Tootfinder

A Pseudo-Hermitian Hybrid Model at Finite Temperature: The Role of the Exceptional Points
Ignacio Fushimi (IFLP-UNLP, Argentina), Marta Reboiro (IFLP-UNLP, Argentina)
https://arxiv.org/abs/2510.08773

A Pseudo-Hermitian Hybrid Model at Finite Temperature: The Role of the Exceptional Points
We study a hybrid system formed by an ensemble of colour nitrogen-vacancy centres in diamond interacting with a superconducting flux-qubit at finite temperature. The presence of impurities in the system is modelled through pseudo-hermitian Hamiltonian, by introducing an asymmetry parameter in the interaction between the superconducting flux qubit and the ensemble of colour nitrogen-vacancy centres in diamond. We construct the exact grand partition function of the system, and from it we derive t…

Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
Andrea Ponte, Luca Demetrio, Luca Oneto, Ivan Tesfai Ogbu, Battista Biggio, Fabio Roli
https://arxiv.org/abs/2508.09652

Demystifying the Role of Rule-based Detection in AI Systems for Windows Malware Detection
Malware detection increasingly relies on AI systems that integrate signature-based detection with machine learning. However, these components are typically developed and combined in isolation, missing opportunities to reduce data complexity and strengthen defenses against adversarial EXEmples, carefully crafted programs designed to evade detection. Hence, in this work we investigate the influence that signature-based detection exerts on model training, when they are included inside the training…

KG-Attention: Knowledge Graph-Guided Attention at Test-Time via Bidirectional Information Aggregation
Songlin Zhai, Guilin Qi, Yuan Meng
https://arxiv.org/abs/2507.08704

KG-Attention: Knowledge Graph-Guided Attention at Test-Time via Bidirectional Information Aggregation
Knowledge graphs (KGs) play a critical role in enhancing large language models (LLMs) by introducing structured and grounded knowledge into the learning process. However, most existing KG-enhanced approaches rely on parameter-intensive fine-tuning, which risks catastrophic forgetting and degrades the pretrained model's generalization. Moreover, they exhibit limited adaptability to real-time knowledge updates due to their static integration frameworks. To address these issues, we introduce the f…

Understanding Pedestrian Gesture Misrecognition: Insights from Vision-Language Model Reasoning
Tram Thi Minh Tran, Xinyan Yu, Callum Parker, Julie Stephany Berrio Perez, Stewart Worrall, Martin Tomitsch
https://arxiv.org/abs/2508.06801

Understanding Pedestrian Gesture Misrecognition: Insights from Vision-Language Model Reasoning
Pedestrian gestures play an important role in traffic communication, particularly in interactions with autonomous vehicles (AVs), yet their subtle, ambiguous, and context-dependent nature poses persistent challenges for machine interpretation. This study investigates these challenges by using GPT-4V, a vision-language model, not as a performance benchmark but as a diagnostic tool to reveal patterns and causes of gesture misrecognition. We analysed a public dataset of pedestrian-vehicle interact…

Collateral and Reputation in a Model of Strategic Defaults
Georgy Lukyanov
https://arxiv.org/abs/2509.08849 https://arxiv.org/pdf/2509.08849

Collateral and Reputation in a Model of Strategic Defaults
This paper builds a finite-horizon model to study the role of physical collateral in a model of strategic defaults, when the borrower can develop reputation for honesty. Asset ownership increases attractiveness of the reputational channel: the borrower who would prefer to remain in autarky in the absence of the asset prefers to apply for collateralized debt. Pledging the asset as collateral facilitates reputation building, which is especially successful at the times of asset price drops, becaus…

Resolving the Structural Duality of Graphene Grain Boundaries
Haojie Guo, Emiliano Ventura-Mac\'ias, Mariano D. Jim\'enez-S\'anchez, Nicoleta Nicoara, Pierre Mallet, Jean-Yves Veuillen, Vincent T. Renard, Antonio J. Mart\'inez-Galera, Pablo Pou, Julio G\'omez-Herrero, Rub\'en P\'erez, Iv\'an Brihuega
https://

Resolving the Structural Duality of Graphene Grain Boundaries
Grain boundaries (GBs) are ubiquitous in large-scale graphene samples, playing a crucial role in their overall performance. Due to their complexity, they are usually investigated as model structures, under the assumption of a fully relaxed interface. Here, we present cantilever-based non-contact atomic force microscopy (ncAFM) as a suitable technique to resolve, atom by atom, the complete structure of these linear defects. Our experimental findings reveal a richer scenario than expected, with t…

The 17-year-old son watched as ICE ripped his father from him.
“It all felt like a lot to bear,” David told the Youth Media Project.
“He’s my role model, my biggest supporter. I rely on him a lot.”
The officer took all of Hector’s belongings, including $200 in cash he was carrying.
They did, however, forget to confiscate his phone, which Hector kept on him during his detainment.
David watched his dad step into the backseat of the blacked-out SUV.
As it sped …

ICE Stranded a 17-Year-Old on I-20 After Arresting His Father. The Mississippi Dad Now Faces Deportation.
A 17-year-old watched as ICE arrested his immigrant father, Hector, on I-20 in June. The family faces mounting legal fees and the risk of deportation.

Trispectrum in Extended USR Model with Transition to SR
Hassan Firouzjahi, Amin Nassiri-Rad
https://arxiv.org/abs/2509.09608 https://arxiv.org/pdf/2509.096…

Trispectrum in Extended USR Model with Transition to SR
We study the trispectrum in a two-phase USR-SR setup of inflation in which the USR stage is extended in the initial phase of inflation while the second stage of inflation proceeds via a slow-roll phase. A key role is played by the sharpness parameter which controls how quickly the system reaches the final attractor phase after the USR stage. We employ both $δN$ and in-in formalisms and calculate trispectrum and the corresponding dimensionless parameters $g_{NL}$ and $τ_{NL}$. We show that bot…

Soil Texture Prediction with Bayesian Generalized Additive Models for Spatial Compositional Data
Joaqu\'in Mart\'inez-Minaya, Lore Zumeta-Olaskoaga, Dae-Jin Lee
https://arxiv.org/abs/2508.07708

Soil Texture Prediction with Bayesian Generalized Additive Models for Spatial Compositional Data
Compositional data (CoDa) plays an important role in many fields such as ecology, geology, or biology. The most widely used modeling approaches are based on the Dirichlet and the logistic-normal formulation under Aitchison geometry. Recent developments in the mathematical field on the simplex geometry allow to express the regression model in terms of coordinates and estimate its coefficients. Once the model is projected in the real space, we can employ a multivariate Gaussian regression to deal…

Neutrino fog in the light dark sector: the role of isospin violation
V\'ictor Mart\'in Lozano, Shankar Pramanik, Soumya Sadhukhan, Adri\'an Terrones
https://arxiv.org/abs/2508.05787

Neutrino fog in the light dark sector: the role of isospin violation
Dark matter (DM) direct detection is now standing at an interesting juncture, where the Standard Model (SM) neutrino background and the upper bound on the DM signal cross section are starting to overlap in the DM mass region around 10 GeV. The neutrino floor, which defines the extent of the neutrino background, can be modified in different Beyond Standard Model (BSM) setups. We work in a simple BSM dark sector extension of the SM visible sector, where isospin-violating interactions occur natura…

A Brief Introduction to Quantum Query Complexity
Yassine Hamoudi
https://arxiv.org/abs/2508.08852 https://arxiv.org/pdf/2508.08852

A Brief Introduction to Quantum Query Complexity
Quantum query complexity is a fundamental model for analyzing the computational power of quantum algorithms. It has played a key role in characterizing quantum speedups, from early breakthroughs such as Grover's and Simon's algorithms to more recent developments in quantum cryptography and complexity theory. This document provides a structured introduction to quantum query lower bounds, focusing on four major techniques: the hybrid method, the polynomial method, the recording method, and the ad…

Mitigating Overthinking through Reasoning Shaping
Feifan Song, Shaohang Wei, Bofei Gao, Yejie Wang, Wen Luo, Wei Li, Linli Yao, Weimin Xiong, Liang Chen, Tianyu Liu, Houfeng Wang
https://arxiv.org/abs/2510.09535

Mitigating Overthinking through Reasoning Shaping
Large reasoning models (LRMs) boosted by Reinforcement Learning from Verifier Reward (RLVR) have shown great power in problem solving, yet they often cause overthinking: excessive, meandering reasoning that inflates computational cost. Prior designs of penalization in RLVR manage to reduce token consumption while often harming model performance, which arises from the oversimplicity of token-level supervision. In this paper, we argue that the granularity of supervision plays a crucial role in ba…

Affordance-R1: Reinforcement Learning for Generalizable Affordance Reasoning in Multimodal Large Language Model
Hanqing Wang, Shaoyang Wang, Yiming Zhong, Zemin Yang, Jiamin Wang, Zhiqing Cui, Jiahao Yuan, Yifan Han, Mingyu Liu, Yuexin Ma
https://arxiv.org/abs/2508.06206

Affordance-R1: Reinforcement Learning for Generalizable Affordance Reasoning in Multimodal Large Language Model
Affordance grounding focuses on predicting the specific regions of objects that are associated with the actions to be performed by robots. It plays a vital role in the fields of human-robot interaction, human-object interaction, embodied manipulation, and embodied perception. Existing models often neglect the affordance shared among different objects because they lack the Chain-of-Thought(CoT) reasoning abilities, limiting their out-of-domain (OOD) generalization and explicit reasoning capabili…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Rohith Mahadevan
https://arxiv.org/abs/2510.06987 https://arxiv.org/pdf/2510.06987…

Spiral Model Technique For Data Science & Machine Learning Lifecycle
Analytics play an important role in modern business. Companies adapt data science lifecycles to their culture to seek productivity and improve their competitiveness among others. Data science lifecycles are fairly an important contributing factor to start and end a project that are data dependent. Data science and Machine learning life cycles comprises of series of steps that are involved in a project. A typical life cycle states that it is a linear or cyclical model that revolves around. It is…

Coarsening model of chromosomal crossover placement
Marcel Ernst, Riccardo Rossetto, David Zwicker
https://arxiv.org/abs/2509.09521 https://arxiv.org/pdf/2…

Coarsening model of chromosomal crossover placement
Chromosomal crossovers play a crucial role in meiotic cell division, as they ensure proper chromosome segregation and increase genetic variability. Experiments have consistently revealed two key observations across species: (i) the number of crossovers per chromosome is typically small, but at least one, and (ii) crossovers on the same chromosome are subject to interference, i.e., they are more separated than expected by chance. These observations can be explained by a recently proposed coarsen…

First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Liwei Kang, Yue Deng, Yao Xiao, Zhanfeng Mo, Wee Sun Lee, Lidong Bing
https://arxiv.org/abs/2510.08308 h…

First Try Matters: Revisiting the Role of Reflection in Reasoning Models
Large language models have recently demonstrated significant gains in reasoning ability, often attributed to their capacity to generate longer chains of thought and engage in reflective reasoning. However, the contribution of reflections to performance improvement remains unclear. In this paper, we systematically analyze the rollouts of eight reasoning models on five mathematical datasets. We focus on reflective behaviours where the model has already produced an answer but continues reflecting …

Regularization in Data-driven Predictive Control: A Convex Relaxation Perspective
Xu Shang, Yang Zheng
https://arxiv.org/abs/2509.09027 https://arxiv.org/p…

Regularization in Data-driven Predictive Control: A Convex Relaxation Perspective
This paper explores the role of regularization in data-driven predictive control (DDPC) through the lens of convex relaxation. Using a bi-level optimization framework, we model system identification as an inner problem and predictive control as an outer problem. Within this framework, we show that several regularized DDPC formulations, including l1-norm penalties, projection-based regularizers, and a newly introduced causality-based regularizer, can be viewed as convex relaxations of their resp…

MIND: A Noise-Adaptive Denoising Framework for Medical Images Integrating Multi-Scale Transformer
Tao Tang, Chengxu Yang
https://arxiv.org/abs/2508.07817 https://

MIND: A Noise-Adaptive Denoising Framework for Medical Images Integrating Multi-Scale Transformer
The core role of medical images in disease diagnosis makes their quality directly affect the accuracy of clinical judgment. However, due to factors such as low-dose scanning, equipment limitations and imaging artifacts, medical images are often accompanied by non-uniform noise interference, which seriously affects structure recognition and lesion detection. This paper proposes a medical image adaptive denoising model (MI-ND) that integrates multi-scale convolutional and Transformer architecture…

DARAS: Dynamic Audio-Room Acoustic Synthesis for Blind Room Impulse Response Estimation
Chunxi Wang, Maoshen Jia, Wenyu Jin
https://arxiv.org/abs/2507.08135

DARAS: Dynamic Audio-Room Acoustic Synthesis for Blind Room Impulse Response Estimation
Room Impulse Responses (RIRs) accurately characterize acoustic properties of indoor environments and play a crucial role in applications such as speech enhancement, speech recognition, and audio rendering in augmented reality (AR) and virtual reality (VR). Existing blind estimation methods struggle to achieve practical accuracy. To overcome this challenge, we propose the dynamic audio-room acoustic synthesis (DARAS) model, a novel deep learning framework that is explicitly designed for blind RI…

The role of near neutron drip-line nuclei in the $r$-process
T. Yu, Y. Y. Guo, X. F. Jiang, X. H. Wu
https://arxiv.org/abs/2509.09478 https://arxiv.org/pdf…

The role of near neutron drip-line nuclei in the $r$-process
The role of near neutron-drip-line nuclei in the rapid neutron-capture process ($r$-process) is studied with the classical $r$-process model. Simulations under different astrophysical conditions ($T$, $n_n$) show that $r$-process paths approach the neutron-drip line under low-temperature and high-neutron-density conditions. A sensitivity study reveals that variations in the nuclear masses of these exotic nuclei significantly impact the abundances of superheavy nuclei, and lead to obvious ab…

Generative Bid Shading in Real-Time Bidding Advertising
Yinqiu Huang, Hao Ma, Wenshuai Chen, Shuli Wang, Yongqiang Zhang, Xue Wei, Yinhua Zhu, Haitao Wang, Xingxing Wang
https://arxiv.org/abs/2508.06550

Generative Bid Shading in Real-Time Bidding Advertising
Bid shading plays a crucial role in Real-Time Bidding~(RTB) by adaptively adjusting the bid to avoid advertisers overspending. Existing mainstream two-stage methods, which first model bid landscapes and then optimize surplus using operations research techniques, are constrained by unimodal assumptions that fail to adapt for non-convex surplus curves and are vulnerable to cascading errors in sequential workflows. Additionally, existing discretization models of continuous values ignore the depend…

A New Hybrid Model of Generative Adversarial Network and You Only Look Once Algorithm for Automatic License-Plate Recognition
Behnoud Shafiezadeh, Amir Mashmool, Farshad Eshghi, Manoochehr Kelarestaghi
https://arxiv.org/abs/2509.06868

A New Hybrid Model of Generative Adversarial Network and You Only Look Once Algorithm for Automatic License-Plate Recognition
Automatic License-Plate Recognition (ALPR) plays a pivotal role in Intelligent Transportation Systems (ITS) as a fundamental element of Smart Cities. However, due to its high variability, ALPR faces challenging issues more efficiently addressed by deep learning techniques. In this paper, a selective Generative Adversarial Network (GAN) is proposed for deblurring in the preprocessing step, coupled with the state-of-the-art You-Only-Look-Once (YOLO)v5 object detection architectures for License-Pl…

Fascinating results from modelling different charging strategies (dumb, smart, #V2G) for 15 million BEVs in Germany in 2030, this research by Adeline Guéret, Carlos Gaete-Morales and @….
At 50% V2G, the system costs are lower than in the situation without EVs.

A moderate share of V2G outperforms large-scale smart charging of electric vehicles and benefits other consumers
While battery electric vehicles (BEVs) play a key role for decarbonizing the transport sector, their impact on the power sector heavily depends on their charging strategies. Here we systematically analyze various combinations between inflexible, smart and bidirectional (or vehicle-to-grid, V2G) charging of 15 million electric cars in Germany. Using a capacity expansion model, we find that even a moderate share of bidirectional charging below 30% leads to lower system costs than a fully smartly …

Efficient High-Order Participation Factor Computation via Batch-Structured Tensor Contraction
Mahsa Sajjadi, Kaiyang Huang, Kai Sun
https://arxiv.org/abs/2509.08968 https://

Efficient High-Order Participation Factor Computation via Batch-Structured Tensor Contraction
Participation factors (PFs) quantify the interaction between system modes and state variables, and they play a crucial role in various applications such as modal analysis, model reduction, and control design. With increasing system complexity, especially due to power electronic devices and renewable integration, the need for scalable and high-order nonlinear PF (NPF) computation has become more critical. This paper presents an efficient tensor-based method for calculating NPFs up to an arbitrar…

ELEC: Efficient Large Language Model-Empowered Click-Through Rate Prediction
Rui Dong, Wentao Ouyang, Xiangzheng Liu
https://arxiv.org/abs/2509.07594 https://

ELEC: Efficient Large Language Model-Empowered Click-Through Rate Prediction
Click-through rate (CTR) prediction plays an important role in online advertising systems. On the one hand, traditional CTR prediction models capture the collaborative signals in tabular data via feature interaction modeling, but they lose semantics in text. On the other hand, Large Language Models (LLMs) excel in understanding the context and meaning behind text, but they face challenges in capturing collaborative signals and they have long inference latency. In this paper, we aim to leverage …

Formation and Regulation of Calcium Sparks on a Nonlinear Spatial Network of Ryanodine Receptors
Tian-Tian Li, Zhong-Xue Gao, Zuo-Ming Ding, Han-Yu Jiang, Jun He
https://arxiv.org/abs/2507.08258

Formation and Regulation of Calcium Sparks on a Nonlinear Spatial Network of Ryanodine Receptors
Accurate regulation of calcium release is essential for cellular signaling, with the spatial distribution of ryanodine receptors (RyRs) playing a critical role. In this study, we present a nonlinear spatial network model that simulates RyR spatial organization to investigate calcium release dynamics by integrating RyR behavior, calcium buffering, and calsequestrin (CSQ) regulation. The model successfully reproduces calcium sparks, shedding light on their initiation, duration, and termination me…

Designing de novo TIM Barrels: Insights into Stabilization, Diversification, and Functionalization Strategies
Julian Beck, Sergio Romero-Romero
https://arxiv.org/abs/2508.05699 …

Designing de novo TIM Barrels: Insights into Stabilization, Diversification, and Functionalization Strategies
The TIM-barrel fold is one of the most versatile and ubiquitous protein folds in nature, hosting a wide variety of catalytic activities and functions while serving as a model system in protein biochemistry and engineering. This review explores its role as a key fold model in protein design, particularly in addressing challenges in stabilization and functionalization. We discuss historical and recent advances in de novo TIM barrel design from the landmark creation of sTIM11 to the development of…

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Personality-Enhanced Social Recommendations in SAMI: Exploring the Role of Personality Detection in Matchmaking
Brittany Harbison, Samuel Taubman, Travis Taylor, Ashok. K. Goel
https://arxiv.org/abs/2509.09583

Personality-Enhanced Social Recommendations in SAMI: Exploring the Role of Personality Detection in Matchmaking
Social connection is a vital part of learning, yet online course environments present barriers to the organic formation of social groups. SAMI offers one solution by facilitating student connections, but its effectiveness is constrained by an incomplete Theory of Mind, limiting its ability to create an effective mental model of a student. One facet of this is its inability to intuit personality, which may influence the relevance of its recommendations. To explore this, we propose a personality …

The role of the initial distribution in population survival within a bounded habitat
Rafael de la Rosa, Elena Medina
https://arxiv.org/abs/2509.06179 https://

The role of the initial distribution in population survival within a bounded habitat
In this paper, we analyze the role of initial conditions in population persistence. Specifically, we consider the reaction-diffusion equation $u_t\,=\,D\,(u^{ν-1}\,u_x)_x\,+\,a\,u^μ$, with $μ,ν>0$, accompanied by hostile boundary conditions and examine two families of one-parametric initial distributions, including homogeneous distributions. The model was previously studied by Colombo and Anteneodo (2018). They determined appropriate habitat sizes $l$ for the survival of a population, whose…

Nonreciprocal Model B: The role of mobilities and nonreciprocal interfacial forces
Bibhut Sahoo, Rituparno Mandal, Peter Sollich
https://arxiv.org/abs/2508.02814 https://…

Nonreciprocal Model B: The role of mobilities and nonreciprocal interfacial forces
We study a non-reciprocal version of Model B, as the continuum theory for non-reciprocal particle mixtures. In contrast to non-reciprocal Cahn-Hilliard models, it is important in this context to consider the dependence of mobility coefficients on the local concentrations. We show that a homogeneous state that is linearly stable for one form of the mobility can be unstable for a different form of mobility, an effect that would be impossible in equilibrium and implies a crucial role for mobilitie…

Controlling the Glass Transition through Active Fluctuating Interactions
Emir Sezik, Henry Alston, Thibault Bertrand
https://arxiv.org/abs/2509.07619 https://

Controlling the Glass Transition through Active Fluctuating Interactions
Fluctuating pairwise interactions are understood to drive fluid-like states in dense biological systems. These states find a broad range of functionalities, such as directing growth during morphogenesis and forming aggregates with heightened mechanical response. However, a tractable model capturing the role of microscopic fluctuating interactions in these structural transitions is crucially lacking. Here, we study a $p$-spin model with fluctuating pairwise couplings (of strength $D_a$ and persi…

A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions
Toan Huynh, Ruth Lopez Fajardo, Guannan Zhang, Lili Ju, Feng Bao
https://arxiv.org/abs/2508.06834

A Score-based Diffusion Model Approach for Adaptive Learning of Stochastic Partial Differential Equation Solutions
We propose a novel framework for adaptively learning the time-evolving solutions of stochastic partial differential equations (SPDEs) using score-based diffusion models within a recursive Bayesian inference setting. SPDEs play a central role in modeling complex physical systems under uncertainty, but their numerical solutions often suffer from model errors and reduced accuracy due to incomplete physical knowledge and environmental variability. To address these challenges, we encode the governin…

Gravity Well Echo Chamber Modeling With An LLM-Based Confirmation Bias Model
Joseph Jackson, Georgiy Lapin, Jeremy E. Thompson
https://arxiv.org/abs/2509.03832 https://

Gravity Well Echo Chamber Modeling With An LLM-Based Confirmation Bias Model
Social media echo chambers play a central role in the spread of misinformation, yet existing models often overlook the influence of individual confirmation bias. An existing model of echo chambers is the "gravity well" model, which creates an analog between echo chambers and spatial gravity wells. We extend this established model by introducing a dynamic confirmation bias variable that adjusts the strength of pull based on a user's susceptibility to belief-reinforcing content. This variable is …

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Sibel \"Ortel, Mutlu Y{\i}ld{\i}z
https://arxiv.org/abs/2510.02931 https://arxiv…

The Role of Asteroseismology in Understanding Mass Loss in Red Giants
Red giant stars play a key role in advancing our understanding of stellar mass loss. However, its initial mass and the amount of mass lost during this phase remain uncertain. In this study, we investigate the asteroseismic signatures of mass loss and the parameters that influence it. We examine six stars identified as red giant branch (RGB) stars in the APOKASC-2 catalog. Assuming these stars are on their first ascent of the RGB, we construct interior models. The resulting model ages are signif…

Influence of Large Mean Delay on Distributed Delay Differential Equations Dynamics: Application to a Neural Mass Model
Isam Al-Darabsah, Sue Ann Campbell, Bootan Rahman
https://arxiv.org/abs/2509.05466

Influence of Large Mean Delay on Distributed Delay Differential Equations Dynamics: Application to a Neural Mass Model
Delay differential equations (DDEs) with large delays play a pivotal role in understanding stability and bifurcations in systems ranging from neural networks to laser dynamics. While prior work has extensively studied DDEs with discrete delays, the impact of distributed delays has been less explored. This paper investigates the spectrum of linear DDEs with a uniformly distributed delay kernel, with mean delay $τ_m$ and a half-width of $ρ$. When $τ_m\to\infty$, we carry out asymptotic analysi…

Design and Implementation of a Domain-specific Language for Modelling Evacuation Scenarios Using Eclipse EMG/GMF Tool
Heerok Banerjee
https://arxiv.org/abs/2509.06688 https://…

Design and Implementation of a Domain-specific Language for Modelling Evacuation Scenarios Using Eclipse EMG/GMF Tool
Domain-specific languages (DSLs) play a crucial role in resolving internal dependencies across enterprises and boosts their upfront business management processes. Yet, a lot of development is needed to build modelling frameworks which support graphical interfaces (canvas, pallettes etc.), hierarchical structures and easy implementation to shorten the gap for novice users. In this paper, a DSL namely, Bmod is introduced, which can be used to model evacuation scenarios. The language is built usin…

Antikaon absorption in the nuclear medium: the role of hadron self-energies and implications for kaonic atoms
J. \'Obertov\'a, \`A. Ramos, J. Mare\v{s}
https://arxiv.org/abs/2508.07921

Antikaon absorption in the nuclear medium: the role of hadron self-energies and implications for kaonic atoms
A systematic study of all relevant in-medium effects on the total $K^-$-nuclear potential is presented in this work. The $K^-N$ scattering amplitudes, including Pauli blocking effects and hadron self-energies (hyperons, nucleons, pions and kaons), are derived within a next-to-leading order chiral meson-baryon coupled-channel interaction model. These amplitudes are employed in a microscopic model of the $K^-$-nuclear potential in symmetric nuclear matter that includes one-, two- and, when the ka…

Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
Sarah H. Cen, Salil Goyal, Zaynah Javed, Ananya Karthik, Percy Liang, Daniel E. Ho
https://arxiv.org/abs/2509.05627

Audits Under Resource, Data, and Access Constraints: Scaling Laws For Less Discriminatory Alternatives
AI audits play a critical role in AI accountability and safety. One branch of the law for which AI audits are particularly salient is anti-discrimination law. Several areas of anti-discrimination law implicate the "less discriminatory alternative" (LDA) requirement, in which a protocol (e.g., model) is defensible if no less discriminatory protocol that achieves comparable performance can be found with a reasonable amount of effort. Notably, the burden of proving an LDA exists typically falls on…

Microscopic calculation of two-particle-two-hole meson-exchange currents in $^{40}$Ar and asymmetric scaling properties for neutrino and electron scattering
V. L. Martinez-Consentino, J. Segovia, J. E. Amaro
https://arxiv.org/abs/2509.08916

Microscopic calculation of two-particle-two-hole meson-exchange currents in $^{40}$Ar and asymmetric scaling properties for neutrino and electron scattering
We present a microscopic calculation of two particle-two hole meson exchange current response functions in asymmetric nuclei, with particular emphasis on the $^{40}$Ar nucleus. Employing a relativistic mean-field and relativistic Fermi gas framework, we compute the nuclear response for $^{40}$Ar and compare it with that of the symmetric $^{40}$Ca nucleus, analyzing the role of proton-neutron imbalance. The model incorporates distinct proton and neutron Fermi momenta to accurately capture the nu…

Interpolation in model theory
Jouko V\"a\"an\"anen
https://arxiv.org/abs/2507.19097 https://arxiv.org/pdf/2507.19097

Interpolation in model theory
We bring an abstract model theory perspective to interpolation. We ask, what is the role of interpolation in the study of extensions of first order logic, such as infinitary logics, generalized quantifiers and higher order logics? The abstract model theory approach reveals the basic connections between various interpolation properties in isolation, on their own, as well as with respect to other model theoretic properties, such as compactness.

Likelihood-based inference for the Gompertz model with Poisson errors
Paolo Onorati, Sofia Ruiz-Suarez, Radu Craiu
https://arxiv.org/abs/2510.06787 https://

Likelihood-based inference for the Gompertz model with Poisson errors
Population dynamics models play an important role in a number of fields, such as actuarial science, demography, and ecology. Statistical inference for these models can be difficult when, in addition to the process' inherent stochasticity, one also needs to account for sampling error. Ignoring the latter can lead to biases in the estimation, which in turn can produce erroneous conclusions about the system's behavior. The Gompertz model is widely used to infer population size dynamics, but a full…

Decarbonizing Basic Chemicals Production in North America, Europe, Middle East, and China: a Scenario Modeling Study
Tubagus Aryandi Gunawan, Hongxi Luo, Chris Greig, Eric D. Larson
https://arxiv.org/abs/2509.08279

Decarbonizing Basic Chemicals Production in North America, Europe, Middle East, and China: a Scenario Modeling Study
The chemicals industry accounts for about 5% of global greenhouse gas emissions today and is among the most difficult industries to abate. We model decarbonization pathways for the most energy-intensive segment of the industry, the production of basic chemicals: olefins, aromatics, methanol, ammonia, and chlor-alkali. Unlike most prior pathways studies, we apply a scenario-analysis approach that recognizes the central role of corporate investment decision making for capital-intensive industries…

Cavity-induced Eliashberg effect: superconductivity vs charge density wave
Md Mursalin Islam, Michele Pini, R. Flores-Calder\'on, Francesco Piazza
https://arxiv.org/abs/2509.07865

Cavity-induced Eliashberg effect: superconductivity vs charge density wave
Recent experiments have shown that non-equilibrium effects can play a key role in cavity-based control of material phases, notably in systems with charge-density-wave order. Motivated by this, we extend the theory of the Eliashberg effect, originally developed for superconducting phases, to charge-density-wave phases. Starting from a minimal electronic model where superconductivity and charge-density-wave order are equivalent at equilibrium, we introduce coupling to cavity photons, which are in…

Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animals
Bertrand Cloez, Adrien Cotil, Jean-Baptiste Menassol, Nicolas Verzelen
https://arxiv.org/abs/2509.15989

Model-free algorithms for fast node clustering in SBM type graphs and application to social role inference in animals
We propose a novel family of model-free algorithms for node clustering and parameter inference in graphs generated from the Stochastic Block Model (SBM), a fundamental framework in community detection. Drawing inspiration from the Lloyd algorithm for the $k$-means problem, our approach extends to SBMs with general edge weight distributions. We establish the consistency of our estimator under a natural identifiability condition. Through extensive numerical experiments, we benchmark our methods a…

Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms
Yushang Zhao, Yike Peng, Li Zhang, Qianyi Sun, Zhihui Zhang, Yingying Zhuang
https://arxiv.org/abs/2509.04751

Multimodal Foundation Model-Driven User Interest Modeling and Behavior Analysis on Short Video Platforms
With the rapid expansion of user bases on short video platforms, personalized recommendation systems are playing an increasingly critical role in enhancing user experience and optimizing content distribution. Traditional interest modeling methods often rely on unimodal data, such as click logs or text labels, which limits their ability to fully capture user preferences in a complex multimodal content environment. To address this challenge, this paper proposes a multimodal foundation model-based…

Does This Look Familiar to You? Knowledge Analysis via Model Internal Representations
Sihyun Park
https://arxiv.org/abs/2509.07311 https://arxiv.org/pdf/25…

Does This Look Familiar to You? Knowledge Analysis via Model Internal Representations
Recent advances in large language models (LLMs) have been driven by pretraining, supervised fine tuning (SFT), and alignment tuning. Among these, SFT plays a crucial role in transforming a model 's general knowledge into structured responses tailored to specific tasks. However, there is no clearly established methodology for effective training data selection. Simply increasing the volume of data does not guarantee performance improvements, while preprocessing, sampling, and validation require s…

“Extensive bidirectional charging functions are also available for the new BMW iX3, meaning that it can be used as an energy supply source for a variety of applications. The Vehicle-to-Load (V2L) function turns the new BMW iX3 into a mobile powerbank, which can supply electric devices with power while on the move. Vehicle-to-Home (V2H) hands it the role of storage unit for solar energy generated by home-fitted photovoltaic systems. [1/2]

The start of a new era. The new BMW iX3.
BMW presents the first series-produced Neue Klasse model. The new-generation BMW iX3 is a fully electric Sports Activity Vehicle (SAV) that gives customers their first on-the-road taste of a whole new era of Sheer Driving Pleasure. An all-new design language gives the car a character-rich appearance that faithfully conveys the technological progress made by the new model. With sixth-generation BMW eDrive technology, a range of up to 805 kilometres (500 miles) and a peak charging rate of 400 kW,…

DeepMind: video models like Veo 3 could become general purpose foundation models for vision, like LLMs for text, using zero-shot "chain-of-frames" reasoning (Simon Willison/Simon Willison's Weblog)
https://simonwillison.net/2025/Sep/27/v…

Video models are zero-shot learners and reasoners
Fascinating new paper from Google DeepMind which makes a very convincing case that their Veo 3 model - and generative video models in general - serve a similar role in …

A CFD model for heat and mass transfer leading to plume formation within Wet Cooling Towers
Luc Favre (CEREA, ENPC), Martin Ferrand (CEREA, ENPC, EDF R,D MFEE)
https://arxiv.org/abs/2509.08394

A CFD model for heat and mass transfer leading to plume formation within Wet Cooling Towers
The crucial role played by Wet Cooling Towers (WCT) in many electricity production plants (e.g. nuclear power plants) make them a key parameter in the industrial design of such facilities. Their impact over the cooling water consumption and surrounding atmosphere through the formation and dispersion of a humid air plume has pushed the need to obtain proper models and simulations in order to anticipate those effects. In this work, we tackle this issue through a dedicated modelling in the CFD sol…

From Propagator to Oscillator: The Dual Role of Symmetric Differential Equations in Neural Systems
Kun Jiang
https://arxiv.org/abs/2507.22916 https://arxiv…

From Propagator to Oscillator: The Dual Role of Symmetric Differential Equations in Neural Systems
In our previous work, we proposed a novel neuron model based on symmetric differential equations and demonstrated its potential as an efficient signal propagator. Building upon that foundation, the present study delves deeper into the intrinsic dynamics and functional diversity of this model. By systematically exploring the parameter space and employing a range of mathematical analysis tools, we theoretically reveal the system 's core property of functional duality. Specifically, the model exhi…

Modeling the formation of N2 and CH4 frost on Pluto's slopes
L. Lange, T. Bertrand, V. Belissa, S. Capry, L. A. Young, A. Falco
https://arxiv.org/abs/2510.07003 https://

Modeling the formation of N2 and CH4 frost on Pluto's slopes
Context:Previous studies suggested that these frosts could result from the peculiar insolation driven by the geometry of these slopes, but this has never been quantitatively tested. We aim to investigate the origin, stability, and potential role in Pluto's volatile cycle of these localized frost deposits. Methods:We implemented a new sub-grid-scale slope parameterization in the Pluto Volatile Transport Model, which accounts for the specific solar irradiation and resulting surface and subsurfa…

Role of non-extensivity $q$-parameter in tectonic seismic forecasting
Oscar Sotolongo-Costa, Miguel Eduardo Mora-Ramos
https://arxiv.org/abs/2508.04932 https://

Role of non-extensivity $q$-parameter in tectonic seismic forecasting
By writing total Tsallis entropy as a function of non-extensivity q-parameter withing the fragment-asperity model for earthquakes, a critical range of values is identified: 1.4

The role of visual experience in haptic spatial perception: evidence from early blind, late blind, and sighted individuals #haptics

The role of visual experience in haptic spatial perception: evidence from early blind, late blind, and sighted individuals - Biology of Sex Differences
There is contradictory evidence on the effect that visual experience has on haptic abilities. Indeed, some studies have documented that a lack of vision (blindness) results in decreased haptic perception, whereas other studies report an enhanced haptic ability in blind individuals. To examine the role of vision in haptic spatial processing, we recruited early blind, late blind, and sighted participants. Each participant completed a haptic task in which they explored a two-piece LEGO model for e…

Analysing contrarian behaviour using nonlinear biased $q$-voter model
Amit Pradhan, Pratik Mullick, Parongama Sen
https://arxiv.org/abs/2509.01982 https://…

Analysing contrarian behaviour using nonlinear biased $q$-voter model
We investigate the role of contrarians in a recently proposed weighted-influence variant of the $q$-voter model. In this framework, non-unanimous influence groups affect the focal agent through weighted contributions governed by a bias parameter $p$. We extend this setting by introducing a fraction $α$ ($α> 0$) of contrarians, defined as agents who systematically oppose the prevailing influence irrespective of whether the group is unanimous or divided. Analytical mean-field calculations and M…

BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation
Rocktim Jyoti Das, Harsh Singh, Diana Turmakhan, Muhammad Abdullah Sohail, Mingfei Han, Preslav Nakov, Fabio Pizzati, Ivan Laptev
https://arxiv.org/abs/2510.08572

BLAZER: Bootstrapping LLM-based Manipulation Agents with Zero-Shot Data Generation
Scaling data and models has played a pivotal role in the remarkable progress of computer vision and language. Inspired by these domains, recent efforts in robotics have similarly focused on scaling both data and model size to develop more generalizable and robust policies. However, unlike vision and language, robotics lacks access to internet-scale demonstrations across diverse robotic tasks and environments. As a result, the scale of existing datasets typically suffers from the need for manual…

A Thermodynamic Model for Thermomigration in Metals
Daniel J. Long, Edmund Tarleton, Alan C. F. Cocks, Felix Hofmann
https://arxiv.org/abs/2508.05327 https://

A Thermodynamic Model for Thermomigration in Metals
We investigate the mechanisms involved in the thermomigration of interstitial hydrogen in metals. Using statistical thermodynamics, we develop a comprehensive mechanistic model to capture the controlling effects. Crucially, through validation against published experimental data, our results demonstrate that an electron-wind effect plays a significant role, particularly for materials in which the thermomigration direction matches the heat flux. These findings provide new insights into the factor…

Forgive and Forget? An Industry 5.0 Approach to Trust-Fatigue Co-regulation in Human-Cobot Order Picking
Soumyadeep Dhar
https://arxiv.org/abs/2508.03765 https://

Forgive and Forget? An Industry 5.0 Approach to Trust-Fatigue Co-regulation in Human-Cobot Order Picking
This paper investigates the critical role of trust and fatigue in human-cobot collaborative order picking, framing the challenge within the scope of Logistics 5.0 -- the implementation of human-robot symbiosis in smart logistics. We propose a dynamic, leader-follower Stackelberg game to model this interaction, where utility functions explicitly account for human fatigue and trust. Through agent-based simulations, we demonstrate that while a naive model leads to a "trust death spiral," a refined…

Enhancing cluster synchronization in phase-lagged multilayer networks
Abhijit Mondal, Pitambar Khanra, Subrata Ghosh, Prosenjit Kundu, Chittaranjan Hens, Pinaki Pal
https://arxiv.org/abs/2508.06502

Enhancing cluster synchronization in phase-lagged multilayer networks
Cluster synchronization in multilayer networks of phase oscillators with phase-lag poses significant challenges due to the destabilizing effects of delayed interactions. Leveraging the Sakaguchi-Kuramoto model, this study addresses these challenges by systematically exploring the role of natural frequency distributions in sustaining cluster synchronization under high phase-lag conditions. We focus on four distributions: uniform (uni-uni), partially degree-correlated (deg-uni, uni-deg), and full…

In the Queue: Understanding How Reddit Moderators Use the Modqueue
Tanvi Bajpai, Eshwar Chandrasekharan
https://arxiv.org/abs/2509.07314 https://arxiv.org/…

In the Queue: Understanding How Reddit Moderators Use the Modqueue
On Reddit, the moderation queue (modqueue) is a primary interface for moderators to review reported content. Despite its central role in Reddit's community-reliant moderation model, little is known about how moderators actually use it in practice. To address this gap, we surveyed 110 moderators, who collectively oversee more than 400 unique subreddits, and asked them about their usage of the modqueue. Modqueue practices vary widely: some moderators approach it as a daily checklist, others as a …

Electromechanical computational model of the human stomach
Maire S. Henke, Sebastian Brandstaeter, Sebastian L. Fuchs, Roland C. Aydin, Alessio Gizzi, Christian J. Cyron
https://arxiv.org/abs/2509.02486

Electromechanical computational model of the human stomach
The stomach plays a central role in digestion through coordinated muscle contractions, known as gastric peristalsis, driven by slow-wave electrophysiology. Understanding this process is critical for treating motility disorders such as gastroparesis, dyspepsia, and gastroesophageal reflux disease. Computer simulations can be a valuable tool to deepen our understanding of these disorders and help to develop new therapies. However, existing approaches often neglect spatial heterogeneity, fail to c…

Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration
Tengwei Song, Min Wu, Yuan Fang
https://arxiv.org/abs/2510.07035 https:/…

Unified Molecule Pre-training with Flexible 2D and 3D Modalities: Single and Paired Modality Integration
Molecular representation learning plays a crucial role in advancing applications such as drug discovery and material design. Existing work leverages 2D and 3D modalities of molecular information for pre-training, aiming to capture comprehensive structural and geometric insights. However, these methods require paired 2D and 3D molecular data to train the model effectively and prevent it from collapsing into a single modality, posing limitations in scenarios where a certain modality is unavailabl…

To break, or not to break: Symmetries in adaptive quantum simulations, a case study on the Schwinger model
Karunya Shailesh Shirali, Kyle Sherbert, Yanzhu Chen, Adrien Florio, Andreas Weichselbaum, Robert D. Pisarski, Sophia E. Economou
https://arxiv.org/abs/2510.03083

To break, or not to break: Symmetries in adaptive quantum simulations, a case study on the Schwinger model
We investigate the role of symmetries in constructing resource-efficient operator pools for adaptive variational quantum eigensolvers. In particular, we focus on the lattice Schwinger model, a discretized model of $1+1$ dimensional electrodynamics, which we use as a proxy for spin chains with a continuum limit. We present an extensive set of simulations comprising a total of $11$ different operator pools, which all systematically and independently break or preserve a combination of discrete tra…

Towards a classification of topological defects in $K3$ sigma models
Roberta Angius, Stefano Giaccari
https://arxiv.org/abs/2508.03612 https://arxiv.org/pd…

Towards a classification of topological defects in $K3$ sigma models
Given a $K3$ surface, a supersymmetric non-linear K3 sigma model is the internal superconformal field theory (SCFT) in a six dimensional compactification of type IIA superstring on $\mathbb{R}^{1,5} \times K3$. These models have attracted attention due to the discovery of Mathieu moonshine phenomena for the elliptic genera of K3 surfaces, and have played a pivotal role in extending Mukai's theorem on classification of symplectic automorphisms of $K3$ surfaces. We report on recent progress (arXi…

Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model
Hyun-kyu Ko, Youbin Kim, Jihyeon Park, Dongheok Park, Gyeongjin Kang, Wonjun Cho, Hyung Yi, Eunbyung Park
https://arxiv.org/abs/2510.00862

Gather-Scatter Mamba: Accelerating Propagation with Efficient State Space Model
State Space Models (SSMs)-most notably RNNs-have historically played a central role in sequential modeling. Although attention mechanisms such as Transformers have since dominated due to their ability to model global context, their quadratic complexity and limited scalability make them less suited for long sequences. Video super-resolution (VSR) methods have traditionally relied on recurrent architectures to propagate features across frames. However, such approaches suffer from well-known issue…

Membrane Heterogeneity Driven Dynamics of Multicomponent Vesicles in Shear Flow
Shuqi Tang, Steven M. Wise, John Lowengrub, Zhenlin Guo
https://arxiv.org/abs/2509.08295 https://…

Membrane Heterogeneity Driven Dynamics of Multicomponent Vesicles in Shear Flow
Despite their significance in biology and materials science, the dynamics of multicomponent vesicles under shear flow remain poorly understood because of their nonlinear and strongly coupled nature, especially regarding the role of membrane heterogeneity in driving nonequilibrium behavior. Here we present a thermodynamically consistent phase-field model, which is validated against experiments, for the quantitative investigation of these dynamics. While prior research has primarily focused on vi…

Flavour Physics Beyond the Standard Model
Wolfgang Altmannshofer, Peter Stangl
https://arxiv.org/abs/2508.03950 https://arxiv.org/pdf/2508.03950

Flavour Physics Beyond the Standard Model
Flavour physics plays a central role in the search for physics beyond the Standard Model, posing fundamental questions whose answers may point to new physics scales far above the electroweak scale. The flavour structure of the Standard Model is strikingly hierarchical, hinting at underlying organizing principles yet to be uncovered. At the same time, flavour-changing processes rank among the most sensitive probes of new physics. In this chapter, we review how precision measurements of flavour-v…

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Zecheng Tang, Baibei Ji, Quantong Qiu, Haitian Wang, Xiaobo Liang, Juntao Li, Min Zhang
https://arxiv.org/abs/2510.06915

LongRM: Revealing and Unlocking the Context Boundary of Reward Modeling
Reward model (RM) plays a pivotal role in aligning large language model (LLM) with human preferences. As real-world applications increasingly involve long history trajectories, e.g., LLM agent, it becomes indispensable to evaluate whether a model's responses are not only high-quality but also grounded in and consistent with the provided context. Yet, current RMs remain confined to short-context settings and primarily focus on response-level attributes (e.g., safety or helpfulness), while largel…

Probing departures from $\Lambda$CDM by late-time datasets
Himanshu Chaudhary, Vipin Kumar Sharma, Salvatore Capozziello, G. Mustafa
https://arxiv.org/abs/2510.08339 https://

Probing departures from $Λ$CDM by late-time datasets
Observational data play a pivotal role in identifying cosmological models that are both theoretically consistent and empirically viable. In this work, we investigate whether the standard $Λ$CDM model exhibits significant departure with current late time datasets, including Cosmic Chronometers, Baryon Acoustic Oscillations from DESI DR2, and various Type Ia supernova compilations (Pantheon$^+$, DES-SN5Y, Union3). We analyze several dynamical dark energy models, including $ω$CDM, o$ω$CDM, $ω_…

Understanding the Impact of Hydro-Reservoirs and Inverters on Frequency-Constrained Operation
Valeria Aravena, Samuel Cordova, Maximiliano Kairath, Matias Negrete-Pincetic
https://arxiv.org/abs/2510.06422

Understanding the Impact of Hydro-Reservoirs and Inverters on Frequency-Constrained Operation
The increasing participation of renewable energy sources in power systems has entailed a series of challenges resulting from the replacement of conventional synchronous machines with carbon-free Inverter-Based-Resources (IBRs). In this context, the present work contributes to the existing literature on Frequency-Constrained Unit Commitment (FCUC) models by studying the role of hydro-reservoirs in the ongoing decarbonization of power systems. For this purpose, a novel FCUC model is developed, wh…

A Measurement Study of Model Context Protocol
Hechuan Guo, Yongle Hao, Yue Zhang, Minghui Xu, Peizhuo Lyu, Jiezhi Chen, Xiuzhen Cheng
https://arxiv.org/abs/2509.25292 https://…

A Measurement Study of Model Context Protocol
The Model Context Protocol (MCP) has been proposed as a unifying standard for connecting large language models (LLMs) with external tools and resources, promising the same role for AI integration that HTTP and USB played for the Web and peripherals. Yet, despite rapid adoption and hype, its trajectory remains uncertain. Are MCP marketplaces truly growing, or merely inflated by placeholders and abandoned prototypes? Are servers secure and privacy-preserving, or do they expose users to systemic r…

We Have It Covered: A Resampling-based Method for Uplift Model Comparison
Yang Liu, Chaoyu Yuan
https://arxiv.org/abs/2509.04315 https://arxiv.org/pdf/2509…

We Have It Covered: A Resampling-based Method for Uplift Model Comparison
Uplift models play a critical role in modern marketing applications to help understand the incremental benefits of interventions and identify optimal targeting strategies. A variety of techniques exist for building uplift models, and it is essential to understand the model differences in the context of intended applications. The uplift curve is a widely adopted tool for assessing uplift model performance on the selection universe when observations are available for the entire population. Howeve…

Space-time Areas and Hadronization Studies
S. Abachi, C. Buchanan
https://arxiv.org/abs/2508.05784 https://arxiv.org/pdf/2508.05784

Space-time Areas and Hadronization Studies
Space-time area laws play a fundamental role in modeling strongly interacting phenomena, such as in relativistic string models, QCD on the lattice, and in hadronization modeling. For the latter, an exact expression for relevant space-time areas related to the final state hadronic events for hadrons of any mass is calculated. Usage of this expression in the UCLA hadronization model helps validate its space-time area law (STAL) principle and unifies the treatment of heavy and light hadrons via a …

The Magnetic Ground State of Atacamite Cu$_2$Cl(OH)$_3$: The Crucial Role of Frustrated Zigzag Chains Revealed by Inelastic Neutron Scattering
J. L. Allen, L. Heinze, R. A. Mole, S. S\"ullow, O. Janson, S. Nishimoto, R. A. Lewis, K. C. Rule
https://arxiv.org/abs/2508.02201

The Magnetic Ground State of Atacamite Cu$_2$Cl(OH)$_3$: The Crucial Role of Frustrated Zigzag Chains Revealed by Inelastic Neutron Scattering
We report inelastic neutron scattering (INS) measurements on the magnetically frustrated $S=\frac12$ sawtooth-chain compound atacamite Cu$_2$Cl(OH)$_3$ featuring inequivalent Cu(1) and Cu(2) sites. Transverse to the sawtooth chains, INS reveals two dispersive spin-wave modes and a gap of at least 0.75 meV. This behavior is rationalized within a zigzag-chain model of Cu(2) spins in an effective magnetic field of Cu(1) spins. The model is compatible with first-principles calculations and accounts…

Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate
Luis Enrique Coronas, Stepan Timr, Fabio Sterpone, Giancarlo Franzese
https://arxiv.org/abs/2510.06037

Unveiling the entropic role of hydration water in SOD1 partitioning within FUS condensate
Biological processes like the sequestration of Superoxide Dismutase 1 (SOD1) into biomolecular condensates such as FUS and stress granules are essential to understanding disease mechanisms, including amyotrophic lateral sclerosis (ALS). Our study demonstrates that the hydration environment is crucial in these processes. Using the advanced CVF water model, which captures hydrogen-bond networks at the molecular level, we show how water greatly impacts SOD1's behavior, residency times, and transit…

Planning Persuasive Trajectories Based on a Leader-Follower Game Model
Chaozhe R. He, Yichen Dong, Nan Li
https://arxiv.org/abs/2507.22022 https://arxiv.or…

Planning Persuasive Trajectories Based on a Leader-Follower Game Model
We propose a framework that enables autonomous vehicles (AVs) to proactively shape the intentions and behaviors of interacting human drivers. The framework employs a leader-follower game model with an adaptive role mechanism to predict human interaction intentions and behaviors. It then utilizes a branch model predictive control (MPC) algorithm to plan the AV trajectory, persuading the human to adopt the desired intention. The proposed framework is demonstrated in an intersection scenario. Simu…

Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
Mohammed A. Shehab
https://arxiv.org/abs/2510.02325 https://arxiv.org/pdf/2510…

Agentic-AI Healthcare: Multilingual, Privacy-First Framework with MCP Agents
This paper introduces Agentic-AI Healthcare, a privacy-aware, multilingual, and explainable research prototype developed as a single-investigator project. The system leverages the emerging Model Context Protocol (MCP) to orchestrate multiple intelligent agents for patient interaction, including symptom checking, medication suggestions, and appointment scheduling. The platform integrates a dedicated Privacy and Compliance Layer that applies role-based access control (RBAC), AES-GCM field-level e…

FUTransUNet-GradCAM: A Hybrid Transformer-U-Net with Self-Attention and Explainable Visualizations for Foot Ulcer Segmentation
Akwasi Asare, Mary Sagoe, Justice Williams Asare
https://arxiv.org/abs/2508.03758

FUTransUNet-GradCAM: A Hybrid Transformer-U-Net with Self-Attention and Explainable Visualizations for Foot Ulcer Segmentation
Automated segmentation of diabetic foot ulcers (DFUs) plays a critical role in clinical diagnosis, therapeutic planning, and longitudinal wound monitoring. However, this task remains challenging due to the heterogeneous appearance, irregular morphology, and complex backgrounds associated with ulcer regions in clinical photographs. Traditional convolutional neural networks (CNNs), such as U-Net, provide strong localization capabilities but struggle to model long-range spatial dependencies due to…

Comparing Cluster-Based Cross-Validation Strategies for Machine Learning Model Evaluation
Afonso Martini Spezia, Mariana Recamonde-Mendoza
https://arxiv.org/abs/2507.22299 https…

Comparing Cluster-Based Cross-Validation Strategies for Machine Learning Model Evaluation
Cross-validation plays a fundamental role in Machine Learning, enabling robust evaluation of model performance and preventing overestimation on training and validation data. However, one of its drawbacks is the potential to create data subsets (folds) that do not adequately represent the diversity of the original dataset, which can lead to biased performance estimates. The objective of this work is to deepen the investigation of cluster-based cross-validation strategies by analyzing the perform…

Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models
Zhanna Kaufman, Madeline Endres, Cindy Xiong Bearfield, Yuriy Brun
https://arxiv.org/abs/2508.00140

Your Model Is Unfair, Are You Even Aware? Inverse Relationship Between Comprehension and Trust in Explainability Visualizations of Biased ML Models
Systems relying on ML have become ubiquitous, but so has biased behavior within them. Research shows that bias significantly affects stakeholders' trust in systems and how they use them. Further, stakeholders of different backgrounds view and trust the same systems differently. Thus, how ML models' behavior is explained plays a key role in comprehension and trust. We survey explainability visualizations, creating a taxonomy of design characteristics. We conduct user studies to evaluate five sta…

Optimization via a Control-Centric Framework
Liraz Mudrik, Isaac Kaminer, Sean Kragelund, Abram H. Clark
https://arxiv.org/abs/2510.05455 https://arxiv.org…

Optimization via a Control-Centric Framework
Optimization plays a central role in intelligent systems and cyber-physical technologies, where the speed and reliability of convergence directly impact performance. In control theory, optimization-centric methods are standard: controllers are designed by repeatedly solving optimization problems, as in linear quadratic regulation, $H_\infty$ control, and model predictive control. In contrast, this paper develops a control-centric framework for optimization itself, where algorithms are construct…

Exploring Scaling Laws of CTR Model for Online Performance Improvement
Weijiang Lai, Beihong Jin, Jiongyan Zhang, Yiyuan Zheng, Jian Dong, Jia Cheng, Jun Lei, Xingxing Wang
https://arxiv.org/abs/2508.15326

Exploring Scaling Laws of CTR Model for Online Performance Improvement
CTR models play a vital role in improving user experience and boosting business revenue in many online personalized services. However, current CTR models generally encounter bottlenecks in performance improvement. Inspired by the scaling law phenomenon of LLMs, we propose a new paradigm for improving CTR predictions: first, constructing a CTR model with accuracy scalable to the model grade and data size, and then distilling the knowledge implied in this model into its lightweight model that can…

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning
Yiming Lin, Yuchen Niu, Shang Wang, Kaizhu Huang, Qiufeng Wang, Xiao-Bo Jin
https://arxiv.org/abs/2508.21816

The Demon is in Ambiguity: Revisiting Situation Recognition with Single Positive Multi-Label Learning
Context recognition (SR) is a fundamental task in computer vision that aims to extract structured semantic summaries from images by identifying key events and their associated entities. Specifically, given an input image, the model must first classify the main visual events (verb classification), then identify the participating entities and their semantic roles (semantic role labeling), and finally localize these entities in the image (semantic role localization). Existing methods treat verb cl…

Efficient Differentiable Contact Model with Long-range Influence
Xiaohan Ye, Kui Wu, Zherong Pan, Taku Komura
https://arxiv.org/abs/2509.20917 https://arxi…

Efficient Differentiable Contact Model with Long-range Influence
With the maturation of differentiable physics, its role in various downstream applications: such as model predictive control, robotic design optimization, and neural PDE solvers, has become increasingly important. However, the derivative information provided by differentiable simulators can exhibit abrupt changes or vanish altogether, impeding the convergence of gradient-based optimizers. In this work, we demonstrate that such erratic gradient behavior is closely tied to the design of contact m…

Role of universal function of the nuclear proximity potential: A systematic study on the alpha-decay of heavy/super-heavy nuclei and {\alpha}-induced reactions
S. Mohammadi, R. Gharaei, S. A. Alavi
https://arxiv.org/abs/2510.02764

Role of universal function of the nuclear proximity potential: A systematic study on the alpha-decay of heavy/super-heavy nuclei and α-induced reactions
The idea of the universal function is fundamental advantage of proximity potential model. We present a systematic study of the role of universal function of the proximity potential model on alpha decay process for 250 ground state to ground state transitions using WKB approximation. In order to realize this goal, five universal functions proposed in the proximity models gp 77, Guo 2013, Ngo 80, Zhang 2013 and Prox. 2010 have been incorporated into the formalism of Prox. 77. The obtained results…

Defect-Mediated Aggregation and Motility-Induced Phase Separation in Active XY Model
Shun Inoue, Satoshi Yukawa
https://arxiv.org/abs/2507.17108 https://ar…

Defect-Mediated Aggregation and Motility-Induced Phase Separation in Active XY Model
We propose an ``active XY model'' that incorporates key elements of both the classical XY model and the Vicsek model to study the role of topological defects in active matter systems. This model features self-propelled particles with XY spin degrees of freedom on a lattice and introduces a self-propulsion parameter controlling the directional bias of particle motion. Using numerical simulations, we demonstrate that self-propulsion induces motility-induced phase separation (MIPS), where particle…

EfficientDepth: A Fast and Detail-Preserving Monocular Depth Estimation Model
Andrii Litvynchuk, Ivan Livinsky, Anand Ravi, Nima Kalantari, Andrii Tsarov
https://arxiv.org/abs/2509.22527

EfficientDepth: A Fast and Detail-Preserving Monocular Depth Estimation Model
Monocular depth estimation (MDE) plays a pivotal role in various computer vision applications, such as robotics, augmented reality, and autonomous driving. Despite recent advancements, existing methods often fail to meet key requirements for 3D reconstruction and view synthesis, including geometric consistency, fine details, robustness to real-world challenges like reflective surfaces, and efficiency for edge devices. To address these challenges, we introduce a novel MDE system, called Efficien…

Role-Aware Language Models for Secure and Contextualized Access Control in Organizations
Saeed Almheiri, Yerulan Kongrat, Adrian Santosh, Ruslan Tasmukhanov, Josemaria Vera, Muhammad Dehan Al Kautsar, Fajri Koto
https://arxiv.org/abs/2507.23465

Role-Aware Language Models for Secure and Contextualized Access Control in Organizations
As large language models (LLMs) are increasingly deployed in enterprise settings, controlling model behavior based on user roles becomes an essential requirement. Existing safety methods typically assume uniform access and focus on preventing harmful or toxic outputs, without addressing role-specific access constraints. In this work, we investigate whether LLMs can be fine-tuned to generate responses that reflect the access privileges associated with different organizational roles. We explore t…

Exploring Large Language Model as an Interactive Sports Coach: Lessons from a Single-Subject Half Marathon Preparation
Kichang Lee
https://arxiv.org/abs/2509.26593 https://

Exploring Large Language Model as an Interactive Sports Coach: Lessons from a Single-Subject Half Marathon Preparation
Large language models (LLMs) are emerging as everyday assistants, but their role as longitudinal virtual coaches is underexplored. This two-month single subject case study documents LLM guided half marathon preparation (July-September 2025). Using text based interactions and consumer app logs, the LLM acted as planner, explainer, and occasional motivator. Performance improved from sustaining 2 km at 7min 54sec per km to completing 21.1 km at 6min 30sec per km, with gains in cadence, pace HR cou…

Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation
Claudio Pomo, Matteo Attimonelli, Danilo Danese, Fedelucio Narducci, Tommaso Di Noia
https://arxiv.org/abs/2508.04571

Do Recommender Systems Really Leverage Multimodal Content? A Comprehensive Analysis on Multimodal Representations for Recommendation
Multimodal Recommender Systems aim to improve recommendation accuracy by integrating heterogeneous content, such as images and textual metadata. While effective, it remains unclear whether their gains stem from true multimodal understanding or increased model complexity. This work investigates the role of multimodal item embeddings, emphasizing the semantic informativeness of the representations. Initial experiments reveal that embeddings from standard extractors (e.g., ResNet50, Sentence-Bert)…

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
Maximilian Beck, Kajetan Schweighofer, Sebastian B\"ock, Sebastian Lehner, Sepp Hochreiter
https://arxiv.org/abs/2510.02228 …

xLSTM Scaling Laws: Competitive Performance with Linear Time-Complexity
Scaling laws play a central role in the success of Large Language Models (LLMs), enabling the prediction of model performance relative to compute budgets prior to training. While Transformers have been the dominant architecture, recent alternatives such as xLSTM offer linear complexity with respect to context length while remaining competitive in the billion-parameter regime. We conduct a comparative investigation on the scaling behavior of Transformers and xLSTM along the following lines, prov…

Gravitational form factors of the nucleon in the Skyrme model based on scale-invariant chiral perturbation theory
Mitsuru Tanaka, Daisuke Fujii, Mamiya Kawaguchi
https://arxiv.org/abs/2507.21220

Gravitational form factors of the nucleon in the Skyrme model based on scale-invariant chiral perturbation theory
We investigate the role of the QCD scale anomaly in the gravitational form factors of the nucleon -- particularly the $D(t)$ form factor -- as well as the associated stress distribution and internal forces, using a Skyrme model based on the scale-invariant chiral perturbation theory. A distinctive feature of this model is the inclusion of both the pion and the scalar meson, which respectively capture the effects of the current quark mass and gluonic quantum contributions to the scale anomaly. B…

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey
Qiyuan Liu, Hao Xu, Xuhong Chen, Wei Chen, Yee Whye Teh, Ning Miao
https://arxiv.org/abs/2510.01925

Enhancing Large Language Model Reasoning with Reward Models: An Analytical Survey
Reward models (RMs) play a critical role in enhancing the reasoning performance of LLMs. For example, they can provide training signals to finetune LLMs during reinforcement learning (RL) and help select the best answer from multiple candidates during inference. In this paper, we provide a systematic introduction to RMs, along with a comprehensive survey of their applications in LLM reasoning. We first review fundamental concepts of RMs, including their architectures, training methodologies, an…

Faster and Better: Reinforced Collaborative Distillation and Self-Learning for Infrared-Visible Image Fusion
Yuhao Wang, Lingjuan Miao, Zhiqiang Zhou, Yajun Qiao, Lei Zhang
https://arxiv.org/abs/2509.02424

Faster and Better: Reinforced Collaborative Distillation and Self-Learning for Infrared-Visible Image Fusion
Infrared and visible image fusion plays a critical role in enhancing scene perception by combining complementary information from different modalities. Despite recent advances, achieving high-quality image fusion with lightweight models remains a significant challenge. To bridge this gap, we propose a novel collaborative distillation and self-learning framework for image fusion driven by reinforcement learning. Unlike conventional distillation, this approach not only enables the student model t…

How large are hadronic contributions to $h \to \gamma \gamma$?
Ulrich Haisch
https://arxiv.org/abs/2510.05773 https://arxiv.org/pdf/2510.05773

How large are hadronic contributions to $h \to γγ$?
The decay of the Higgs boson into two photons, $h \to γγ$, is a loop-induced process within the Standard Model, predominantly mediated by loops of $W$ bosons and top quarks. While these leading contributions are well understood, the role of hadronic effects, which arise from non-perturbative QCD dynamics, has received less attention, with recent studies reporting puzzling and contradictory results. In this work, we present a systematic evaluation of the hadronic contributions to the $h \to γ…

Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
Om Dobariya, Akhil Kumar
https://arxiv.org/abs/2510.04950 https://ar…

Mind Your Tone: Investigating How Prompt Politeness Affects LLM Accuracy (short paper)
The wording of natural language prompts has been shown to influence the performance of large language models (LLMs), yet the role of politeness and tone remains underexplored. In this study, we investigate how varying levels of prompt politeness affect model accuracy on multiple-choice questions. We created a dataset of 50 base questions spanning mathematics, science, and history, each rewritten into five tone variants: Very Polite, Polite, Neutral, Rude, and Very Rude, yielding 250 unique prom…

FreeViS: Training-free Video Stylization with Inconsistent References
Jiacong Xu, Yiqun Mei, Ke Zhang, Vishal M. Patel
https://arxiv.org/abs/2510.01686 https://

FreeViS: Training-free Video Stylization with Inconsistent References
Video stylization plays a key role in content creation, but it remains a challenging problem. Naïvely applying image stylization frame-by-frame hurts temporal consistency and reduces style richness. Alternatively, training a dedicated video stylization model typically requires paired video data and is computationally expensive. In this paper, we propose FreeViS, a training-free video stylization framework that generates stylized videos with rich style details and strong temporal coherence. Our…

RAGs to Riches: RAG-like Few-shot Learning for Large Language Model Role-playing
Timothy Rupprecht, Enfu Nan, Arash Akbari, Arman Akbari, Lei Lu, Priyanka Maan, Sean Duffy, Pu Zhao, Yumei He, David Kaeli, Yanzhi Wang
https://arxiv.org/abs/2509.12168

RAGs to Riches: RAG-like Few-shot Learning for Large Language Model Role-playing
Role-playing Large language models (LLMs) are increasingly deployed in high-stakes domains such as healthcare, education, and governance, where failures can directly impact user trust and well-being. A cost effective paradigm for LLM role-playing is few-shot learning, but existing approaches often cause models to break character in unexpected and potentially harmful ways, especially when interacting with hostile users. Inspired by Retrieval-Augmented Generation (RAG), we reformulate LLM role-pl…

COLIBRI Fuzzy Model: Color Linguistic-Based Representation and Interpretation
Pakizar Shamoi, Nuray Toganas, Muragul Muratbekova, Elnara Kadyrgali, Adilet Yerkin, Ayan Igali, Malika Ziyada, Ayana Adilova, Aron Karatayev, Yerdauit Torekhan
https://arxiv.org/abs/2507.11488

COLIBRI Fuzzy Model: Color Linguistic-Based Representation and Interpretation
Colors are omnipresent in today's world and play a vital role in how humans perceive and interact with their surroundings. However, it is challenging for computers to imitate human color perception. This paper introduces the Human Perception-Based Fuzzy Color Model, COLIBRI (Color Linguistic-Based Representation and Interpretation), designed to bridge the gap between computational color representations and human visual perception. The proposed model uses fuzzy sets and logic to create a framewo…

A Role-Aware Multi-Agent Framework for Financial Education Question Answering with LLMs
Andy Zhu, Yingjun Du
https://arxiv.org/abs/2509.09727 https://arxiv…

A Role-Aware Multi-Agent Framework for Financial Education Question Answering with LLMs
Question answering (QA) plays a central role in financial education, yet existing large language model (LLM) approaches often fail to capture the nuanced and specialized reasoning required for financial problem-solving. The financial domain demands multistep quantitative reasoning, familiarity with domain-specific terminology, and comprehension of real-world scenarios. We present a multi-agent framework that leverages role-based prompting to enhance performance on domain-specific QA. Our framew…