, GR can be expressed using Plebanski's formulation, where the basic variables are triples of 2-forms rather than a metric, or alternatively thro

Shahid Alam, Amina Jameel, Zahida Parveen, Ehab Alnfrawy

The Internet of Vehicles (IoV) is advancing modern transportation by improving safety, efficiency, and intelligence. However, the reliance on the Controller Area Network (CAN) introduces critical security risks, as CAN-based communication is highly vulnerable to cyberattacks. Addressing this challenge, we propose DAIRE (Detecting Attacks in IoV in REal-time)

Cristian D. Suarez-Jimenez, Alejandro P. Riascos, Denis Boyer

In this work, we study the dynamics of multiple random walkers on networks subject to a simultaneous resetting protocol, whereby all walkers are synchronously returned to their respective initial nodes. For this collective Markovian process, we derive exact analytical expressions for the mean first-encounter time, defined as the average time required for all

A. V. Guglielmi, A. S. Potapov, F. Z. Feygin

It has been 90 years since the discovery of geomagnetic pulsations in the Pc1 range (0.2-5 Hz), widely known as pearls. In the second half of the last century, the concept of pearls as multiple echoes of a wave packet that propagates along the lines of the geomagnetic field, periodically reflecting off the ionosphere at magnetically conjugate points emerged.

Pankaj Borah, P. S. Bhupal Dev, Anish Ghoshal

Sufficiently strong first-order phase transitions (FOPTs) in the early Universe can simultaneously produce an observable stochastic gravitational wave background (SGWB) and a large-scale primordial magnetic field (PMF). The recent $3.8σ$ evidence for a non-zero intergalactic magnetic field from anisotropic pair-halo searches using \textit{Fermi}-LAT data fur

Soham Sen, Sunandan Gangopadhyay, Vlatko Vedral

The eigenstates of two test-masses (where each test-mass is placed inside of a harmonic trap) separated by a distance, can get entangled where gravity acts as the mediator of entanglement and it has been argued in \href{https://doi.org/10.48550/arXiv.2511.07348}{arXiv:2511.07348 [quant-ph]} that this entanglement of masses cannot be generated without the und

Krishiv Agarwal, Ramneet Kaur, Colin Samplawski, Manoj Acharya

Effective safety auditing of large language models (LLMs) demands tools that go beyond black-box probing and systematically uncover vulnerabilities rooted in model internals. We present a comprehensive, interpretability-driven jailbreaking audit of eight SOTA open-source LLMs: Llama-3.1-8B, Llama-3.3-70B-4bt, GPT-oss- 20B, GPT-oss-120B, Qwen3-0.6B, Qwen3-32B

Dean Muir, Kenneth Duru, Stuart Hudson, Matthew Hole

We present a robust and accurate numerical method for the anisotropic diffusion equation in curvilinear coordinates. This study extends the recent work [Muir et al., Computer Physics Communications, 2025] for solving the anisotropic diffusion equation in magnetic fields from Cartesian meshes to to curvilinear coordinates and complex geometries. The method us

Lena Sinterhauf, Andreas Aßmuth, Roland Kaltefleiter

Critical vulnerabilities with Common Vulnerability Scoring System scores of 9.0 or higher pose severe risks to organisations' information systems. Timely detection and remediation are essential to minimise economic and reputational damage from cyberattacks. This paper provides a thorough analysis of the identification and resolution timelines of such critica

Sreechakra Vasudeva Raju Rachavelpula, Sangwhan Cha

This paper presents a personalized Battery Electric Vehicle (BEV) energy consumption estimation framework that integrates map-based contextual features with driver-specific velocity prediction and physics-based energy consumption modeling. The system combines route selection, detailed road feature processing, a rule-based reference velocity generator, a PID

Andrew Klearman, Radu Revutchi, Rohin Garg, Rishav Chakravarti

Retrieval quality is the primary bottleneck for accuracy and robustness in retrieval-augmented generation (RAG). Current evaluation relies on heuristically constructed query sets, which introduce a hidden intrinsic bias. We formalize retrieval evaluation as a statistical estimation problem, showing that metric reliability is fundamentally limited by the eval

Miguel Vanvlasselaer, Wen Yin

We propose a baryogenesis mechanism in which an electroweak phase boundary is induced by a wall-like configuration of a scalar field, such as a domain wall or a shock wave, coupled to the Higgs field. If the Higgs mass parameter depends on the scalar field value, the wall locally separates the electroweak-symmetric and broken phases, thereby providing an ind

Xiaotian Chang, Yangdi Jiang, Cyrus Mostajeran, Qirui Hu

In this paper, we develop a novel privacy mechanism for Riemannian manifold-valued data. Our key contribution lies in uncovering unexpected connections among geometric analysis, heat diffusion models, and differential privacy (DP). We characterize the Renyi divergence via dimension-free Harnack inequalities on Riemannian manifolds and establish Renyi differe

Manjin Kim, Heeseung Kwon, Karteek Alahari, Minsu Cho

Space-time self-similarity (STSS), which captures visual correspondences across frames, provides an effective way to represent temporal dynamics for video understanding. In this work, we explore higher-order STSS and demonstrate how STSSs at different orders reveal distinct aspects of these dynamics. We then introduce the Multi-Order Self-Similarity (MOSS) m

Lucas Alexandre, João Rulff, Talisson Souza, Gustavo Moreira

The development of visual analytics (VA) systems has traditionally been a labor-intensive process, balancing design methodologies with complex software engineering practices. In domain-specific fields like urban VA, this challenge is amplified by heterogeneous data streams and a reliance on complex, multi-service architectures that hinder fast development, d

Javier Jiménez-Garrido, Ignacio Miguel-Cantero, Javier Sanz, Gerhard Schindl

We study the stability under point-wise product and under composition in Carleman classes of holomorphic functions, defined on sectors of the Riemann surface of the logarithm, and admitting a uniform asymptotic expansion with remainders controlled by a given sequence of positive real numbers $\mathbf{M}$. On the one hand, the well-known conditions of algebra

Klaus Jäger, Jyotirmoy Mandal, Barry P. Rand, Forrest Meggers

Sub-bandgap reflectors (SBR) can reduce the temperature of photovoltaic (PV) modules by reflecting the near-infrared region of the solar spectrum with photon energies smaller than the electronic bandgap of the solar cell absorber material. We consider an ideal SBR, which reflects 100 % of non-harvestable low-energy photons but does not alter the reflectivity

Martti Karvonen

The main claim of Baumeler et al. (Proc. R. Soc. A 481, 20240601; arXiv:2206.08467) is that "functional (deterministic) no-signalling resources can be stronger than probabilistic ones" in a certain nonlocal game on a Bell scenario with countably many parties. We disagree and argue that (i) under standard definitions, deterministic no-signalling resou

Yubo Jiang, Yitong An, Xin Yang, Abudukelimu Wuerkaixi

We introduce V-tableR1, a process-supervised reinforcement learning framework that elicits rigorous, verifiable reasoning from multimodal large language models (MLLMs). Current MLLMs trained solely on final outcomes often treat visual reasoning as a black box, relying on superficial pattern matching rather than performing rigorous multi-step inference. While

Gelin Chen, Chen Song, Chao Yang

Self-excited limit-cycle oscillations (LCOs) from Hopf bifurcations are a key feature of nonlinear aeroelasticity and depend sensitively on structural and aerodynamic parameters. Classical center-manifold and normal-form theory describe this local behavior, but can be cumbersome to apply in large discretized models and standard reduced-order modeling (ROM) w

Csilla Bujtas, Magda Dettlaff, Hanna Furmanczyk, Aleksandra Laskowska

Inspired by the majority colorings and C-colorings, we introduce and study the majority C-coloring of graphs. In such a vertex coloring, every vertex shares its color with at least half of its neighbors. The maximum number of colors that can be used in a majority C-coloring of a graph $G$ is called the majority C-chromatic number and denoted by $\mc(G)$. An

Gang Chen, Yangwen Zhang, Dujin Zuo

We study mixed finite element/Crank--Nicolson discretizations of a nonlinear Oldroyd problem with general nonsingular and weakly singular memory kernels. Direct evaluation of the history term requires storing all previous velocity snapshots, which leads to $\mathcal{O}(mN)$ memory and $\mathcal{O}(mN^2)$ work over $N$ time steps, where $m$ denotes the number

Thomas Creutzig, Volodymyr Kovalchuk, Andrew R. Linshaw, Arim Song

The universal $2$-parameter vertex algebra $\mathcal{W}_{\infty}$ of type $\mathcal{W}(2,3,\dots)$ is a classifying object for vertex algebras of type $\mathcal{W}(2,3,\dots,N)$ for some $N$; under mild hypotheses, all such vertex algebras arise as quotients of $\mathcal{W}_{\infty}$. In 2017, Gaiotto and Rapčák introduced a family of such vertex algebras ca

Dongding Lin, Jian Wang, Yongqi Li, Wenjie Li

Situated conversational recommendation (SCR), which utilizes visual scenes grounded in specific environments and natural language dialogue to deliver contextually appropriate recommendations, has emerged as a promising research direction due to its close alignment with real-world scenarios. Compared to traditional recommendations, SCR requires a deeper under

Bo Zhang, Zhuotao Tian, Xin Tao, Songlin Tang

Amodal segmentation is a challenging task that aims to predict the complete geometric shape of objects, including their occluded regions. Although existing methods primarily focus on amodal segmentation within the training domain, these approaches often lack the generalization capacity to extend effectively to novel object categories and unseen contexts. Thi

Petr Harmanec, Stephenson Yang, Miroslav Slechta, Erika D. Grundstrom

Analysis of radial velocities of two narrow absorption components in the Mg II 4481 A line demonstrated that the secondary of the Be star omicron Cas is indeed a close binary system composed of two B7 stars orbiting each other with a period of 11.6604 days. Orbital solutions and spectral disentangling lead to consistent system properties. The system is extre

Tatsuro Banno, Koki Kawada, Mizuki Takenawa, Masatoshi Denda

Virtual flood experience systems, which enable users to vividly experience flooding, are attracting increasing attention as effective tools for communicating flood risks. However, existing systems typically rely on virtual cities that do not correspond to real locations and often lack sufficient photorealism, limiting users' ability to relate scenarios to th

Beining Wu, Jun Huang

Federated continual learning (FCL) allows distributed autonomous fleets to adapt collaboratively to evolving terrain types across extended mission lifecycles. However, current approaches face several key challenges: 1) they use uniform protection strategies that do not account for the varying sensitivities to forgetting on different network layers; 2) they f

Jonathan Washburn, Megan Simons, Elshad Allahyarov

We introduce a single dimensionless landscape function $J_{\rm chem}(\rho) = \cosh(\rho \ln \varphi) - 1$, $\varphi = (1+\sqrt{5})/2$, on the noble-gas-centred coordinate $\rho = d/L_p \in [0,1)$, and show that it organizes four central atomic observables: first ionization energy \IE$_1$, electron affinity EA, Mulliken electronegativity $\chi_M$, and Pearson

An T. Le, Vien Ngo

We introduce \textbf{AAC} (Architecturally Admissible Compressor), a differentiable landmark-selection module for ALT (A*, Landmarks, and Triangle inequality) shortest-path heuristics whose outputs are admissible by construction: each forward pass is a row-stochastic mixture of triangle-inequality lower bounds, so the heuristic is admissible for \emph{every}

Matteo Amestoy, Mark A. van de Wiel, Wessel N. van Wieringen

ProfileGLMM is an R package integrating Generalised Linear Mixed Models (GLMMs) as the outcome model for Bayesian profile regression. This statistical framework simultaneously i) explains the variation in the outcome and ii) clusters the observations based on a specified set of interdependent clustering covariates. The derived cluster memberships are then in

Luigi Lavazza, Gabriele Rotoloni, Sandro Morasca

Background: Receiver Operating Characteristic (ROC) curves are widely used to evaluate the performance of Software Defect Prediction (SDP) models that estimate module fault-proneness, i.e., the probability that a module is faulty. A ROC curve maps a model's performance in terms of True Positive Rate and False Positive Rate for any possible threshold set on f

Francis Brown

We establish a higher-dimensional irrationality criterion for periods which are presented as Mellin integrals depending on many parameters. The criterion is stated as an upper bound on the multi-variate transfinite diameter of the image of the domain of integration under the Mellin arguments. Most of the paper is devoted to studying notions of transfinite di

Casey Crane

We study the emergence of symmetric oscillatory behavior in multi-agent systems where each agent incorporates a continuous memory of its past states and past rates of change, modeled by distributed retarded and neutral delays. The closed-loop dynamics are described by a system of nonlinear neutral functional differential equations (NFDEs) with a high degree

Pawel Goclowski, Hong Mao, Maciek Trusiak, Balpreet S. Ahluwalia

In this letter, a high-fidelity single-shot differential quantitative phase microscopy (dQPM) method is presented to effectively image nearly transparent biological samples. The proposed method is based on a common-path Sagnac interferometric configuration, which provides superior temporal phase stability and robustness against environmental disturbances. Th

Marisa Hudspeth, Patrick J. Burns, Brendan O'Connor

We introduce a benchmark dataset for question answering and translation in bilingual Latin and English settings, containing about 7,800 question-answer pairs. The questions are drawn from Latin pedagogical sources, including exams, quizbowl-style trivia, and textbooks ranging from the 1800s to the present. After automated extraction, cleaning, and manual rev

Jinliang Xu

The rapid collapse of decentralized game economies, often characterized by the \textit{death spiral,} remains the most formidable barrier to the mass adoption of Web3 gaming. This paper proposes that the sustainability of an open game economy is predicated on three necessary and sufficient conditions: Anti-Sybil Resilience, Anti-Capital Dominance, and Anti-I

Yutong Shen, Ruizhe Xia, Jingyi Liu, Yinqi Liu

Semi-supervised node classification is a foundational task in graph machine learning, yet state-of-the-art Graph Neural Networks (GNNs) are hindered by significant computational overhead and reliance on strong homophily assumptions. Traditional GNNs require expensive iterative training and multi-layer message passing, while existing training-free methods, su

Peter Collett, Alexander Johannes Stasik, Simone Casolo, Signe Riemer-Sørensen

Accurate condition monitoring of industrial equipment requires inferring latent degradation parameters from indirect sensor measurements under uncertainty. While traditional Bayesian methods like Markov Chain Monte Carlo (MCMC) provide rigorous uncertainty quantification, their heavy computational bottlenecks render them impractical for real-time process con

Mehran Dehpour

Axion-Like Particles (ALPs) are well-motivated candidates for dark matter and potential mediators to the dark sector. We present a search for ALPs coupled to photons, based on a reinterpretation of COMPASS data. Using the 2009 dataset consisting of $190~\text{GeV}$ $π^-$ and $μ^-$ beams impinging on a fixed nickel target, we investigate the Primakoff product

Chuanyu Qin, Chenxu Yang, Qingyi Si, Naibin Gu

Reinforcement learning with verifiable rewards (RLVR) has become a core post-training recipe. Introducing suitable off-policy trajectories into on-policy exploration accelerates RLVR convergence and raises the performance ceiling, yet finding a source of such trajectories remains the key challenge. Existing mixed-policy methods either import trajectories fro

Hoang Nguyen, Lu Wang, Marta Gaia Bras

Freight brokerages negotiate thousands of carrier rates daily under dynamic pricing conditions where models frequently revise targets mid-conversation. Classical time-dependent concession frameworks use a fixed shape parameter $\beta$ that cannot adapt to these updates. Deriving $\beta$ from the live spread enables adaptation but introduces a new problem: a

Askold Vilkha, Tomasz Służalec, Marcin Łoś, Maciej Paszyński

This paper presents the hybrid solver for a $CO_2$ sequestration problem. The solver uses the IGA-ADS (IsoGeometric Analysis Alternating Directions solver) to compute the saturation scalar field update using the explicit method, and CRVPINN (Collocation-based Robust Variational Physics Informed Neural Networks solver) to compute the pressure scalar field. Th

Cicero Carvalho, Maria Vaz Pinto, Rafael H. Villarreal

Let $X$ be a projective nested product of fields and let $\delta_X(d)$ be the minimum distance in degree $d\geq 1$ of the projective nested Cartesian code $C_X(d)$. The regularity index ${\rm reg}(\delta_X)$ of the minimum distance function $\delta_X$ is the minimum integer $d_0\geq 0$ such that $\delta_X(d)=1$ for $d\geq d_0$. We give a formula for ${\rm re

William Scarbro, Ravi Mangal

Autonomous systems that rely on learned perception can make unsafe decisions when sensor readings are misclassified. We study shielding for this setting: given a proposed action, a shield blocks actions that could violate safety. We consider the common case where system dynamics are known but perception uncertainty must be estimated from finite labeled data.

Young Min Cho, Daniele Bonadiman, Divya Bhargavi, Tamer Alkhouli

Training large foundation models for agentic tasks is increasingly impractical due to the high computational costs, long iteration cycles, and rapid obsolescence as new models are continuously released. Instead of post-training massive models for every new task or domain, we propose Supplement Generation Training (SGT), a more efficient and sustainable strat