April 2026 arXiv papers — page 69

Mohamed Hesham Elganayni, Runsheng Chen, Sebastian Nagl, Matthias Grabmair

This work explores the role of prompt design and judge selection in LLM-as-a-Judge evaluations of free text legal question answering. We examine whether automatic task prompt optimization improves over human-centered design, whether optimization effectiveness varies by judge feedback style, and whether optimized prompts transfer across judges. We systematica

Masayuki Matsuo, Arata Nishiwaki, Toshiyuki Okihashi, Masaru Hongo

The interaction between lattice vibrations of nuclear clusters and superfluid phonons associated with neutron superfluidity plays an important role in the dynamics of the neutron-star inner crust. While this coupling has been discussed mainly within macroscopic approaches such as hydrodynamics and effective field theory, its microscopic origin and the value

Gerald Gebhardt, Bernd Engel

Modern distribution grids with high penetration of renewable generation provide substantial flexibility through distributed reactive power sources and transformer tap changers. This high degree of freedom can be exploited for optimisation. However, choosing an objective function for optimisation is not trivial, e.~g. minimising grid losses may lead to overvo

Giovanni Charles, Cosmo Santoni, Seth Flaxman, Elizaveta Semenova

The cost of simulator evaluations is a key practical bottleneck for Simulation Based Inference (SBI). In hierarchical settings with shared global parameters and exchangeable site-level parameters and observations, this structure can be exploited to improve simulation efficiency. Existing hierarchical SBI approaches factorise the posterior yet still simulate

Yutong Shen, Hangxu Liu, Lei Zhang, Penghui Liu

Long-Horizon (LH) tasks in Human-Scene Interaction (HSI) are complex multi-step tasks that require continuous planning, sequential decision-making, and extended execution across domains to achieve the final goal. However, existing methods heavily rely on skill chaining by concatenating pre-trained subtasks, with environment observations and self-state tightl

Noah Flynn

Large language models (LLMs) often exhibit performance disparities across languages, with naive multilingual fine-tuning frequently degrading performance due to negative cross-lingual interference. To address this, we introduce COMPASS (COntinual Multilingual PEFT with Adaptive Semantic Sampling), a novel data-centric framework for adapting LLMs to target la

Menghe Ma, Siqing Wei, Yuecheng Xing, Ziyue Zhu

Omnimodal notation processing, centered on sheet music, is a controlled scientific setting in which auditory, visual, symbolic, and physical representations must encode the same musical events. Yet existing work remains fragmented across recognition and transcription, rarely testing structural consistency across notation systems. Western-staff bias and under

Rebekah Edwards, Taylor Martini, Jonathan E. Swindell, David W. Cox

Accurate antenna array calibrations and measurements of aspects such as active element pattern (AEP) are critical for enabling integrated sensing and communication (ISAC) technologies such as directional modulation. One reliable way of obtaining accurate and repeatable AEP measurements is to spin the antenna array on a turntable, but many turntables designed

Leonardo A. Pachon

We present a complete analysis of the angular momentum selection rules and electromagnetic backgrounds that constrain any spectroscopic search for the gravitomagnetic spin-quadrupole coupling in highly charged ions. A sequence of four barriers is identified: (i)~the Wigner-Eckart theorem mandates $j \geq 3/2$ electronic states for sensitivity to the rank-2 g

M. F. Hansen, C. Lepoittevin, J. -B. Vaney, P. Boullay

Chemical composition provides a powerful route to tune the electronic ground state of iron-based superconductors and other quantum materials, yet access to highly doped phases remains limited. Here we demonstrate that high-pressure thermal decomposition of hydrogen-rich precursors enables over-hydrogenation of LaFeSi. Using anthracene, we synthesize tetragon

Yuxuan Xue, Ruofan Liang, Egor Zakharov, Timur Bagautdinov

Relighting a person from a single photo is an attractive but ill-posed task, as a 2D image ambiguously entangles 3D geometry, intrinsic appearance, and illumination. Current methods either use sequential pipelines that suffer from error accumulation, or they do not explicitly leverage 3D geometry during relighting, which limits physical consistency. Since re

Shan He, Runze Wang, Zhuoyun Du, Huiyu Bai

Designing and optimizing multi-agent systems (MAS) is a complex, labor-intensive process of "Agent Engineering." Existing automatic optimization methods, primarily focused on flat prompt tuning, lack the structural awareness to debug the intricate web of interactions in MAS. More critically, these optimizers are static; they do not learn from experience to i

Wadim Gerner

Given a plasma domain $P\subset\mathbb{R}^3$, a plasma equilibrium field $B$ on $P$ and a coil winding surface $\Sigma$ surrounding $P$, we provide an analytic formula whose output is a surface current distribution $j$ on $\Sigma$ such that $\operatorname{BS}(j)+\operatorname{BS}(\operatorname{curl}(B))=B$ in $P$, i.e. the combination of the plasma current m

Yongqiang Zhao, Xuyang Zhang, Zhuo Chen, Matteo Leonetti

Peg-in-hole (PiH) assembly is a fundamental yet challenging robotic manipulation task. While reinforcement learning (RL) has shown promise in tackling such tasks, it requires extensive exploration. In this paper, we propose a novel visual-tactile skill learning framework for the PiH task that leverages its inverse task, i.e., peg-out-of-hole (PooH) disassemb

Yi-Yung Yang, Sanghyun Lee, Dmitri Kuzmin

Enhanced geothermal systems (EGS) involve strongly coupled, advection-dominated flow and heat transfer in fractured porous media. Conventional models typically assume local thermal equilibrium with a single effective fluid temperature or, at best, an averaged pore-fluid temperature, so the thermal evolution of injected cold fluid is only inferred indirectly.

Mizuki Ohno, Reiley Dorrian, Veronica Show, Joseph Falson

ThCr$_2$Si$_2$-type intermetallics are layered conductors in which crystallographic anisotropy and multiband electronic states often give rise to characteristic magnetotransport phenomena. Here, we report the molecular-beam epitaxy growth of LaAg$_2$Ge$_2$ thin films on MgO(001) and their magnetotransport properties. The Hall effect and magnetoresistance are

Daria Poliakova

We study cubic realizations of posets compatible with projection maps, meaning that the projection is represented by deletion of the last coordinate. For cylindrical projections, we introduce the pre-Reeb graph and the augmented pre-Reeb graph, which control compatible cubic lifts and compatible order-embedding cubic lifts, respectively. We apply this constr

Pascal Archambault, Houari Sahraoui, Eugene Syriani

Digital twins of natural systems must remain aligned with physical systems that evolve over time, are only partially observed, and are typically modeled by mechanistic simulators whose parameters cannot be measured directly. In such settings, model adaptation is naturally posed as a simulation-based inference problem. However, sparse and indirect observation

Minqi Shao, Shangzhou Xia, Jianjun Zhao

With the growing synergy between deep learning and quantum computing, Quantum Neural Networks (QNNs) have emerged as a promising paradigm by leveraging quantum parallelism and entanglement. However, testing QNNs remains underexplored due to their complex quantum dynamics and limited interpretability. Developing a mutation testing technique for QNNs is promis

Yongquan Yang

In many real-world machine learning (ML) applications, the true target cannot be precisely defined due to ambiguity or subjectivity information. To address this challenge, under the assumption that the true target for a given ML task is not assumed to exist objectively in the real world, the EL-MIATTs (Evaluation and Learning with Multiple Inaccurate True Ta

Saish Sachin Shinde

We present SCM (Sleep-Consolidated Memory), a research preview of a memory architecture for large language models that draws on neuroscientific principles to address a fundamental limitation in current systems: the absence of persistent, structured, and biologically plausible memory. Existing approaches rely on truncating context windows, growing vector data

Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr, Federico Tombari

Reinforcement learning (RL) with verifiable rewards (RLVR) has demonstrated the great potential of enhancing the reasoning abilities in multimodal large language models (MLLMs). However, the reliance on language-centric priors and expensive manual annotations prevents MLLMs' intrinsic visual understanding and scalable reward designs. In this work, we introdu

Abhijit Talluri

Adversarial robustness evaluation underpins every claim of trustworthy ML deployment, yet the field suffers from fragmented protocols and undetected gradient masking. We make two contributions. (1) Structured synthesis. We analyze nine peer-reviewed corpus sources (2020--2026) through seven complementary protocols, producing the first end-to-end structured a

Yichen Li, Aleksey Bolotnikov, Milind Diwan, Jay Hyun Jo

We describe the design and performance of a 260-liter liquid argon (LAr) cryogenic test stand for liquid argon detector research and development at BNL. The system uses gas-phase argon purification with continuous pump-free circulation, in which boil-off argon gas is purified, recondensed, and returned to the cryostat by gravity without a mechanical recircul

Yuya Kawamata, Yuichiro Nakano, Keisuke Fujii

Sampling problems are promising candidates for demonstrating quantum advantage, and one approach known as quantum-enhanced Markov chain Monte Carlo [Layden, D. et al., Nature 619, 282-287 (2023)] uses quantum samples as a proposal distribution to accelerate convergence to a target distribution. On the other hand, many practical problems are large-scale and c

Swornalata Ojha, Hermie Monterde, Hiranmoy Pal

For $q\in\mathbb{R}\backslash\{0\}$, the generalized Laplacian of a graph $X$ is the matrix $\mathscr{L}=\Delta+qA$, where $\Delta$ is the degree matrix and $A$ is the adjacency matrix of $X$. In this paper, we investigate perfect state transfer (PST) on graphs with possible loops equipped with non-trivial involutions, where we take the generalized Laplacian

Nashrah Afroze, Salma Soliman, Yu-Hsin Kuo, Sanghyun Kang

We systematically explore the design space of ferroelectric hafnium-zirconium oxide (H0.5Z0.5O or HZO) heterostructures for reliable high temperature operation. HZO films are deposited using thermal and plasma-enhanced atomic layer deposition (Th-ALD and PE-ALD) on tungsten (W) and titanium nitride (TiN) bottom electrodes (BE), while maintaining identical to

Doru Sticlet, Ovidiu I. Pâţu, Balázs Dóra, Cătălin Paşcu Moca

We study dynamical correlations of interacting hard-core anyons on a one-dimensional lattice at infinite temperature. This is a setting in which the many-body spectrum is independent of the statistical phase $θ$, while dynamical correlators remain sensitive to $θ$ through nonlocal Jordan-Wigner strings. We compute single-particle Green's functions, spect

Jiahao Xie, Alessio Tonioni, Nathalie Rauschmayr, Federico Tombari

Large vision-language models (LVLMs) have demonstrated impressive performance in various multimodal understanding and reasoning tasks. However, they still struggle with object hallucinations, i.e., the claim of nonexistent objects in the visual input. To address this challenge, we propose Region-aware Chain-of-Verification (R-CoV), a visual chain-of-verifica

Antonio Blanca, Reza Gheissari, Heehyun Park, Xusheng Zhang

We study the random-cluster model on trees and treelike graphs at low temperatures. This is a model of dependent percolation parametrized by an edge probability $p\in (0,1)$ and a clustering weight $q\in [1,\infty)$, generalizing independent Bernoulli percolation ($q=1$) and closely related to the classical ferromagnetic Ising and Potts spin systems at integ

HyoJae Kang, Joonho Lee, Hyunmok Jung, Dong Il Park

Evaluating the pinch capability of a robotic hand is important for understanding its functional dexterity. However, many existing grasp evaluation methods rely on object geometry or contact force models, which limits their applicability during the early stages of robotic hand design. This study proposes a kinematic evaluation method for analyzing pinch confi

Dinh Triem Phan, Jérôme Bobin, Cheick Thiam, Christophe Bobin

Identifying and quantifying $\gamma$-emitting radionuclides, considering spectral deformation from $\gamma$-interactions in radioactive source surroundings, present a significant challenge in $\gamma$-ray spectrometry. In that context, a hybrid machine learning method has been previously proposed to jointly estimate the counting and spectral signatures of $\

Noujoud Nader, Stefanos Giaremis, Clint Dawson, Carola Kaiser

Storm surge forecasting remains a critical challenge in mitigating the impacts of tropical cyclones on coastal regions, particularly given recent trends of rapid intensification and increasing nearshore storm activity. Traditional high fidelity numerical models such as ADCIRC, while robust, are often hindered by inevitable uncertainties arising from various

Sandro Kraemer, Karen Mamian, Toby Bi, Shun Fujii

While the $^{229}$Th nuclear isomer has recently been observed and laser-excited, converting optical nuclear manipulation into a chip-scale solid-state frequency standard remains an open challenge. Here, we present a nanophotonic platform to realize an all-solid-state nuclear clock based on the low-energy isomeric transition of $^{229}$Th embedded in high-$Q

HyoJae Kang, Joonho Lee, Jeongdo Ahn, Dong Il Park

In the design stage of robotic hands, it is not straightforward to quantitatively evaluate the effect of phalanx length ratios on dexterity without defining specific objects or manipulation tasks. Therefore, this study presents a framework for optimizing the phalanx length ratios of a five-finger robotic hand based on potential dexterity within a kinematic s

Andor Vári-Kakas, Ji Won Park, Natasa Tagasovska

Aligning large language models (LLMs) to desirable human values requires balancing multiple, potentially conflicting objectives such as helpfulness, truthfulness, and harmlessness, which presents a multi-objective optimisation challenge. Most alignment pipelines rely on a fixed scalarisation of these objectives, which can introduce procedural unfairness by s

Z. Chen, S. Fu, Y. Zeng, X. Xu

Channel knowledge map (CKM) is a promising technique to achieve environment-aware wireless communication and sensing. Constructing the complete CKM based on channel knowledge observations at sparse locations is a fundamental problem for CKM-enabled wireless networks. However, most existing works on CKM construction only consider the special type of CKM, i.e.

Exequiel Jun V. Villejo, Aurelio A. de los Reyes, Bryan S. Hernandez

Understanding how biochemical systems settle into stable states, such as how protein concentrations reach equilibrium, is central to explaining cellular behavior and designing synthetic biological circuits. However, existing analytical tools for computing these equilibria, such as COMPILES, are limited by computational bottlenecks and can only be applied to

Samuel Salfati

We present a systematic empirical study of transformer compression through over 40 experiments on GPT-2 (124M parameters) and Mistral 7B (7.24B parameters). Our analysis covers spectral compression, block-level function replacement, rotation-based quantization, activation geometry, and adaptive early exit. We identify five structural properties relevant to c

Chen-Can Wang, Jia-Ai Shi, Bing-Nan Lu

Cutoff independence is an essential requirement for the predictive power of nuclear \textit{ab initio} calculations based on effective field theory (EFT). While it is conventionally assumed that such invariance necessitates high-order interactions and complex many-body forces, we present a minimal chiral nuclear force that exhibits remarkable cutoff independ

Tian-Le Yang, Pei-Rong Han, Zhen-Biao Yang, Shi-Biao Zheng

Dissipatively stabilized cat qubits are promising for fault-tolerant quantum information processing, yet their non-Hermitian (NH) spectral topology remains largely unexplored. We uncover rich Liouvillian exceptional structures in a cat-qubit mode stabilized by two-photon drive (TPD) and engineered two-photon loss, in the presence of single-photon drive (SPD)

Daniele Corradetti, Renato Corradetti

We present a biologically detailed extension of the classical Hopfield/Marr auto-associative memory model for CA3, implementing ten populations (two asymmetric pyramidal subtypes, eight GABAergic interneuron classes), forty-seven compartments, multi-rule plasticity (recurrent Hebb, BCM anti-saturation, mossy-fiber short-term, endocannabinoid iLTD, burst-gate

Yuto Yokoyama, Vincenzo Calabrese, Fabian Hillebrand, Henry J. London

Orientation and relaxation dynamics of rod-like colloids under flow govern the optical and mechanical properties of many emerging soft materials. In polydisperse suspensions, particles of different lengths exhibit distinct rotational diffusion timescales, yet how this polydispersity influences relaxation following flow cessation remains unclear. In particula

Chaima Boufaied, Ronnie De Souza Santos, Ann Barcomb

Large Language Models (LLMs) are increasingly deployed in socially sensitive settings, raising concerns about fairness and biases, particularly across intersectional demographic attributes. In this paper, we systematically evaluate intersectional fairness in six LLMs using ambiguous and disambiguated contexts from two benchmark datasets. We assess LLM behavi

Jiangong Chen, Xia Lei, Yuchen Zhang, Kaitao Meng

Integrated Sensing and Communication (ISAC) systems require efficient beamforming architectures to jointly support communication and sensing functionalities. To reduce hardware overhead, Hybrid Beamforming (HBF) has been widely studied and shown to achieve performance close to fully digital beamforming under practical hardware constraints. As a promising evo

Sara Petiton, Antoine Grigis, Raphaël Vock, Edouard Duchesnay

Linear models are widely used in computational neuroimaging to identify biomarkers associated with brain pathologies. However, interpreting the learned weights remains challenging, as they do not always yield clinically meaningful insights. This difficulty arises in part from the inherent correlation between brain regions, which causes linear weights to refl

Baptiste Filoche, Stefan Hohenegger, Taro Kimura

We study the instanton counting in four dimensional $\mathcal{N}=2$ supersymmetric gauge theories on the blow-up of $\mathbb{C}^2$: we start by formulating the instanton moduli space as a quiver variety, which we regularise by introducing two stability parameters, thus endowing it with a structure of infinitely many chambers separated by walls. Within a give

Auejin Ham, Ben Boudaoud

Submovements are ballistic components of human motion constituting a large part of motor interaction and arising from the cyclical and overlapping cognitive processes of perception, motor planning, and motor execution. Extracting submovements is challenging as the motions tend to overlap, or start before the previous ends. We propose and evaluate use of a wa

Vedin Dewan, Aleksei M. Zheltikov, Julia M. Mikhailova

Ultrafast strong-field laser--plasma physics is shown to offer a promising framework for relativistic nonlinear quantum electrodynamics (QED). As one of its key advantages, this approach to relativistic nonlinear QED does not require an external beam of relativistic particles. Instead, high-energy electrons are produced in this setting as a part of ultrafast

Adam Białożyt

The medial axis of a closed set is well established tool in pattern recognition, cherished for its power of reconstruction of domains. In this article we fill this gap answering the question which sets precisely are reconstructible from the medial axis information. We do not assume any additional structure of considered sets besides them being closed in n-di

Xingyang Zhang

In this paper, we consider the global spherically symmetric strong solutions to the compressible Navier-Stokes equations with far-field vacuum and density-dependent degenerate viscosity, following the framework proposed by Bresch-Vasseur-Yu \cite{B-V-Y 2021}. For the 1D Navier-Stokes equations, Wen-Zhang \cite{W-Z SIAM 2025} considered the Cauchy problem whi

Richard B. Arthur

High-consequence decision making demands peak performance from individuals in positions of responsibility. Such executive authority bears the obligation to act despite uncertainty, limited resources, time constraints, and accountability risks. Tools and strategies to motivate confidence and foster risk tolerance must confront informational noise and can prov

Meng Ji

Bipartite Ramsey numbers is the smallest size of a complete bipartite graph $K_{N,N}$ such that every edge-coloring with a given number of colors inevitably yields a monochromatic copy of a prescribed bipartite graph. While exact values have been determined for certain specific graphs, the general asymptotic behavior of these numbers in terms of structural g

Youqi Yang, Walter Dempsey, Bhramar Mukherjee

Randomized controlled trials (RCTs) are often underpowered to detect treatment heterogeneity in subgroups defined by cross-classifications of multiple covariates, due to sparse sample sizes in some strata. External RCT data can help, but typically provide treatment effect estimates at a coarser level (e.g., by sex or race) rather than for the finer subgroups

Ioannis E. Livieris, Athanasios Koursaris, Alexandra Apostolopoulou, Konstantinos Kanaris Dimitris Tsakalidis

Effective retrieval-augmented generation across bilingual Greek--English applications requires embedding models capable of capturing both domain-specific semantic relationships and cross-lingual semantic alignment. Existing multilingual embedding models distribute their representational capacity across numerous languages, limiting their optimization for Gree

Anastasia Burkovskaya, Egor Starkov

We propose a model of causal persuasion, in which a sender selectively discloses a set of variables together with their true joint distribution and proposes a subjective causal model that binds them. A receiver is persuaded by this model only if the data conclusively identifies the causal link of interest. We characterize when such persuasion succeeds or fai

Yubo Jiang, Yitong An, Xin Yang, Abudukelimu Wuerkaixi

Vision-Language Models (VLMs) are frequently undermined by object hallucination, generating content that contradicts visual reality, due to an over-reliance on linguistic priors. We introduce Positive-and-Negative Decoding (PND), a training-free inference framework that intervenes directly in the decoding process to enforce visual fidelity. PND is motivated

Marcel R. R. Hughes, Kohei Jin, Daiki Matsumoto, Leon Miyahara

BPS states in holographic CFTs are usually classified into supergravitons, namely BPS fluctuations around empty AdS, and black-hole microstates, which appear above an energy threshold. In AdS$_3$/CFT$_2$, however, this picture is incomplete because of additional degrees of freedom, called singletons, associated with boundary diffeomorphisms. We present a gen

Jennifer S. Balakrishnan, Francesca Bianchi, Netan Dogra

The Chabauty--Coleman--Kim method, under favourable circumstances, describes the set of integral points of a hyperelliptic curve inside the $p$-adic zeroes of certain transcendental functions. For an elliptic curve of Mordell--Weil rank one, the Chabauty--Coleman--Kim set in depth 2 is given by the zeroes of a (finite union of) quadratic polynomial(s) in the

P. A. González, Marco Olivares, Eleftherios Papantonopoulos, Yerko Vásquez

We investigate timelike geodesics in asymptotically flat regular black holes supported by a phantom scalar field characterized by a scalar charge $A$. This parameter removes the central singularity and continuously deforms the Schwarzschild geometry while preserving asymptotic flatness. We derive the equations of motion for massive test particles and classif

Jeanne Boursier

We study the complexity of the Thouless-Anderson-Palmer (TAP) free energy for Ising spin glasses with a general mixed p-spin covariance, working with the generalized TAP functional of Chen, Panchenko, and Subag. We formulate three conjectures about the complexity (i.e. number of critical points). First, the annealed complexity is given by the Legendre transf

Jingyi Wang, Lei Zhu, Tengjin Weng, Song-Li Wu

Reinforcement Learning with Verifiable Rewards (RLVR) has advanced the reasoning capabilities of Large Language Models (LLMs) by leveraging direct outcome verification instead of learned reward models. Building on this paradigm, Group Relative Policy Optimization (GRPO) eliminates the need for critic models but suffers from indiscriminate credit assignment f

Shivani Kumar, Adarsh Bharathwaj, David Jurgens

Multi-agent systems built from teams of large language models (LLMs) are increasingly deployed for collaborative scientific reasoning and problem-solving. These systems require agents to coordinate under shared constraints, such as GPUs or credit balances, where cooperative behavior matters. Behavioral economics provides a rich toolkit of games that isolate

Hirotaka Yoshino, Kousuke Tanaka

The interaction between a Nambu-Goto string and a Kerr black hole gives one of the methods of energy extraction from a rotating black hole. Although the properties of such processes have been well studied for rigidly rotating strings, little is known for non-rigidly rotating strings. In this paper, we study time evolution of a Nambu-Goto string on the equato

Rui Wang, Xuhang Dai, Xin Cao, Changchuan Yin

A comprehensive analysis of viral mutations is essential for understanding viral evolution, disease epidemiology, diagnosis, drug resistance, etc. However, challenges remain in capturing complex mutation patterns and supporting diverse viral families with varying genome architectures. To address these needs, we present VARIANT, an web server for mutational a

Mei-San Maggie Lei, John Stewart Fabila Carrasco, Javier Escudero

We introduce a graph-signal generalisation of Sample Entropy, denoted SampEn$_{G}$, to quantify irregularity of graph signals on a continuous state space, complementing existing methods on symbolic dynamics. Our approach replaces the temporal delay embedding of classical SampEn with a multi-hop graph-based embedding: for each node, we aggregate patterns from

Chayan Chatterjee

Recent LIGO-Virgo-KAGRA (LVK) analyses have revealed complex structure in the binary black hole (BBH) population, including distinct features in the primary mass spectrum and nontrivial spin-mass correlations. However, the phenomenological models used to capture these features often lack analytic transparency, making it difficult to isolate robust physical l

Houssam Abdul-Rahman, Thomas A. Jackson, Yousef Salah

We prove general sufficient conditions for zero velocity in position dependent one-dimensional quantum walks, and hence for the absence of ballistic transport. Our starting point is a general a priori upper bound on the velocity, formulated in terms of sparse bi-infinite sequences of sites, their gap structure, and the corresponding local coin parameters. Th

Nattavudh Powdthavee

Large language models trained on human feedback may suppress fraud warnings when investors arrive already persuaded of a fraudulent opportunity. We tested this in a preregistered experiment across seven leading LLMs and twelve investment scenarios covering legitimate, high-risk, and objectively fraudulent opportunities, combining 3,360 AI advisory conversati

A. Koursaris, G. Domalis, A. Apostolopoulou, K. Kanaris

Understanding the intricate dynamics of online discourse depends on large-scale deliberation data, a resource that remains scarce across interactive web platforms due to restrictive accessibility policies, ethical concerns and inconsistent data quality. In this paper, we propose Chorus, an agentic framework, which orchestrates LLM-powered actors with behavio

Kenta Ueyama

Let $S$ be an $\mathbb N$-graded Koszul Artin-Schelter regular algebra and let $\sigma$ be a graded algebra automorphism of $S$. We study the stable category of graded maximal Cohen-Macaulay modules over the trivial extension algebra $S\ltimes S_\sigma(-1)$. We show that this category is triangle equivalent to the bounded derived category of finitely generat

Sepehr Assadi, Helia Yazdanyar

A celebrated result of Johansson in graph theory states that every triangle-free graph of maximum degree $\Delta$ can be properly colored with $O(\Delta/\ln\Delta)$ colors, improving upon the "greedy bound" of $\Delta+1$ coloring in general graphs. This coloring can also be found in polynomial time. We present an algorithm for maintaining an $O(\Delta/\ln\De

Stephanie Wehner

Consider two parties who want to agree on a common frequency band for communication in the presence of independent jammers. Such jammers block a different subset of bands at each site, where each party can observe only its own set of unjammed bands. Yet, they must agree on a common band without communicating. We first establish the optimal classical strategy

Arindam Banerjee, Marc Chardin, Rafael Holanda

We extend some properties of a pair of ideals described in terms of Tor modules to any number of ideals, including the well-known rigidity property. Those extensions require the development of a homological theory for spectral sequences arising from multiple complexes. Out of this theory, two new complexes associated with quotients by sums and quotients by p

L. Aviles Felix, M. Vasquez Mansilla, J. E. Gomez, M. Balod

Co80Ir20 ferromagnetic thin films have recently been the focus of intensive research because the negative magnetocrystalline anisotropy adds to the shape anisotropy and favors a strong alignment of the magnetization in the film plane for [001] textured or epitaxial thin films. However, the role of magnetoelastic effects has not been properly considered in mo

Yijia Zeng, Xiang Pan, Hailong Ma

Experimental measurements of different decays of charmed mesons have been extensively performed at BESIII. Precision measurements of absolute branching fractions of different decays, the decay constants of $D^+$ and $D^+_s$ mesons, hadronic form factors of $D$ transitions to light hadrons ($K$, $\pi$, $\eta$, $\eta^\prime$, $K^*(892)$, $\rho$, $\omega$, $\ph

Robson Christie, Cerys Murray, Youngchan Kim, Jaewoo Joo

We quantify the excitonic coupling in the homodimer of dimeric Venus fluorescent protein using a quantum-classical hybrid workflow. Employing a transition-density coupling formalism, we calculate $J = 74.38~\mathrm{cm^{-1}}$, which is 5.6 times stronger than the far-field point-dipole estimate of $13.31~\mathrm{cm^{-1}}$. This disparity highlights the critic

Deekshith Pathayappilly Krishnan, Kaan Okumus, Khac-Hoang Ngo, Giuseppe Durisi

We derive finite-blocklength bounds on the minimum achievable energy per bit over a Gaussian unsourced multiple access (UMA) channel in the presence of heterogeneous path-loss conditions. We consider a setting in which the path loss is known to the users, which enables the use of location-based codebook partitioning [\c{C}akmak et al., 2025]. Through numeric

Nikita Fominykh, Vladimir Stegailov

The enigmatic puzzle of the Verwey transition in magnetite Fe$_3$O$_4$ has been unresolved for almost a century. We present an ab initio-based model of the polaron transport combining kinetic Monte Carlo and molecular dynamics calculations to directly describe the coupling of polarons with lattice vibrations. Contrary to the Ihle-Lorentz small-polaron model,

Gabriella D. Franco, Marta C. Couto, Vítor V. Vasconcelos, Fernando P. Santos

Recommendation algorithms, used in online social networks, shape interactions between users. In particular, link-recommendation algorithms suggest new connections and affect how individuals interact and exchange information. These algorithms' efficacy relies on key mechanisms governing the creation of social ties, such as triadic closure and homophily. The f

Jialang Ding, Guanhong Lin, Dejia Zhou, Jianli Zhang

We present a Python/CuPy FX software correlator for small radio interferometer arrays and evaluate it on QUEST (Qilu University Explorer Survey Telescope). The system combines multi-threaded data ingest, pinned-memory host-device transfers, GPU-accelerated correlation, Polyphase Filter Bank channelization, MAD-based RFI flagging, and delay/phase calibration

Dominik Soós, Marc Paterno, John Stenger, Nikos Chrisochoides

Optimization problems become fundamentally challenging as the number of variables increases. Because the volume of the search space grows exponentially, classical algorithms frequently fail to locate the global minimum of non-convex functions. While quantum optimization offers a potential alternative, mapping continuous problems onto near-term quantum hardwa

Chetan Choppali Sudarshan, Aman Arora, Vidya A Chhabria

Climate change concerns emphasize the need for sustainable computing. Modeling the carbon footprint (CFP), including operational and embodied CFP from semiconductor use, manufacture and design, is essential. Field programmable gate arrays (FPGAs) stand out as promising platforms due to their reconfigurability across various applications, enabling the amortiz

Abdul Rahman

We study finite-node conifold degenerations of Calabi--Yau threefolds from the point of view of interacting light sectors. Although each ordinary double point contributes a rank-one local vanishing sector, the corrected global object need not assemble as a freely independent sum of nodewise pieces. Using the corrected perverse and mixed-Hodge-module degenera

François Gay-Balmaz, Cheng Yang

Hamilton's principle plays a central role in fluid mechanics as a fundamental tool for deriving governing equations, analyzing conservation laws, and designing structure-preserving numerical schemes. However, its classical formulation is restricted to smooth solutions and does not directly accommodate shock discontinuities. Addressing this limitation within

Grant Molnar

We define a multi-scale metric $d_\rho$ on strings by aggregating angle distances between all $n$-gram count vectors with exponential weights $\rho^n$. We benchmark $d_\rho$ in DBSCAN clustering against edit and $n$-gram baselines, give a linear-time suffix-tree algorithm for evaluation, prove metric and stability properties (including robustness under tande

M. Bonamente

A new method for including systematic errors in the regression with Poisson data is reviewed in this contribution, with emphasis on applications to astronomical spectra. The method consists of generalizing the usual Poisson log-likelihood, known as the Cash statistic $C_{min}$, and its associated likelihood-ratio statistic $\Delta C$, to include the presence

Jonathan Terhorst

The sequentially Markov coalescent (SMC) is a Markov jump process which models correlations in local genealogies across a chromosome. It has been used as a theoretical tool for studying linkage disequilibrium and identity-by-descent, and it also forms the basis of a class of statistical procedures for estimating population history and inferring ancestry. In

Joé Brendel, Jean-Philippe Chassé, Laurent Côté

Given a symplectic manifold, can one pack uncountably many Lagrangian submanifolds in a given Hamiltonian isotopy class of this symplectic manifold? We address $C^\infty$ and $C^0$ versions of this question.

Aravind Venugopal, Jiayu Chen, Xudong Wu, Chongyi Zheng

The temporal lag between actions and their long-term consequences makes credit assignment a challenge when learning goal-directed behaviors from data. Generative world models capture the distribution of future states an agent may visit, indicating that they have captured temporal information. How can that temporal information be extracted to perform credit a

Lukas Picek, Timm Haucke, Lukáš Adam, Ekaterina Nepovinnykh

Recognizing individual animals over time is central to many ecological and conservation questions, including estimating abundance, survival, movement, and social structure. Recent advances in automated identification from images and even acoustic data suggest that this process could be greatly accelerated, yet their promise has not translated well into ecolo

Sidi Wang, Kelley Kidwell, Bo Huang, Satrajit Roychoudhury

Overall survival (OS) is the gold standard for assessing patient benefit and cost-effectiveness of new cancer drugs. However, it is often difficult to use OS as the primary endpoint in randomized clinical trials (RCTs) for patients with metastatic cancer due to multiple reasons. In recent years, progression-free survival (PFS) has increasingly been used as t

Zhenming Zhang, Tianyu Li, Wei Yi

We propose a unified framework, dubbed topological word, for the complete non-Abelian bulk-boundary correspondence in multigap non-Abelian topological insulators. Composed by an ordered sequence of letters, each a non-Abelian charge depicting the gap-resolved topology, the topological word captures both the global non-Abelian topology corresponding to the ho

Mahmoud Abdelmoneum, Pierfrancesco Beneventano, Tomaso Poggio

We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific ideation, nor fully automated research. It is narrower and more practical: to reduce by orders of magnitude the human steering required to turn a specified hypothesis into a literature-grounded, mathematically es

Shahriar Rahman Khan, Tariqul Islam, Raiful Hasan

Autonomous vehicles (AVs) increasingly rely on multi-sensor perception pipelines that combine data from cameras, lidar, radar, and other modalities to interpret the environment. This SoK systematizes 48 peer-reviewed studies on perception-layer attacks against AVs, tracking the field's evolution from single-sensor exploits to complex cross-modal threats that

Masatake Yamada, Kurama Hirano, Masahiro Yabuno, Shigehito Miki

Interconnecting heterogeneous quantum systems is an important step toward realizing the quantum internet. We propose a quantum network hub that interfaces local quantum devices with dense wavelength-division multiplexing (DWDM) networks in the telecom band via quantum frequency conversion (QFC) with frequency-channel selectivity. We show that standard period

Arpan Bhattacharyya, S. Shajidul Haque, Jeff Murugan, Mpho Tladi

In closed quantum systems, Krylov complexity admits a geometric description; operator growth is equivalent to Hamiltonian flow in an emergent phase space whose structure is fixed by the Lanczos coefficients. We show that this picture survives, albeit in a fundamentally altered form, once the system is coupled to an environment.Using a Schwinger-Keldysh formu

Zhe-Hao Cao, Zhi-Yuan Chen, You-You Lin, Ji-Ying Wang

Strange hidden-charm pentaquark states have been systematically investigated within a diquark-triquark model. Through a Gaussian expansion method, masses of some diquarks, triquarks and strange hidden-charmed pentaquark states from S-wave to P-wave excitations have been calculated with the non-relativistic Semay and Silvestre-Brac potentials in terms of the

Dario Giandinoto, Boris Shapiro

Twisted Toeplitz matrices constitute a generalization of Toeplitz matrices in the sense that the entries on each diagonal no longer need to be constant, but are given by the values of a continuous function on a partition of $[0,1]$. We study the limiting statistical distribution of the eigenvalues of matrices of the form $R_n(a) = T_n(a) + \sigma_n X_n$, whe

Andrzej Rybicki

NA61/SHINE is a multipurpose, fixed-target spectrometer operating at the CERN SPS. The studied regime of collision energies, 5.1<\sqrt{s_{NN}}<16.8/27.4 GeV, places the project in-between the two main European heavy ion activities of the coming decade, the continued LHC (0.9<\sqrt{s_{NN}}<14 TeV) and the announced FAIR SIS100 (2.7<\sqrt{s_{NN}}<4.9 GeV) prog