April 2026 arXiv papers — page 5

Mesfin Taye

Primates exhibit a robust deviation from canonical allometric scaling: at fixed body mass, their lifespans exceed those of non-primate mammals by factors of two to three. A rhesus macaque (8 kg) lives 25-40 years, whereas a cat of similar mass rarely exceeds 18 years. This statistically significant clade-level excess cannot be explained by standard metabolic

Eklavya Sarkar, Marius Miron, David Robinson, Gagan Narula

Animals hear and vocalize across frequency ranges that differ substantially from humans, often extending into the ultrasonic domain. Yet most computational bioacoustics systems rely on audio models pre-trained at 16 kHz, restricting their usable bandwidth to the 0-8 kHz baseband and discarding higher-frequency information present in many bioacoustic recordin

Kaleem Arshid, Ali Krayani, Lucio Marcenaro, David Martin Gomez

This paper presents an expert-guided active-inference-inspired framework for adaptive UAV swarm trajectory planning. The proposed method converts multi-UAV trajectory design from a repeated combinatorial optimization problem into a hierarchical probabilistic inference problem. In the offline phase, a genetic-algorithm planner with repulsive-force collision a

Weihai Lu, Zhejun Zhao, Yanshu Li, Huan He

Multimodal Stance Detection (MSD) is crucial for understanding public discourse, yet effectively fusing text and image, especially with conflicting signals, remains challenging. Existing methods often face difficulties with contextual grounding, cross-modal interpretation ambiguity, and single-pass reasoning fragility. To address these, we propose Retrieval-

Martin Schottlender, Pengjie Zhou, Veronika Volkova, Fatima Rani

Concurrent advances across fields such as organoid technology, Microelectrode Arrays (MEAs), neuromorphic computing, and machine learning have given rise to a groundbreaking research paradigm: Synthetic Biological Intelligence (SBI). SBI refers to engineered systems in which living Biological Neural Networks (BNNs) are interfaced with hardware and software t

Joydwip Singh

In this paper, we study the $L^p$-boundedness of Stein's square function $\mathfrak{S}^{\alpha}(\mathcal{L})$ associated with the sub-Laplacian $\mathcal{L}$ on M\'etivier group $G$. A key aspect of our result is that the smoothness condition is expressed in terms of the topological dimension $d$ of the underlying M\'etivier group $G$. Consequently, we also

Yeonsu Jeong, Deok-Sun Lee, Mi Jin Lee, Seung-Woo Son

In heterogeneous network systems such as ecological and social networks, structural stability depends on how connectivity changes under node removal, as different removal sequences can trigger distinct modes of systemic collapse. While robustness to random failures and targeted attacks has been extensively studied, most analyses have focused on connectivity

Lifan Zheng, Xue Yang, Jiawei Chen, Chenyan Wu

With the widespread adoption of large language models (LLMs), understanding their personality representation mechanisms has become critical. As a novel paradigm in Personality Editing, most existing methods employ neuron-editing to locate and modify LLM neurons, requiring changes to numerous neurons and leading to significant performance degradation. This ra

Shipeng Liu, Liang Zhao, Dengfeng Chen, Zhanping Song

Tunnel inspection requires outputs that can support defect localization, measurement, severity grading, and engineering documentation. Existing training-free foundation-model pipelines usually stop at coarse open-vocabulary proposals, which are difficult to use directly in interference-heavy tunnel scenes. We propose a training-free framework TunnelMIND. Spe

Matteo Da Pelo, Alessio Donvito, Claudio Frongia, Pietro Salis

We introduce a framework called LAPITHS (Language model Analysis through Paradigm grounded Interpretations of Theses about Human likenesS) and use it to show that several major claims advanced by models such as CENTAUR, proposed as an artificial Unified Model of Cognition, are not theoretically or empirically justified. LAPITHS provides a principled referenc

Nell Hartney, Thomas M. Bendall, Jemma Shipton

One of the key choices for numerical models of geophysical fluids is how parametrisations of physical processes interact with the numerical methods that handle the resolved flow, known in the atmospheric community as the dynamical core. As both the dynamical core and parametrisations of physics processes continue to evolve and improve, the issue of physics-d

Xingjian Lu, Shuzhe Shi

A thermal spectrum is often taken as a signature that the emitted probe has reached detailed balance with the surrounding medium. We show that this interpretation is not generally valid by studying how the microscopic emission kernel determines the macroscopic spectrum. In $3+1$ dimensions, a simple thermal spectrum can be generated without probe thermalizat

Geza Kovacs

We present a highly simplified nonlinear hydrodynamical model to emulate the main observed features of amplitude modulation (commonly known as Blazhko effect) in RR Lyrae stars. The model is based on the assumption that the periodic flow generated by the pulsation carries surplus helium in the ionization zones He I and II. Once this extra helium reaches a cr

Sihong Wu, Owen Jiang, Yilun Zhao, Tiansheng Hu

Peer review is a multi-stage process involving reviews, rebuttals, meta-reviews, final decisions, and subsequent manuscript revisions. Recent advances in large language models (LLMs) have motivated methods that assist or automate different stages of this pipeline. In this survey, we synthesize techniques for (i) peer review generation, including fine-tuning

Rufat Badal, Manuel Friedrich, Martin Horák, Martin Kružík

We consider a quasi-static nonlinear model in thermoviscoelasticity at a finite-strain setting in the Kelvin-Voigt rheology where both the elastic and viscous stress tensors comply with the principle of frame indifference under rotations. We refine the discretization schemes in [Badal-Friedrich-Kru\v{z}\'ik '23, Mielke-Roub\'{\i}\v{c}ek '20] by imposing fram

Armin Gießler, Felix Thömmes, Sören Hohmann

This paper studies data-driven approaches to the continuous-time linear quadratic regulator (LQR) problem based on two existing parameterizations, namely a closed-loop (CL) parameterization from behavioral system theory and an integral reinforcement learning (IRL) parameterization. The CL parameterization characterizes the closed-loop system via a matrix tha

Rohan Bansal, Jessica Striker

Magog matrices, introduced by Holmlund and Striker in 2025, provide a matrix model for totally symmetric self-complementary plane partitions (TSSCPPs), as a natural analogue of alternating sign matrices (ASMs). In this paper, we develop several new combinatorial representations of magog matrices, mirroring classical representations of ASMs. Specifically, we

Dawid Wisniewski, Igor Czudy

Preserving affective nuance remains a challenge in Machine Translation (MT), where semantic equivalence often takes precedence over emotional fidelity. This paper evaluates the performance of three state-of-the-art Small Language Models (SLMs) -- EuroLLM, Aya Expanse, and Gemma -- in maintaining fine-grained emotions during backtranslation. Using the GoEmoti

Aijin Lin, Qingyi Liu

The Circle Pattern Theorem characterizes the existence and rigidity of circle patterns with prescribed intersection angles on simplicial triangulations of closed surfaces. In this paper we extend the theorem to quasi-simplicial triangulations -- triangulations that may contain loops and multiple edges, but whose lifts to the universal cover are simplicial. C

Zujin Guo, Zhenhui Ye, Yi Ren, Yuanming Li

Existing talking avatar methods typically adopt an image-to-video pipeline conditioned on a static reference image within the same scene as the target generation. This restricted, single-view perspective lacks sufficient temporal and expression cues, limiting the ability to synthesize high-fidelity talking avatars in customized backgrounds. To this end, we i

Shanxia Wang

Coalition Logic is primarily concerned with what coalitions can achieve, whereas what coalitions cannot achieve -- their \emph{inability} -- has received comparatively little explicit attention. This asymmetry matters in artificial intelligence and safety-critical multi-agent systems, where one often needs to specify not merely what agents are instructed or

Dietrich Burde, Karel Dekimpe

In this paper, we investigate the existence of fixed-point-free automorphisms for finite-dimensional Lie algebras. By a result of Jacobson, a Lie algebra admitting a fixed-point-free automorphism is solvable. We prove that such a Lie algebra must be even strongly unimodular. We find a necessary and sufficient criterion such that a complex almost abelian Lie

Jin Xin Ng, Ori Livneh, Richard O'Grady, Josh Don

Modern large multicore systems often run multiple workloads that share CPUs under schedulers such as Linux CFS. To keep CPUs busy, these schedulers load-balance runnable work, causing each workload to execute on many cores. This weakens locality at the microarchitectural level: workloads lose reuse in caches, branch predictors, and prefetchers, and interfere

Rui Xu, Yi Chen, Sihong Xie, Hui Xiong

When language models lack relevant knowledge for a given query, they frequently generate plausible responses that can be hallucinations, rather than admitting being agnostic about the answer. Retraining models to reward admitting ignorance can lead to overly conservative behaviors and poor generalization due to scarce evaluation benchmarks. We propose a post

Anshika Dhiman, Sanbo Qin, Huan-Xiang Zhou

Salts are an integral part of the environment for living systems and, therefore, understanding their effects on proteins and other biomolecules is of fundamental interest. Small-angle X-ray scattering (SAXS) of protein solutions can provide valuable information on salt effects, but extracting this information has been a significant challenge. For example, SA

Logan G Wright, Tianyu Wang, Tatsuhiro Onodera, Peter L. McMahon

Foundation models are deep neural networks (such as GPT-5, Gemini~3, and Opus~4) trained on large datasets that can perform diverse downstream tasks -- text and code generation, question answering, summarization, image classification, and so on. The philosophy of foundation models is to put effort into a single, large (${\sim}10^{12}$-parameter) general-purp

Akhil Reddy Peeketi, Blas P Uberuaga, Travis E Jones

Predictive simulation of electrochemical interfaces requires atomistic models that capture reactive bond rearrangements, long-range electrostatics, and charge distributions reflecting the electronic distinctness of electrode and electrolyte. Existing charge-aware machine-learned interatomic potentials (MLIPs) built on global charge equilibration (QEq) settle

Aida Abiad, Antonina P. Khramova, Sven C. Polak, Ferdinando Zullo

The sum-rank metric provides a unifying framework that generalizes both the celebrated Hamming and rank metrics, and has found applications in areas such as network coding, distributed storage, and space-time coding. A central problem is to determine the maximum size of a code with prescribed minimum distance. In this paper, we derive new sharp upper bounds

Caili Jia, Yong Lu

The toughness of a graph $G$, denoted by $\tau(G)$, is defined by $\tau(G)=$min $\{\frac{|S|}{c(G-S)}:S\subseteq V(G)$ and $c(G-S)\geq2\}$. A graph $G$ is said to be $\tau$-tough if $\tau(G)\geq \tau$. Let $k\geq2$ be an integer. A tree $T$ is called a $k$-tree if $d_{T}(v)\leq k$ for each $v\in V(T)$, that is, the maximum degree of a $k$-tree is at most $k$

Hao Luo, Wanpeng Zhang, Yicheng Feng, Sipeng Zheng

Visual-Language-Action models (VLAs) have advanced generalist robot control by mapping multimodal observations and language instructions directly to actions, but sparse action supervision often encourages shortcut mappings rather than representations of dynamics, contact, and task progress. Recent world-action models introduce future prediction through video

Angela Andreella, Livio Finos

Linear mixed models are widely used to analyze non-independent data, but inference for fixed effects can be unreliable under misspecification of the random-effects distribution, inaccurate Fisher information estimation, or convergence failures, leading to a lack of control over false positives. These difficulties are amplified in multivariate settings, where

Alex Petrov, Alexander Gusak, Denis Mukha, Dima Korolev

Persistent AI memory is often reduced to a retrieval problem: store prior interactions as text, embed them, and ask the model to recover relevant context later. This design is useful for thematic recall, but it is mismatched to the kinds of memory that agents need in production: exact facts, current state, updates and deletions, aggregation, relations, negat

Shuchang Zhou, Kaiwen Shen, Jiwei Wei, Yuyang Zhou

The rapid evolution of generative models has enabled the creation of highly realistic and diverse synthetic images, posing significant challenges to reliable and generalizable Synthetic Image Detection (SID). However, existing detectors are typically trained on limited and biased datasets, resulting in poor generalization to unseen generators. To address thi

Mark J. Henriksen, Layla Ahmed

Archival XMM and ROSAT X-ray data are used to investigate the structure of the Abell 548 - Abell 3367 region. Based on previous optical studies, this is a region likely to be rich in structure though studies are in disagreement regarding the connection between Abell 3367 and Abell 548. We use the available archival X-ray data together with kinematic data of

Fausto Colantoni

This paper investigates the heat equation on a bounded domain with a Robin boundary condition, where the reactivity parameter (or killing rate) is modeled as a continuous-time Markov chain. We analyze the system under two stochastic frameworks using a functional analytic approach. First, we examine the annealed case, which accounts for the joint stochasticit

Theo Tang, Toby Handfield, Julian Garcia

The volume of scientific manuscripts is growing faster than the capacity to evaluate them, yet the institutions that govern peer review have remained largely unchanged. The result is a widening mismatch: reviewer scarcity, noisier assessments, and declining confidence in editorial decisions. Every scientist wants better reviews, but review quality depends on

Guy Lutsker, Gal Sapir, Jordi Merino, Smadar Shilo

Understanding how human health changes over time, and why responses to interventions vary between individuals, remains a central challenge in medicine. Here we present HealthFormer, a decoder-only transformer that models the human physiological trajectory generatively, by training on data from the Human Phenotype Project, a multi-visit cohort of over 15,000

Shuncai Zhao, Zhengdong Liu

A scheme is proposed for realizing simultaneous negative permittivity and negative permeability based on quantum coherence in a four-level dense atomic system here.Under some parametric conditions the system shows that simultaneous negative permittivity and negative permeability(i.e.Left handness) can be achieved in a wider frequency band because of quantum

Dilem Eşlik, Bahadır Utku Kesgin, Uğur Teğin

Capturing ultrafast transient phenomena conventionally requires streak cameras or computational imaging based on compressed sensing, which lead to complex and costly systems. In this Letter, we demonstrate, to the best of our knowledge, the first fully passive single-shot ultrafast imaging architecture assembled entirely from off-the-shelf, low-cost componen

Hongguang Liu, Ioannis Soranidis

We derive a class of inner-extremal regular black hole solutions characterized by a degenerate inner horizon. These geometries arise as polymerized vacuum configurations inspired by loop quantum gravity and constitute effective quantum-gravity solutions that admit a Birkhoff-type theorem, rendering them unique within the considered framework. We show that su

J. M. Marcos, J. J. Meléndez, R. Cuerno, J. J. Ruiz-Lorenzo

We investigate the behavior of discrete interface growth models belonging to the Edwards--Wilkinson (EW) and Kardar--Parisi--Zhang (KPZ) universality classes, when defined on a complete graph, a topology commonly used to probe the infinite-dimensional limit of statistical mechanical systems. Our aim is to assess to what extent discrete lattice models reprodu

Jiawei Liu, Senqiao Yang, Mingjun Wang, Yu Wang

As one of the mainstream models of artificial intelligence, world models allow agents to learn the representation of the environment for efficient prediction and planning. However, classical world models based on flat tensors face several key problems, including noise sensitivity, error accumulation and weak reasoning. To address these limitations, many rece

Dirk Ostwald, Rasmus Bruckner, Franziska Usée, Belinda Fleischmann

Integrating theoretical neuroscience, decision theory, and probabilistic inference offers a promising route to understanding human cognition, yet concrete methodological bridges between agentic AI models and behavioral data analysis remain formally underdeveloped. We advance this synthesis under the framework of agentic behavioral modeling (ABM), which treat

Maykon Nunes, Emanuel Coutinho, Carla Bezerra, Ivan Machado

Angular is one of the most widely adopted frameworks for developing large-scale, dynamic web applications. As projects increase in scope and complexity, developers face growing challenges in managing architecture and maintaining clean, modular code. These challenges often lead to design flaws, commonly referred to as code smells. While React-specific smells

Yanwu Gu, Linglong Kong, Dong Xia

The rapidly expanding artificial intelligence (AI) industry has produced diverse yet powerful prediction tools, each with its own network architecture, training strategy, data-processing pipeline, and domain-specific strengths. These tools create new opportunities for semi-supervised inference, in which labeled data are limited and expensive to obtain, where

Simon Dennis, Michael Diamond, Rivaan Patil, Kevin Shabahang

Agent orchestration frameworks -- LangGraph, CrewAI, Google ADK, OpenAI Agents SDK, and others -- place an external orchestrator above the LLM, tracking state and injecting routing instructions at every turn. We present a controlled comparison showing that for procedural tasks, this architecture is dominated by a simpler alternative: putting the entire proce

Harold Blum, Yuchen Liu

We construct valuatively independent bases for the space of sections of an ample line bundle on a log Calabi--Yau pair over a discretely valued field and the space of regular functions on an affine CY pair with maximal boundary. While the bases are not in general unique, they induce canonical functions on the respective skeletons and are expected to agree wi

Ali Shibli, Andrea Nascetti, Yifang Ban

Semantic segmentation and change detection are two fundamental challenges in remote sensing, requiring models to capture either spatial semantics or temporal differences from satellite imagery. Existing deep learning models often struggle with temporal inconsistencies or in capturing fine-grained spatial structures, require extensive pretraining, and offer l

L. Pecoraro, A. Mercurio, M. Annunziatella, M. D'Addona

Galaxy physical properties are influenced by their environments, but the processes responsible for mass and environmental quenching and structural transformations remain debated. Galaxy clusters are ideal laboratories for investigating galaxy formation and evolution, offering a full range of galaxy properties and environments. Observations of large-scale str

Daihe Sui, Elizabeth Tipton

Standard random-effects meta-analysis relies heavily on the assumption that the underlying true effects are normally distributed. In the social sciences, where evidence synthesis increasingly involves large, highly heterogeneous datasets, this assumption is often restrictive and unjustified. Misspecification of the random-effects distribution prevents the de

Hannes Köper, Thomas Gasenzer

Degenerate spinor Bose gases with repulsive density-density interaction and anti-ferromagnetic spin-spin coupling in one spatial dimension are shown to be described by a quantum integrable matrix extension of the nonlinear Schr\"odinger model, whose fundamental fields are described by an $m\,\times\,n$ matrix of bosonic field operators. The eigenstates of th

Linjie Liu, Wei Zhang, Xian Hou, Pierrick Martin

Star-forming galaxies (SFGs) are a subclass of $\gamma$-ray emitters and a correlation between their $\gamma$-ray luminosity ($L_{\rm \gamma}$) and the total infrared (IR) luminosity ($L_{\rm IR}$) has been established based on the Fermi Large Area Telescope (LAT) data. NGC 2403 and NGC 3424 have been reported as outliers in the $L_{\rm \gamma}$-$L_{\rm IR}$

Max Lovig

In modern parametric model training, full-batch gradient descent (and its variants) suffers due to progressively stronger biasing towards the exact realization of training data; this drives the systematic ``generalization gap'', where the train error becomes an unreliable proxy for test error. Existing approaches either argue this gap is benign through compl

Giuseppe Arbore, Andrea Sillano, Luigi De Russis

Recent advances in agentic AI are shifting automation from discrete tools to proactive multi-agent systems that coordinate multi-specialized capabilities behind unified interfaces. However, today's agent systems typically rely on hard-coded agent architectures with fixed roles, coordination patterns, and interaction flows that limit end-user personalization

V. I. Kuznetsov, O. V. Trofimov

We measured unusual critical currents as functions of temperature in the zero field and as functions of a magnetic field perpendicular to the substrate surface at a given temperature close to the critical temperature in thin-film long quasi-one-dimensional superconducting aluminum two-width structures consisting of narrow and wide wires with different critic

Vladimir Gasparian, Esther Jódar, Antonio Pérez-Garrido

In this work, we provide a complete description of the scattering matrix elements and electron energy spectrum in one dimensional PT-symmetric hybrid finite systems, using the characteristic determinant approach. We present an analytical formulation of the problem and obtain a closed-form expression for the energy spectrum of the system, consisting of a regi

Hongguang Liu, Ioannis Soranidis

We present a systematic derivation of regular black hole solutions -- and their horizonless counterparts -- that achieve regularization via an anti-de Sitter core. These geometries emerge as polymerized vacuum solutions inspired by loop quantum gravity, constituting effective quantum gravity configurations that admit a Birkhoff-type theorem and are uniquely

Alexander C. Tyner, Avinash Pathapati, Alexander V. Balatsky

The potential to utilize metal-organic frameworks as a replacement for rare earth materials as well as in technological applications has prompted increased interested in this material class. The simulation of organic materials, including metal-organic frameworks (MOFs), represents a computational challenge due to an increased average number of atoms in the u

Saber Zerhoudi

User simulators are increasingly central to interactive information retrieval, yet the community lacks standardized evaluation tools. Simulators serve two objectives, behavioral realism (matching real user behavior) and tester reliability (producing valid system rankings), and these are often conflated despite being distinct and sometimes conflicting. We pre

Johannes Bärlin

In this paper, we present a new approach to obtain so-called damping estimates for self-similar solutions to general hyperbolic relaxation systems applying the method of characteristics. Such damping estimates are an important part of the stability theory of shock profiles, where they enable the closure of nonlinear stability arguments. We extend the damping

Aoxuan Wang, Fabrice Toussaint, Thomas Gibaud

Discontinuous shear thickening (DST) in dense suspensions leads to flow instabilities that limit processing in many systems. While high-power ultrasound has been reported to reduce the apparent viscosity of such materials, the origin of this effect remains unclear. Here, we investigate dense adhesive cornstarch suspensions, where shear thickening arises from

Shuchang Zhou, Shangkun Wu, Jiwei Wei, Ke Liu

AI-generated images are becoming increasingly realistic and diverse, posing significant challenges for generalizable detection. While Vision Foundation Models (VFMs) provide rich semantic representations and frequency-based methods capture complementary artifact cues, existing approaches that combine these modalities still suffer from limited generalization,

Tyrone Cutler, Tseleung So

The cohomological rigidity problem for toric orbifolds asks when an integral cohomology isomorphism implies a homotopy equivalence. In this paper we reformulate the cohomological rigidity problem in the context of $4$-dimensional toric orbifolds by introducing what we call proper isomorphisms, a variant of a concept studied by J.H.C. Whitehead. We prove that

Tom Sorger, Eric Cornelissen, Aman Sharma, Javier Ron

Software Bills of Materials (SBOMs) are increasingly mandated by regulators, yet existing sharing mechanisms impose a binary choice between full disclosure and full opacity. This exposes software suppliers to attacks that can be deduced from the SBOM only, such as the presence of a vulnerable dependency. Conversely, software consumers can be fooled by softwa

Justus Leiber, Quinn Emilia Fischer, Sven Lohmann, Philipp Maass

The mixed alkali or mixed mobile ion effect in glasses manifests itself by strong nonlinear variations of ionic transport properties upon mixing of different types of mobile ions. We develop a theory for this effect based on thermally activated hopping transport in disordered site energy landscapes that consistently incorporates the statistical-mechanical an

Sukesh Subaharan, Venkatesan VS, Murugadasan P, Sivakumar D

Large language model (LLM) agents deployed in clinical settings often exhibit abrupt, threshold-driven behavior, offering little visibility into accumulating risk prior to escalation. In real-world care, however, clinicians act on gradually rising concern rather than instantaneous triggers. We study whether explicit state dynamics can expose such pre-escalat

Timo Teufel, Xilong Zhou, Umar Iqbal, Jan Kautz

We present D-Rex, a person-specific framework for photorealistic, relightable, expressive, and animatable full-body human avatars with free-viewpoint rendering. Existing methods for relightable full-body avatars rely on explicit 3D intrinsic decomposition with analytic reflectance models, which require accurate geometry registration and careful optimization

Nuria Alabau-Bosque, Jorge Vila-Tomas, Paula Dauden-Oliver, Valero Laparra

Convolutional Neural Networks (CNNs) are widely assumed to be translation-invariant, yet standard architectures exhibit a startling fragility: even a single-pixel shift can drastically degrade performance due to their reliance on spatially dependent fully connected layers. In this work, we resolve this vulnerability by proposing a lightweight 'Online Archite

Tolga Yarman, Nimet Zaim, Alexander Kholmetskii, Ozan Yarman

We investigate the systematics of the maximum Electron-decay energy E as a function of the mass number A along isotopic chains with a fixed proton number across Z<47. By making use of the available curated nuclear data, we find that, for each fixed Z, the decay energy can be described to excellent accuracy by a linear dependence on A, provided that even-A an

Hugo Beeloo-Sauerbier Couvée, Alessandro Neri

The Etzion-Silberstein conjecture asserts that, for any finite field $\mathbb F$, Ferrers diagram $\mathcal D$, and integer $d$, there exists a linear matrix code supported on $\mathcal D$ with minimum rank distance $d$ that attains a natural upper bound on its dimension. Codes achieving this bound are called maximum Ferrers diagram (MFD) codes. While the co

V. V. Tsymbal, A. A. Raikov, N. Yu. Lovyagin

In this work, we investigate a classical cosmological test - the dependence of galaxy surface brightness on redshift z (the Tolman test). We analyzed 6 860 galaxies with reliably determined spectroscopic redshifts from the ASTRODEEP-JWST photometric catalogue. We find that (a) the mean surface brightness of galaxies indeed decreases with increasing distance,

Doyeop Kwak, Jeongsoo Choi, Suyeon Lee, Joon Son Chung

We introduce LRS-VoxMM, an in-the-wild benchmark for audio-visual speech recognition (AVSR). The benchmark is derived from VoxMM, a dataset of diverse real-world spoken conversations with human-annotated transcriptions. We select AVSR-suitable samples and preprocess them in an LRS-style format for direct use in existing AVSR pipelines. Compared with commonly

Thomas Grady, Kip Parker, Iliyan Zarov, Henry Course

Language models are saturating benchmarks for procedural tasks with narrow objectives. But they are increasingly being deployed in long-horizon, non-stationary environments with open-ended goals. In this paper we introduce KellyBench, an environment for evaluating sequential decision-making in sports betting markets. Agents are placed in a sequential simulat

Alessandra Di Gaspare, Sara Ghayeb, Craig Knox, Edmund H. Linfield

High-order harmonic generation (HHG) in solids - the frequency up-conversion of an optical signal - is governed by symmetries. At terahertz (THz) frequencies, HHG is a key technology to access high frequency spectral windows that are usually difficult to cover using conventional solid state laser technologies. This effect has been recently exploited in graph

Behnaz Ranjbar, Akash Kumar

In Mixed-Criticality (MC) systems, although the high Worst-Case Execution Time (WCET) serves as a conservative upper bound representing the task's maximum execution time under all conditions, obtaining a low WCET is essential for representing realistic executions and improving utilization and Quality-of-Service (QoS). Nevertheless, determining appropriate lo

Hassan Nasreddine

Let \(O\mapsto A(O)\) be a local Haag--Kastler net and let \(A^d(O)=A(O&#39;)&#39;\) be its dual net. Normal unital completely positive maps on \(B(H)\) that fix \(A(O&#39;)\) pointwise are exactly the channels with Kraus operators in \(A^d(O)\). Thus Haag duality at \(O\) is equivalent to equality with the \(A(O)\)-inner channels, while essential duality is

Bowen Sun, Chaozhuo Li, Yaodong Yang, Yiwei Wang

Decompositional jailbreaks pose a critical threat to large language models (LLMs) by allowing adversaries to fragment a malicious objective into a sequence of individually benign queries that collectively reconstruct prohibited content. In real-world deployments, LLMs face a continuous, untraceable stream of fully anonymized and arbitrarily interleaved reque

Dmitry A. Egorov, Dmitriy A. Pokhabov, Evgeny Yu. Zhdanov, Andrey A. Shevyrin

We report the formation of large-scale steady-state whirlpools in a GaAs-based two-dimensional electron liquid and demonstrate them by straightforward transport measurements. A whirlpool forming inside a circular cavity adjoining a wide conducting channel appears as a negative four-terminal resistance over a broad range of temperatures and cavity sizes. The

Tan Van Vu, Keiji Saito

The third law of thermodynamics forbids cooling a physical system to absolute zero in a finite number of operational steps. Although this unattainability principle has been quantified for specific state-to-state transitions, a universal, dynamics-independent bound for implementing a state-agnostic reset map remains elusive. In this work, we unveil the fundam

Mesfin Taye

A pygmy shrew (\textit{Suncus etruscus}, ${\approx}2$\,g) sustains a resting heart rate near $1{,}000$\,beats\,min$^{-1}$ and dies within two years; an African elephant (${\approx}4{,}000$\,kg) beats at $28$\,beats\,min$^{-1}$ and lives seven decades. Their chronological lifespans differ by a factor of 35, yet each accumulates close to $10^9$ cardiac cycles

Xubin Luo, Cheng Yang

AI inference is becoming a persistent and geographically distributed source of electricity demand. Unlike many traditional electrical loads, inference workloads can sometimes be executed away from the user-facing service location, provided that latency, state locality, capacity, and regulatory constraints remain acceptable. This paper studies when such digit

Andrea Detti, Shahram Dadras, Giuseppe Tropea

NetSatBench is a distributed emulation platform for evaluating communication protocols and application workloads over large-scale LEO satellite systems. Satellites, gateways, and user terminals are implemented as Linux containers distributed across a cluster of bare-metal or virtual machines, while emulated links are realized through a Layer-2 VXLAN overlay.

Shiyao Peng, Qianhe Zheng, Zhuodi Hao, Zichen Tang

Although precise recall is a core objective in Retrieval-Augmented Generation (RAG), a critical oversight persists in the field: improvements in retrieval performance do not consistently translate to commensurate gains in downstream reasoning. To diagnose this gap, we propose the Recall Conversion Rate (RCR), a novel evaluation metric to quantify the contrib

David Navia, Ángel S. Sanz

Fractal structures naturally emerge in quantum systems whose initial states exhibit spatial discontinuities, a phenomenon first identified by Berry in the paradigmatic case of a particle confined in an infinite potential well. While previous analyses of quantum fractals have mainly relied on spectral decompositions and geometric scaling arguments, their quan

Oier Ijurco, Oier Lopez de Lacalle

Task-based dialogue systems assist users in achieving specific goals, such as executing actions or retrieving information, through natural language interactions. Accurate coreference resolution is essential, as it involves identifying object references within the dialogue - a task that becomes increasingly challenging in visually grounded environments charac

Khalil Al-Rahman Youssefi, Marija Gojkovic, Walter Stefanutti, Mika Auer

This paper presents a configurable, grid-aware Agent-Based Model (ABM) for the systematic analysis of electric vehicle (EV) charging systems under configurable infrastructure and operational conditions. The model integrates heterogeneous EV behavior, charging column constraints, and a shared Energy Sandbox that regulates aggregate power allocation, enabling

V. I. Kuznetsov, O. V. Trofimov

We measured the rectification of an ac voltage in a structure of superconducting circularly-asymmetric aluminum rings in series, permeated with a magnetic flux and biased with a low-frequency alternating current (without a dc component). This rectification is due to the shift of the maxima of the critical currents of different polarity relative to the zero f

Harry Altman, Paolo Lipparini

J. Conway defined useful operations on the Class of combinatorial games and also introduced a notion of equivalence between games. Conway showed that, under his equivalence, games form a Group. However, Conway product is not well defined on equivalence classes of arbitrary games (though it is well defined for surreals). We consider an equivalence relation fi

Yuxi Ma, Jieming Cui, Muyang Li, Ye Zhao

How people narrate their experiences offers a window into how the mind organizes them. Computational approaches to therapeutic writing have evolved from lexical counting to neural methods, yet remain fragmented: dictionary tools miss discourse structure, while embeddings conflate local coherence with global organization. No existing framework maps these tech

Zhuoming Zhang, Weiguang Cui, Yun Chen, Romeel Davé

Using the SIMBA, EAGLE, and IllustrisTNG-100 galaxy formation simulations, we examine the anisotropy of the satellite distribution and its dependencies on central galaxies, host halos, and cosmic filaments. We find that in all simulations the satellite anisotropy is robustly aligned with the halo/central galaxy major axis. This correlation is both redshift-

Wenxiang Lin, Xinglin Pan, Ruibo Fan, Shaohuai Shi

Communication has emerged as a critical bottleneck in the distributed training of large language models (LLMs). While numerous approaches have been proposed to reduce communication overhead, the potential of lossless compression has remained largely underexplored since compression and decompression typically consume larger overheads than the benefits of redu

Yuki Nakamura, Takuya Iwasaki, Shu Nakaharai, Shinichi Ogawa

Negatively charged boron vacancy (VB-) defects in hexagonal boron nitride (hBN) are promising for nanoscale-proximity quantum sensing. To evaluate their performance, it is important to characterize the spin coherence times T2* and T2. In this study, we realized sub-GHz Rabi oscillations of VB- using an isotopically enriched hBN thin film directly stamped ont

Asma Ben Rjeb, Pedro Tradacete

We study structural properties of the free Banach lattice $FBL\langle L\rangle$ generated by a distributive lattice $L$. We characterize when $FBL\langle L\rangle$ has a strong unit, compute its density character, analyze the density character of order intervals and study when is $FVL\langle L\rangle$ order dense in $FBL\langle L\rangle$. We also study proje

Bokai Pan, Mingyue Cheng, Zhiding Liu, Shuo Yu

Recently, large language models (LLMs) have shown great promise in time series forecasting. However, most existing LLM-based forecasting methods still follow a static generative paradigm that directly maps historical observations to future values in a single pass. Under this paradigm, forecasting is constrained by limited temporal pattern extraction, single-

Myeongjin Shin, Junseo Lee, Changhun Oh

Characterizing quantum systems by learning their underlying Hamiltonians is a central task in quantum information science. While recent algorithmic advances have achieved near-optimal efficiency in this task, they critically rely on accessing arbitrarily short-time dynamics. This reliance poses severe experimental challenges due to finite control bandwidth a

Wenjun Jiang, Qingqing Zhang, Yiying Zhang

This paper investigates two optimal insurance contracting problems under distributional uncertainty from the perspective of a potential policyholder, utilizing a Bregman-Wasserstein (BW) ball to characterize the ambiguity set of loss distributions. Unlike the $p$-Wasserstein distance, BW divergence enables asymmetric penalization of deviations from the bench

Namasi G Sankar, Georgios Miliotis, Simon Caton

Practical applicability of quantum optimisation on near term devices is constrained by limited qubit counts and hardware noise, which restricts the scalability of quantum optimisation algorithms for combinatorial problems. The simulation of large quantum circuits is also difficult and constrained by memory requirement. The Hamiltonian Auto Decomposition Opti

Luis E. Ibáñez

The 'Species Scale' has proved to be an important concept when studying consistent effective actions in Quantum Gravity. This is a short summary of my contribution to the Corfu Summer Institute in September 2025, in which I covered two topics, both related in different ways to the fact that the Species Scale is moduli dependent. In the first, based on work d

Ramon Moya

We study hypergeometric functions of nilpotent operators in finite-dimensional settings, motivated by the algebraic structure of exceptional points in non-Hermitian quantum mechanics. Our starting point is the following exact result: if N is a nilpotent operator of index m+1 in an associative algebra over C, then every generalized hypergeometric function pFq

Yuhua Wang, Qinnan Zhang, Xiaodong Li, Huan Zhang

Prototype-based Personalized Federated Learning (ProtoPFL) enables efficient multi-domain adaptation by communicating compact class prototypes, but directly sharing them poses privacy risks. A common defense involves per-example $\ell_2$ clipping before prototype computation to bound sensitivity, followed by isotropic Gaussian noise to enforce Local Differen