Tootfinder

📰 Deine Spende macht’s möglich: Ich informiere täglich über #Klima und #Forschung auf Deutsch, damit englischdominierte #Wissenschaftsmeldungen besser zugänglich werden. Danke für das Tei…

KlimaCrew
Ich informiere über Zukunftsthemen, um Menschen vor Risiken zu warnen und Fortschritte sichtbar zu machen.

Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Miguel A. Lago, Ghada Zamzmi, Brandon Eich, Jana G. Delfino
https://arxiv.org/abs/2506.13917

Evaluating Explainability: A Framework for Systematic Assessment and Reporting of Explainable AI Features
Explainability features are intended to provide insight into the internal mechanisms of an AI device, but there is a lack of evaluation techniques for assessing the quality of provided explanations. We propose a framework to assess and report explainable AI features. Our evaluation framework for AI explainability is based on four criteria: 1) Consistency quantifies the variability of explanations to similar inputs, 2) Plausibility estimates how close the explanation is to the ground truth, 3) F…

@… say, what was the page switching protocol you've encountered with PHYs before? reg 0xD/0xE appears to be 802.3 standard

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[4/4]:
- PLD: A Choice-Theoretic List-Wise Knowledge Distillation
Ejafa Bassam, Dawei Zhu, Kaigui Bian

Passing the Turing Test in Political Discourse: Fine-Tuning LLMs to Mimic Polarized Social Media Comments
. Pazzaglia, V. Vendetti, L. D. Comencini, F. Deriu, V. Modugno
https://arxiv.org/abs/2506.14645

Passing the Turing Test in Political Discourse: Fine-Tuning LLMs to Mimic Polarized Social Media Comments
The increasing sophistication of large language models (LLMs) has sparked growing concerns regarding their potential role in exacerbating ideological polarization through the automated generation of persuasive and biased content. This study explores the extent to which fine-tuned LLMs can replicate and amplify polarizing discourse within online environments. Using a curated dataset of politically charged discussions extracted from Reddit, we fine-tune an open-source LLM to produce context-aware…

Updated my Fediverse profile page, so it references more background stories rather than just referencing the apps we currently build.
Of course, given space constraints most of those story references are very brief allusions. But they might still serve as useful launch points for conversation! If anything there piques your interest and you're curious to learn more, feel free to ask me about them.

Enhancing photon-axion conversion probability with squeezed coherent states
Taiki Ikeda, Sugumi Kanno, Jiro Soda
https://arxiv.org/abs/2506.14354 https://

Enhancing photon-axion conversion probability with squeezed coherent states
In particle physics, axions and axion-like particles are ubiquitous. Remarkably, ultra-light axions could constitute dark matter or dark energy. Therefore, it is important to detect axions experimentally. In the presence of a magnetic field, a photon can be converted into an axion, and vice versa. Utilizing the conversion phenomenon, several methods for detecting axions have been proposed. To improve detectability, it is desirable to use quantum sensing. However, since the conversion process is…

Data Driven Approach to Input Shaping for Vibration Suppression in a Flexible Robot Arm
Jarkko Kotaniemi, Janne Saukkoriipi, Shuai Li, Markku Suomalainen
https://arxiv.org/abs/2506.14405

Data Driven Approach to Input Shaping for Vibration Suppression in a Flexible Robot Arm
This paper presents a simple and effective method for setting parameters for an input shaper to suppress the residual vibrations in flexible robot arms using a data-driven approach. The parameters are adaptively tuned in the workspace of the robot by interpolating previously measured data of the robot's residual vibrations. Input shaping is a simple and robust technique to generate vibration-reduced shaped commands by a convolution of an impulse sequence with the desired input command. The gene…

Defining the Game Producer: A Mapping of Key Characteristics and Differentiators of the Professional Behind Digital Game Production
Rafael C. Lopes, Danilo M. Ribeiro
https://arxiv.org/abs/2506.14409

Defining the Game Producer: A Mapping of Key Characteristics and Differentiators of the Professional Behind Digital Game Production
Introduction: As digital games grow in complexity, the role of the Game Producer becomes increasingly relevant for aligning creative, technical, and business dimensions. Objective: This study aimed to identify and map the main characteristics, skills, and competencies that define the Digital Game Producer profile. Methodology: A qualitative investigation was conducted with 11 semi-structured interviews, analyzed through Grounded Theory to build categories grounded in professional practice. Resu…

Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
Andrzej Cichocki
https://arxiv.org/abs/2506.13984 https://a…

Mirror Descent Using the Tempesta Generalized Multi-parametric Logarithms
In this paper, we develop a wide class Mirror Descent (MD) algorithms, which play a key role in machine learning. For this purpose we formulated the constrained optimization problem, in which we exploits the Bregman divergence with the Tempesta multi-parametric deformation logarithm as a link function. This link function called also mirror function defines the mapping between the primal and dual spaces and is associated with a very-wide (in fact, theoretically infinite) class of generalized tra…

[2025-06-18 Wed (UTC), 2 new articles found for math.LO Logic]
toXiv_bot_toot

Posets for Specht ideals of essential real reflection groups
Sebastian Debus, Kurt Klement Gottwald
https://arxiv.org/abs/2506.15335 https://

Posets for Specht ideals of essential real reflection groups
Specht ideals are symmetric ideals in the polynomial ring generated by Specht polynomials associated with group representations. These ideals were previously studied for reflection groups of types $A$ and $B$, where their inclusion relations and their varieties reflect rich combinatorial structures. In this paper, we extend this theory to type $D$ and the dihedral groups. Our results complete the combinatorial study of Specht ideals across all infinite families of essential real reflection grou…

[2025-05-19 Mon (UTC), no new articles found for q-fin.TR Trading and Market Microstructure]
#toXiv_bot_toot

Long strings of composite values of polynomials and a basis of order 2
Artyom Radomskii
https://arxiv.org/abs/2506.15641 https://arxi…

Long strings of composite values of polynomials and a basis of order 2
We show that for any polynomial $f: \mathbb{Z}\to \mathbb{Z}$ with positive leading coefficient and irreducible over $\mathbb{Q}$, if $N$ is large enough then there are two strings of consecutive positive integers $I_{1}=\{n_1-m,\ldots, n_1+m\}$ and $I_{2}=\{n_2-m, \ldots, n_2+m\}$, where $m = [(\log N) (\log \log N)^{1/325525}]$, such that $I_{1}\cup I_{2} \subset [1, N]$, $N = n_1 + n_2$, and $f(n)$ is composite for any $n\in I_{1}\cup I_{2}$. This extends the result in [5] which showed the s…

Virtual invariants of Quot schemes of points on threefolds
Solomiya Mizyuk
https://arxiv.org/abs/2506.14490 https://arxiv.org/pdf/250…

Virtual invariants of Quot schemes of points on threefolds
We construct an almost perfect obstruction theory of virtual dimension zero on the Quot scheme parametrizing zero-dimensional quotients of a locally free sheaf on a smooth projective $3$-fold. This gives a virtual class in degree zero and therefore allows one to define virtual invariants of the Quot scheme. We compute these invariants proving a conjecture by Ricolfi. The computation is done by reducing to the toric case via cobordism theory and a degeneration argument. The toric case is solved …

Brain Stroke Classification Using Wavelet Transform and MLP Neural Networks on DWI MRI Images
Mana Mohammadi, Amirhesam Jafari Rad, Ashkan Behrouzi
https://arxiv.org/abs/2506.15364

Brain Stroke Classification Using Wavelet Transform and MLP Neural Networks on DWI MRI Images
This paper presents a lightweight framework for classifying brain stroke types from Diffusion-Weighted Imaging (DWI) MRI scans, employing a Multi-Layer Perceptron (MLP) neural network with Wavelet Transform for feature extraction. Accurate and timely stroke detection is critical for effective treatment and improved patient outcomes in neuroimaging. While Convolutional Neural Networks (CNNs) are widely used for medical image analysis, their computational complexity often hinders deployment in re…

Coordinate-energy transformation and the one-point function for the Heisenberg-Ising XXZ spin-1/2 chain on the ring
Eric I. Corwin, Nikolaus Elsaesser, Axel Saenz
https://arxiv.org/abs/2506.14171

Coordinate-energy transformation and the one-point function for the Heisenberg-Ising XXZ spin-1/2 chain on the ring
We provide a basis transformation that inverts the coordinate Bethe Ansatz. It is widely believed that the Bethe Ansatz is complete, based on numerical evidence and combinatorial arguments. We present a constructive and comprehensive approach to show that the Bethe Ansatz is complete. The transformation formula is verified numerically with excellent accuracy for non-zero anisotropy parameters and rings of odd length. Additionally, assuming the Bethe Ansatz is complete, we derive a novel exact f…

[2025-06-19 Thu (UTC), no new articles found for cs.CC Computational Complexity]
toXiv_bot_toot

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
Alex C. Newkirk, Jared Fernandez, Jonathan Koomey, Imran Latif, Emma Strubell, Arman Shehabi, Constantine Samaras
https://arxiv.org/abs/2506.14551

Empirically-Calibrated H100 Node Power Models for Reducing Uncertainty in AI Training Energy Estimation
As AI's energy demand continues to grow, it is critical to enhance the understanding of characteristics of this demand, to improve grid infrastructure planning and environmental assessment. By combining empirical measurements from Brookhaven National Laboratory during AI training on 8-GPU H100 systems with open-source benchmarking data, we develop statistical models relating computational intensity to node-level power consumption. We measure the gap between manufacturer-rated thermal design pow…

Laser-Driven Annular Shock Waves as Laboratory Analogues of $w$CDM Cosmologies and Cosmological Gravitational Waves
Felipe A. Asenjo, Felipe Veloso, Julio C. Valenzuela
https://arxiv.org/abs/2506.15493

Laser-Driven Annular Shock Waves as Laboratory Analogues of $w$CDM Cosmologies and Cosmological Gravitational Waves
We demonstrate that the experimental evolution of an annular, laser-driven plasma shock wave, expanding over time and undergoing self-interaction gives rise to multiple shock structures that evolve analogously to a multicomponent cosmological universe. Different propagation trajectories along the shock surface correspond to various forms of $w$CDM cosmologies, enabling the study of scenarios ranging from simple radiation- or matter-dominated universes to those including dark energy. We further …

Analyzing URA Geometry for Enhanced Spatial Multiplexing and Extended Near-Field Coverage
Ahmed Hussain, Asmaa Abdallah, Abdulkadir Celik, Ahmed M. Eltawil
https://arxiv.org/abs/2506.15470

Analyzing URA Geometry for Enhanced Spatial Multiplexing and Extended Near-Field Coverage
With the deployment of large antenna arrays at high frequency bands, future wireless communication systems are likely to operate in the radiative near-field. Unlike far-field beam steering, near-field beams can be focused within a spatial region of finite depth, enabling spatial multiplexing in both the angular and range dimensions. This paper derives the beamdepth for a generalized uniform rectangular array (URA) and investigates how array geometry influences the near-field beamdepth and the l…

Analysis of three-body charmed $B$ meson decays $B \to {D}(V^* \to){V P}$
Jing Ou-Yang, Run-Hui Li, Si-Hong Zhou
https://arxiv.org/abs/2506.14675 https://

Analysis of three-body charmed $B$ meson decays $B \to {D}(V^* \to){V P}$
We systematically analyze the decays $B_{(s)} \to D_{(s)} (V^* \to)\, V\, P$, where $V^*$ represents a vector resonance ($ρ, \, ω$ or $K^*$), and $V P$ denotes the final-state meson pairs $ ω\, π$, $ ρ\, π$ and $ ρ\, K$. The intermediate subprocesses $B_{(s)} \to D_{(s)} V^*$ are calculated in the factorization-assisted topological-amplitude approach, while the intermediate resonant states $V^*$ are modeled using a relativistic Breit-Wigner distribution, subsequently decaying into $VP$ t…

Examples of complete Calabi--Yau metrics on affine smoothings of irregular toric Calabi--Yau cones
Ronan J. Conlon, Tran-Trung Nghiem
https://arxiv.org/abs/2506.14118

Examples of complete Calabi--Yau metrics on affine smoothings of irregular toric Calabi--Yau cones
We present new examples of affine Calabi--Yau manifolds of Euclidean volume growth and quadratic curvature decay, whose tangent cones at infinity are irregular and have smooth links. In the process, we demonstrate (and provide the relevant computer code) how to explicitly compute the Reeb field and all Minkowski decompositions of a given toric Calabi--Yau cone with smooth link from the data of its toric polytope. Minkowski decompositions of this polytope into lattice segments and/or triangles g…

Charged Scalar Field at Future Null Infinity via Nonlinear Hyperboloidal Evolution
Jo\~ao D. \'Alvares, Alex Va\~no-Vin\~uales
https://arxiv.org/abs/2506.15311

Charged Scalar Field at Future Null Infinity via Nonlinear Hyperboloidal Evolution
Quasinormal modes and power-law late-time decay tails of a charged scalar field in a charged black hole background have been studied, but never in the fully non-linear regime, as far as we know. In this paper, we study the dependence of these properties on the charges of scalar field and black hole. For the quasinormal modes, a fit of the spherical fundamental mode is shown for the purely uncharged case and compared to the charged one. We also see for the first time the transition from gravitat…

A Data-Integrated Framework for Learning Fractional-Order Nonlinear Dynamical Systems
Bahram Yaghooti, Chengyu Li, Bruno Sinopoli
https://arxiv.org/abs/2506.15665

A Data-Integrated Framework for Learning Fractional-Order Nonlinear Dynamical Systems
This paper presents a data-integrated framework for learning the dynamics of fractional-order nonlinear systems in both discrete-time and continuous-time settings. The proposed framework consists of two main steps. In the first step, input-output experiments are designed to generate the necessary datasets for learning the system dynamics, including the fractional order, the drift vector field, and the control vector field. In the second step, these datasets, along with the memory-dependent prop…

Replaced article(s) found for cond-mat.stat-mech. https://arxiv.org/list/cond-mat.stat-mech/new
[1/1]:
- Fermionic logarithmic negativity in the Krawtchouk chain
Gabrielle Blanchet, Gilles Parez, Luc Vinet

Posterior contraction rates of computational methods for Bayesian data assimilation
Erik Burman, Mingfei Lu
https://arxiv.org/abs/2506.14685 https://

Posterior contraction rates of computational methods for Bayesian data assimilation
In this paper, we analyze posterior consistency of a Bayesian data assimilation problem under discretization. We prove convergence rates for the discrete posterior to ground truth solution under both conforming discretization and finite element discretization (usually non-conforming). The analysis is based on the coupling of asymptotics between the number of samples and the dimension of discrete spaces. In the finite element discretization, tailor-made discrete priors, instead of the discretiza…

Towards High-Efficiency Solar Cells: Insights into AsNCa 3 Antiperovskite as Active Layer
M. Irfan, B. D. Aparicio-Huacarpuma, C. M. de Oliveira Bastos, M. J. Piotrowski, C. R. C. R\^ego, D. Guedes-Sobrinho, R. Besse, A. M. Almeida Silva, Alexandre C. Dias, L. A. Ribeiro Jr
https://arxiv.org/abs/2506.15403

Towards High-Efficiency Solar Cells: Insights into AsNCa 3 Antiperovskite as Active Layer
Advances in photovoltaic technology are a viable route to contribute to cleaner and more sustainable energy solutions, placing perovskite-based materials among the best candidates for solar energy conversion. However, some challenges must be addressed to enhance their performance and stability. Herein, we report an investigation of the AsNCa3 antiperovskite system for its potential in photovoltaic devices. We consider eight distinct crystalline phases, their structural parameters, dynamical sta…

Application of a modified commercial laser mass spectrometer as a science analog of the Mars Organic Molecule Analyzer (MOMA)
Zachary K. Garvin (Georgetown University, Washington, D.C., USA), Ana\"is Roussel (Georgetown University, Washington, D.C., USA), Luoth Chou (NASA Goddard Space Flight Center, Greenbelt, MD, USA), Marco E. Castillo (NASA Goddard Space Flight Center, Greenbelt, MD, USA, Aerodyne Industries, Cape Canaveral, FL, USA), Xiang Li (NASA Goddard Space Flight Center…

Application of a modified commercial laser mass spectrometer as a science analog of the Mars Organic Molecule Analyzer (MOMA)
The ESA/NASA Rosalind Franklin rover, planned for launch in 2028, will carry the first laser desorption ionization mass spectrometer (LDI-MS) to Mars as part of the Mars Organic Molecule Analyzer (MOMA) instrument. MOMA will contribute to the astrobiology goals of the mission through the analysis of potential organic biosignatures. Due to the minimal availability of comparable equipment, laboratory analyses using similar techniques and instrumentation have been limited. In this study, we presen…

Versatile SPH Open Boundary Conditions for Multiphase Flows in Extreme Condition
Zi-Yang Zhan, Zhen Chen
https://arxiv.org/abs/2506.14500 https://

Versatile SPH Open Boundary Conditions for Multiphase Flows in Extreme Condition
Although the Smoothed Particle Hydrodynamics (SPH) method has been demonstrated as a promising numerical solver for multiphase flow problems due to its Lagrangian nature, its application to complex channel flow may encounter additional issues such as the open boundary condition and numerical instability in the extreme flow state. The present work aims to establish a general SPH algorithm for accurate and stable simulation of complex multiphase flows in configurations with open boundaries. The g…

Replaced article(s) found for physics.soc-ph. https://arxiv.org/list/physics.soc-ph/new
[1/1]:
Community detection in hypergraphs through hyperedge percolation

Replaced article(s) found for cs.MM. https://arxiv.org/list/cs.MM/new
[1/1]:
- Bi-VLDoc: Bidirectional Vision-Language Modeling for Visually-Rich Document Understanding
Chuwei Luo, Guozhi Tang, Qi Zheng, Cong Yao, Lianwen Jin, Chenliang Li, Yang Xue, Luo Si

Admissible solutions of the 2D Onsager's conjecture
Lili Du, Xinliang Li, Weikui Ye
https://arxiv.org/abs/2506.15396 https://arxi…

Admissible solutions of the 2D Onsager's conjecture
We show that for any $γ< \frac{1}{3}$ there exist Hölder continuous weak solutions $v \in C^γ([0,T] \times \mathbb{T}^2)$ of the two-dimensional incompressible Euler equations that strictly dissipate the total kinetic energy, improving upon the elegant work of Giri and Radu [Invent. Math., 238 (2), 2024]. Furthermore, we prove that the initial data of these \textit{admissible} solutions are dense in $B^γ_{\infty,r<\infty}$. Our approach introduces a new class of traveling waves, refining …

Replaced article(s) found for math.RA. https://arxiv.org/list/math.RA/new
[1/1]:
Two axes in non-commutative algebras with a Frobenius form
https:/…

Approximation of pseudohermitian structures via embeddings into spheres
Hendrik Herrmann, Chin-Yu Hsiao, Bernhard Lamel
https://arxiv.org/abs/2506.14033 ht…

Approximation of pseudohermitian structures via embeddings into spheres
Let $(X,T^{1,0}X)$ be a compact strictly pseudoconvex CR manifold which is CR embeddable into the complex Euclidean space. We show that $T^{1,0}X$ can be approximated in $\mathscr{C}^\infty$-topology by a sequence of strictly pseudoconvex CR structures $\{\mathcal{V}^k\}_{k\in \mathbb N}$ such that each $(X,\mathcal{V}^k)$ is CR embeddable into the unit sphere of a complex Euclidean space. Furthermore, as a refinement of this statement, we show that given a one form $α$ on $X$ such that $(X,T^…

Replaced article(s) found for physics.ao-ph. https://arxiv.org/list/physics.ao-ph/new
[1/1]:
Regional climate risk assessment from climate models using probabilistic machine learning

Replaced article(s) found for cs.GR. https://arxiv.org/list/cs.GR/new
[1/1]:
- ImmerseGen: Agent-Guided Immersive World Generation with Alpha-Textured Proxies
Yuan, Yang, Wang, Pan, Ma, Zhang, Liu, Cui, Ma

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[8/8]:
Active Perception for Tactile Sensing: A Task-Agnostic Attention-Based Approach

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[3/4]:
- RoCA: Robust Cross-Domain End-to-End Autonomous Driving
Yasarla, Han, Cheng, Liu, Mahajan, Bhattacharyya, Shi, Garrepalli, Cai, Porikli

SANGAM: SystemVerilog Assertion Generation via Monte Carlo Tree Self-Refine
Adarsh Gupta, Bhabesh Mali, Chandan Karfa
https://arxiv.org/abs/2506.13983 http…

SANGAM: SystemVerilog Assertion Generation via Monte Carlo Tree Self-Refine
Recent advancements in the field of reasoning using Large Language Models (LLMs) have created new possibilities for more complex and automatic Hardware Assertion Generation techniques. This paper introduces SANGAM, a SystemVerilog Assertion Generation framework using LLM-guided Monte Carlo Tree Search for the automatic generation of SVAs from industry-level specifications. The proposed framework utilizes a three-stage approach: Stage 1 consists of multi-modal Specification Processing using Sign…

When Does Meaning Backfire? Investigating the Role of AMRs in NLI
Junghyun Min, Xiulin Yang, Shira Wein
https://arxiv.org/abs/2506.14613 https://

When Does Meaning Backfire? Investigating the Role of AMRs in NLI
Natural Language Inference (NLI) relies heavily on adequately parsing the semantic content of the premise and hypothesis. In this work, we investigate whether adding semantic information in the form of an Abstract Meaning Representation (AMR) helps pretrained language models better generalize in NLI. Our experiments integrating AMR into NLI in both fine-tuning and prompting settings show that the presence of AMR in fine-tuning hinders model generalization while prompting with AMR leads to sligh…

A Cooperative Contactless Object Transport with Acoustic Robots
Narsimlu Kemsaram, Akin Delibasi, James Hardwick, Bonot Gautam, Diego Martinez Plasencia, Sriram Subramanian
https://arxiv.org/abs/2506.13957

A Cooperative Contactless Object Transport with Acoustic Robots
Cooperative transport, the simultaneous movement of an object by multiple agents, has been widely observed in biological systems such as ant colonies, which improve efficiency and adaptability in dynamic environments. Inspired by these natural phenomena, we present a novel acoustic robotic system for the transport of contactless objects in mid-air. Our system leverages phased ultrasonic transducers and a robotic control system onboard to generate localized acoustic pressure fields, enabling pre…

Automatic Qiskit Code Refactoring Using Large Language Models
Jos\'e Manuel Su\'arez, Luis Mariano Bibb\'o, Joaquin Bogado, Alejandro Fernandez
https://arxiv.org/abs/2506.14535

Automatic Qiskit Code Refactoring Using Large Language Models
As quantum software frameworks evolve, developers face increasing challenges in maintaining compatibility with rapidly changing APIs. In this work, we present a novel methodology for refactoring Qiskit code using large language models (LLMs). We begin by extracting a taxonomy of migration scenarios from the different sources of official Qiskit documentation (such as release notes), capturing common patterns such as migration of functionality to different modules and deprecated usage. This taxon…

Strongly First Order Disjunctive Embedded Dependencies in Team Semantics
Pietro Galliani
https://arxiv.org/abs/2506.15367 https://arx…

Strongly First Order Disjunctive Embedded Dependencies in Team Semantics
First Order Team Semantics is a generalization of Tarskian Semantics in which formulas are satisfied with respect to sets of assignments. In Team Semantics, it is possible to extend First Order Logic via new types of atoms that describe dependencies between variables; some of these extensions are strictly more expressive than First Order Logic, while others are reducible to it. Many of the atoms studied in Team Semantics are inspired by Database Theory and belong in particular to the class of…

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[2/4]:
- SFDLA: Source-Free Document Layout Analysis
Sebastian Tewes, Yufan Chen, Omar Moured, Jiaming Zhang, Rainer Stiefelhagen

Generating uniform linear extensions using few random bits
Mark Huber
https://arxiv.org/abs/2506.14725 https://arxiv.org/pdf/2506.147…

Generating uniform linear extensions using few random bits
A \emph{linear extension} of a partial order \(\preceq\) over items \(A = \{ 1, 2, \ldots, n \}\) is a permutation \(σ\) such that for all \(i < j\) in \(A\), it holds that \(\neg(σ(j) \preceq σ(i))\). Consider the problem of generating uniformly from the set of linear extensions of a partial order. The best method currently known uses \(O(n^3 \ln(n))\) operations and \(O(n^3 \ln(n)^2)\) iid fair random bits to generate such a permutation. This paper presents a method that generates a unifor…

Probabilistic Trajectory GOSPA: A Metric for Uncertainty-Aware Multi-Object Tracking Performance Evaluation
Yuxuan Xia, \'Angel F. Garc\'ia-Fern\'andez, Johan Karlsson, Yu Ge, Lennart Svensson, Ting Yuan
https://arxiv.org/abs/2506.15148

Probabilistic Trajectory GOSPA: A Metric for Uncertainty-Aware Multi-Object Tracking Performance Evaluation
This paper presents a generalization of the trajectory general optimal sub-pattern assignment (GOSPA) metric for evaluating multi-object tracking algorithms that provide trajectory estimates with track-level uncertainties. This metric builds on the recently introduced probabilistic GOSPA metric to account for both the existence and state estimation uncertainties of individual object states. Similar to trajectory GOSPA (TGOSPA), it can be formulated as a multidimensional assignment problem, and …

ProfiLLM: An LLM-Based Framework for Implicit Profiling of Chatbot Users
Shahaf David, Yair Meidan, Ido Hersko, Daniel Varnovitzky, Dudu Mimran, Yuval Elovici, Asaf Shabtai
https://arxiv.org/abs/2506.13980

ProfiLLM: An LLM-Based Framework for Implicit Profiling of Chatbot Users
Despite significant advancements in conversational AI, large language model (LLM)-powered chatbots often struggle with personalizing their responses according to individual user characteristics, such as technical expertise, learning style, and communication preferences. This lack of personalization is particularly problematic in specialized knowledge-intense domains like IT/cybersecurity (ITSec), where user knowledge levels vary widely. Existing approaches for chatbot personalization primarily …

On balanced HKT manifolds
Giovanni Gentili, Mehdi Lejmi
https://arxiv.org/abs/2506.15519 https://arxiv.org/pdf/2506.15519

On balanced HKT manifolds
We prove the openness of the balanced HKT cone within the cone of HKT structures on a compact hypercomplex manifold $(M,I,J,K)$. We also study the Lie algebra of hyperholomorphic vector fields of type (1,0) with respect to $I$, with particular emphasis on the case when there exists a compatible balanced HKT metric. These fields exhibit a strict interplay with the balanced HKT structure, for instance, we prove a harmonicity property for (1,0)-forms dual to hyperholomorphic vector fields. We also…

Fokker-Planck Score Learning: Efficient Free-Energy Estimation under Periodic Boundary Conditions
Daniel Nagel, Tristan Bereau
https://arxiv.org/abs/2506.15653

Fokker-Planck Score Learning: Efficient Free-Energy Estimation under Periodic Boundary Conditions
Accurate free-energy estimation is essential in molecular simulation, yet the periodic boundary conditions (PBC) commonly used in computer simulations have rarely been explicitly exploited. Equilibrium methods such as umbrella sampling, metadynamics, and adaptive biasing force require extensive sampling, while non-equilibrium pulling with Jarzynski's equality suffers from poor convergence due to exponential averaging. Here, we introduce a physics-informed, score-based diffusion framework: by ma…

Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural
Emmanuel Franck (MACARON), Laurent Navoret (IRMA, MACARON), Vincent Vigon (IRMA, MACARON), Rapha\"el C\^ote (IRMA), Guillaume Steimer (MACARON)
https://arxiv.org/abs/2506.15203

Reduced Particle in Cell method for the Vlasov-Poisson system using auto-encoder and Hamiltonian neural
Hamiltonian particle-based simulations of plasma dynamics are inherently computationally intensive, primarily due to the large number of particles required to obtain accurate solutions. This challenge becomes even more acute in many-query contexts, where numerous simulations must be conducted across a range of time and parameter values. Consequently, it is essential to construct reduced order models from such discretizations to significantly lower computational costs while ensuring validity acr…

Symbolic Regression-Enhanced Dynamic Wake Meandering: Fast and Physically Consistent Wind-Turbine Wake Modeling
Ding Wang, Dachuan Feng, Kangcheng Zhou, Yuntian Chen, Shijun Liao, Shiyi Chen
https://arxiv.org/abs/2506.14403

Symbolic Regression-Enhanced Dynamic Wake Meandering: Fast and Physically Consistent Wind-Turbine Wake Modeling
Accurately modeling wind turbine wakes is essential for optimizing wind farm performance but remains a persistent challenge. While the dynamic wake meandering (DWM) model captures unsteady wake behavior, it suffers from near-wake inaccuracies due to empirical closures. We propose a Symbolic Regression-enhanced DWM (SRDWM) framework that achieves equation-level closure by embedding symbolic expressions for volumetric forcing and boundary terms explicitly into governing equations. These physicall…

A novel approach for converting spatio-temporal series into complex networks
G. Cigdem Yalcin, M. Berk Onder
https://arxiv.org/abs/2506.14378 https://

A novel approach for converting spatio-temporal series into complex networks
This study aims to offer a new perspective on complex network representation of real-world systems. Currently, the most well-known transformation algorithms in the literature treat each data point in a time series as a node and transform the time series into a network. In this study, we present a new approach converting spatio-temporal series into a complex network. We focus on studying this transformation by grounding it in the context of physics , with the aim of adapting it to real-world pro…

How Does LLM Reasoning Work for Code? A Survey and a Call to Action
Ira Ceka, Saurabh Pujar, Irene Manotas, Gail Kaiser, Baishakhi Ray, Shyam Ramji
https://arxiv.org/abs/2506.13932

How Does LLM Reasoning Work for Code? A Survey and a Call to Action
The rise of large language models (LLMs) has led to dramatic improvements across a wide range of natural language tasks. These advancements have extended into the domain of code, facilitating complex tasks such as code generation, translation, summarization, and repair. However, their utility for real-world deployment in-the-wild has only recently been studied, particularly on software engineering (SWE) tasks such as GitHub issue resolution. In this study, we examine the code reasoning techniqu…

A ringed-space-like structure on coalgebras for noncommutative algebraic geometry
So Nakamura
https://arxiv.org/abs/2506.14689 https://

A ringed-space-like structure on coalgebras for noncommutative algebraic geometry
Inspired by the perspective of Reyes' noncomutative spectral theory, we attempt to develop noncommutative algebraic geometry by introducing ringed coalgebras, which can be thought of as a noncommutative generalization of schemes over a field $k$. These objects arise from fully residually finite-dimensional(RFD) algebras introduced by Reyes and from schemes locally of finite type over $k$. The construction uses the Heyneman-Sweedler finite dual coalgebra and the Takeuchi underlying coalgebra. Wh…

$\Sigma^1_3$ sets in the Sacks model
Jonathan Schilhan
https://arxiv.org/abs/2506.15308 https://arxiv.org/pdf/2506.15308

$Σ^1_3$ sets in the Sacks model
We show that in the iterated Sacks model over the constructible universe the Mansfield-Solovay Theorem holds for $Σ^1_3$ sets. In particular, every $\mathbfΣ^1_3$ set is Marczewski measurable and the optimal complexity for a Bernstein set is $Δ^1_4$. Based on a result by Kanovei, we also briefly show how to separate the Mansfield-Solovay Theorem at non-trivial levels of the projective hierarchy.

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[7/8]:
Achieving Collective Welfare in Multi-Agent Reinforcement Learning via Suggestion Sharing

Replaced article(s) found for cs.CV. https://arxiv.org/list/cs.CV/new
[1/4]:
- Bi-VLDoc: Bidirectional Vision-Language Modeling for Visually-Rich Document Understanding
Chuwei Luo, Guozhi Tang, Qi Zheng, Cong Yao, Lianwen Jin, Chenliang Li, Yang Xue, Luo Si

Integrating Knowledge Graphs and Bayesian Networks: A Hybrid Approach for Explainable Disease Risk Prediction
Mbithe Nzomo, Deshendran Moodley
https://arxiv.org/abs/2506.13920

Integrating Knowledge Graphs and Bayesian Networks: A Hybrid Approach for Explainable Disease Risk Prediction
Multimodal electronic health record (EHR) data is useful for disease risk prediction based on medical domain knowledge. However, general medical knowledge must be adapted to specific healthcare settings and patient populations to achieve practical clinical use. Additionally, risk prediction systems must handle uncertainty from incomplete data and non-deterministic health outcomes while remaining explainable. These challenges can be alleviated by the integration of knowledge graphs (KGs) and Bay…

Linear Planar 3-SAT and Its Applications in Planning
Victorien Desbois, Ocan Sankur, Fran\c{c}ois Schwarzentruber
https://arxiv.org/abs/2506.14713 https://…

Linear Planar 3-SAT and Its Applications in Planning
Several fragments of the satisfiability problem have been studied in the literature. Among these, Linear 3-SAT is a satisfaction problem in which each clause (viewed as a set of literals) intersects with at most one other clause; moreover, any pair of clauses have at most one literal in common. Planar 3-SAT is a fragment which requires that the so-called variable-clause graph is planar. Both fragments are NP-complete and have applications in encoding NP-hard planning problems. In this paper, we…

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
Anirud Aggarwal, Abhinav Shrivastava, Matthew Gwilliam
https://arxiv.org/abs/2506.15682

Evolutionary Caching to Accelerate Your Off-the-Shelf Diffusion Model
Diffusion-based image generation models excel at producing high-quality synthetic content, but suffer from slow and computationally expensive inference. Prior work has attempted to mitigate this by caching and reusing features within diffusion transformers across inference steps. These methods, however, often rely on rigid heuristics that result in limited acceleration or poor generalization across architectures. We propose Evolutionary Caching to Accelerate Diffusion models (ECAD), a genetic a…

Flips Reveal the Universal Impact of Memory on Random Explorations
Julien Br\'emont, L\'eo R\'egnier, Alex Barbier--Chebbah, Olivier B\'enichou, Rapha\"el Voituriez
https://arxiv.org/abs/2506.15642

Flips Reveal the Universal Impact of Memory on Random Explorations
Quantifying space exploration is a central question in random walk theory, with direct applications ranging from animal foraging, diffusion-limited reactions, and intracellular transport to stock markets. In particular, the explored domain by one or many simple memoryless (or Markovian) random walks has received considerable attention . However, the physical systems mentioned above typically involve significant memory effects, and so far, no general framework exists to analyze such systems. We …

Definability of complex functions in o-minimal structures
Adele Padgett, Patrick Speissegger
https://arxiv.org/abs/2506.15119 https://

Definability of complex functions in o-minimal structures
We prove that some holomorphic continuations of functions in the classes $\mathbf{an}^*$ and $\mathcal{G}$ are definable in the o-minimal structures $\mathbb{R}_{\mathrm{an}^*}$ and $\mathbb{R}_{\mathcal{G}}$ respectively. More specifically, we give complex domains on which the holomorphic continuations are definable, and show they are optimal. As an application, we describe optimal domains on which the Riemann $ζ$ function is definable in o-minimal expansions of $\mathbb{R}_{\mathrm{an}^*,\ex…

Optimal alignment of Lorentz orientation and generalization to matrix Lie groups
Congzhou M Sha
https://arxiv.org/abs/2506.14994 https://

Optimal alignment of Lorentz orientation and generalization to matrix Lie groups
There exist elegant methods of aligning point clouds in $\mathbb R^3$. Unfortunately, these methods rely on the positive definite property of the Euclidean metric, and do not easily extend to the indefinite Minkowski metric. In this paper, we propose two solutions to the following problem: given inertial reference frames $A$ and $B$, and given (possibly noisy) measurements of a set of 4-vectors $\{v_i\}$ made in those reference frames with components $\{v_{A,i}\}$ and $\{v_{B,i}\}$, find the op…

A simple and efficient second-order immersed-boundary method for the incompressible Navier--Stokes equations
Paolo Luchini, Davide Gatti, Alessandro Chiarini, Federica Gattere, Marco Atzori, Maurizio Quadrio
https://arxiv.org/abs/2506.14328

A simple and efficient second-order immersed-boundary method for the incompressible Navier--Stokes equations
An immersed-boundary method for the incompressible Navier--Stokes equations is presented. It employs discrete forcing for a sharp discrimination of the solid-fluid interface, and achieves second-order accuracy, demonstrated in examples with highly complex three-dimensional geometries. The method is implicit, meaning that the point in the solid which is nearest to the interface is accounted for implicitly, which benefits stability and convergence properties; the correction is also implicit in ti…

Mitigating collusion in Gold Humanism Honor Society nominations
Congzhou M Sha
https://arxiv.org/abs/2506.14061 https://arxiv.org/pdf…

Mitigating collusion in Gold Humanism Honor Society nominations
An anecdotally common complaint regarding induction into the Gold Humanism Honor Society is the bias toward close friends during the initial nomination process. In this work, we numerically simulate the nomination process under different assumptions, demonstrate that collusion can be detected, and propose a simple strategy to correct for bias in the nomination process.

Associative Pentagon Algebras
Marzia Mazzotta, Agata Pilitowska
https://arxiv.org/abs/2506.14216 https://arxiv.org/pdf/2506.14216

Associative Pentagon Algebras
A set-theoretic solution to the Pentagon Equation can be described as a \emph{pentagon} algebra $(S, \cdot, \ast)$ such that $(S, \cdot)$ is a semigroup and the operations $\cdot$ and $\ast$ are related by two additional equations. This paper aims to investigate associative pentagon algebras in which $(S, \ast)$ is also a semigroup. We introduce and describe two families of associative pentagon algebras which are strongly determined by the properties of the semigroup $(S,\ast)$. We present a co…

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[6/8]:
Efficient Numerical Integration in Reproducing Kernel Hilbert Spaces via Leverage Scores Sampling

Sekai: A Video Dataset towards World Exploration
Zhen Li, Chuanhao Li, Xiaofeng Mao, Shaoheng Lin, Ming Li, Shitian Zhao, Zhaopan Xu, Xinyue Li, Yukang Feng, Jianwen Sun, Zizhen Li, Fanrui Zhang, Jiaxin Ai, Zhixiang Wang, Yuwei Wu, Tong He, Jiangmiao Pang, Yu Qiao, Yunde Jia, Kaipeng Zhang
https://arxiv.org/abs/2506.15675…

Sekai: A Video Dataset towards World Exploration
Video generation techniques have made remarkable progress, promising to be the foundation of interactive world exploration. However, existing video generation datasets are not well-suited for world exploration training as they suffer from some limitations: limited locations, short duration, static scenes, and a lack of annotations about exploration and the world. In this paper, we introduce Sekai (meaning ``world'' in Japanese), a high-quality first-person view worldwide video dataset with rich…

The Complexity of Counting Small Sub-Hypergraphs
Marco Bressan, Julian Brinkmann, Holger Dell, Marc Roth, Philip Wellnitz
https://arxiv.org/abs/2506.14081 …

The Complexity of Counting Small Sub-Hypergraphs
Subgraph counting is a fundamental and well-studied problem whose computational complexity is well understood. Quite surprisingly, the hypergraph version of subgraph counting has been almost ignored. In this work, we address this gap by investigating the most basic sub-hypergraph counting problem: given a (small) hypergraph $H$ and a (large) hypergraph $G$, compute the number of sub-hypergraphs of $G$ isomorphic to $H$. Formally, for a family $\mathcal{H}$ of hypergraphs, let #Sub($\mathcal{H}$…

Class of extensions of real field and their topological properties
E. V. Alexandrov
https://arxiv.org/abs/2506.14838 https://arxiv.or…

Class of extensions of real field and their topological properties
Proper classes of extensions of real field was defined and topological properties of these extensions were studied. These extensions can be connected, in this case such set is not closed under binary operations (addition and multiplication), and not connected, in this case this extension is linearly ordered field. In the future these constructions can be applied to building measure that "feels" set of zero Lebesgue measure.

Duplication-divergence growing graph models
Dario Borrelli
https://arxiv.org/abs/2506.15640 https://arxiv.org/pdf/2506.15640

Duplication-divergence growing graph models
In recent decades, it has been emphasized that the evolving structure of networks may be shaped by interaction principles that yield sparse graphs with a vertex degree distribution exhibiting an algebraic tail, and other structural traits that are not featured in traditional random graphs. In this respect, through a mean-field approach, this review tackles the statistical physics of graph models based on the interaction principle of duplication-divergence. Additional sophistications extending t…

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
Kai He, Ruofan Liang, Jacob Munkberg, Jon Hasselgren, Nandita Vijaykumar, Alexander Keller, Sanja Fidler, Igor Gilitschenski, Zan Gojcic, Zian Wang
https://arxiv.org/abs/2506.15673

UniRelight: Learning Joint Decomposition and Synthesis for Video Relighting
We address the challenge of relighting a single image or video, a task that demands precise scene intrinsic understanding and high-quality light transport synthesis. Existing end-to-end relighting models are often limited by the scarcity of paired multi-illumination data, restricting their ability to generalize across diverse scenes. Conversely, two-stage pipelines that combine inverse and forward rendering can mitigate data requirements but are susceptible to error accumulation and often fail …

Turbulent stretching of dumbbells with hydrodynamic interactions: an analytical study
Jason R. Picardo, Dario Vincenzi
https://arxiv.org/abs/2506.14282 htt…

Turbulent stretching of dumbbells with hydrodynamic interactions: an analytical study
We study the stretching of an elastic dumbbell in a turbulent flow, with the aim of understanding and quantifying the effect of hydrodynamic interactions (HI) between the beads of the dumbbell. Adopting the Batchelor-Kraichnan model for the flow, we derive a Fokker-Planck equation and solve it analytically to obtain the probability distribution of the dumbbell's extension. Using different formulations of the HI tensor, we find that HI preferentially enhances the stretching of stiff dumbbells, i…

Detection, attribution, and modeling of climate change: key open issues
Nicola Scafetta
https://arxiv.org/abs/2506.13994 https://arxi…

Detection, attribution, and modeling of climate change: key open issues
The CMIP global climate models (GCMs) assess that nearly 100% of global surface warming observed between 1850-1900 and 2011-2020 is attributable to anthropogenic drivers like greenhouse gas emissions. These models also generate future climate projections based on shared socioeconomic pathways (SSPs), aiding in risk assessment and the development of costly Net-Zero climate mitigation strategies. Yet, the CMIP GCMs face significant scientific challenges in attributing and modeling climate change,…

[2025-06-18 Wed (UTC), 3 new articles found for cs.CC Computational Complexity]
toXiv_bot_toot

[2025-06-18 Wed (UTC), 2 new articles found for math.RA Rings and Algebras]
toXiv_bot_toot

[2025-06-19 Thu (UTC), 4 new articles found for math.LO Logic]
toXiv_bot_toot

Replaced article(s) found for cs.LG. https://arxiv.org/list/cs.LG/new
[5/8]:
Latent Structured Hopfield Network for Semantic Association and Retrieval

Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
Ankan Deria, Adinath Madhavrao Dukre, Feilong Tang, Sara Atito, Sudipta Roy, Muhammad Awais, Muhammad Haris Khan, Imran Razzak
https://arxiv.org/abs/2506.15649

Dual-Stage Value-Guided Inference with Margin-Based Reward Adjustment for Fast and Faithful VLM Captioning
Despite significant advances in inference-time search for vision-language models (VLMs), existing approaches remain both computationally expensive and prone to unpenalized, low-confidence generations which often lead to persistent hallucinations. We introduce \textbf{Value-guided Inference with Margin-based Reward (ViMaR)}, a two-stage inference framework that improves both efficiency and output fidelity by combining a temporal-difference value model with a margin-aware reward adjustment. In th…

Advanced Langevin thermostats: Properties, extensions to rheology, and a lean momentum-conserving approach
Shubham Agarwal, Sergey V. Sukhomlinov, Marc Honecker, Martin H. M\"user
https://arxiv.org/abs/2506.15579

Advanced Langevin thermostats: Properties, extensions to rheology, and a lean momentum-conserving approach
The Langevin equation accounts for unresolved bath degrees of freedom driving the system toward the bath temperature. Because of this, numerical solutions of the Langevin equation have a long history. Here, we recapitulate, combine, and extend existing Langevin-equation based thermostats, scrutinize their properties and demonstrate their superiority over global kinetic-energy controls. Our work includes compact, asymptotic-analysis based derivations of stochastic thermostats, including the high…

Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Shuo Xing, Lanqing Guo, Hongyuan Hua, Seoyoung Lee, Peiran Li, Yufei Wang, Zhangyang Wang, Zhengzhong Tu
https://arxiv.org/abs/2506.15645

Demystifying the Visual Quality Paradox in Multimodal Large Language Models
Recent Multimodal Large Language Models (MLLMs) excel on benchmark vision-language tasks, yet little is known about how input visual quality shapes their responses. Does higher perceptual quality of images already translate to better MLLM understanding? We conduct the first systematic study spanning leading MLLMs and a suite of vision-language benchmarks, applying controlled degradations and stylistic shifts to each image. Surprisingly, we uncover a visual-quality paradox: model, task, and even…

Harnessing the "Reactive Falling Effect" for rehabilitation and performance boosting
Paul-Emmanuel Sornette, Didier Sornette
https://arxiv.org/abs/2506.13959

Harnessing the "Reactive Falling Effect" for rehabilitation and performance boosting
We present Logic Workout, a novel training method based on radical dynamic instability combining rolling, deformation and spring instability on small fitballs. By exploiting the "reactive falling effect", it re-engages innate balance mechanisms and forces real-time motor corrections, leading to better joint control, coordination, and movement precision. Preliminary results from a cohort of 18 participants show complete resolution of chronic pain, enhanced functional mobility, and surprising imp…

FindingDory: A Benchmark to Evaluate Memory in Embodied Agents
Karmesh Yadav, Yusuf Ali, Gunshi Gupta, Yarin Gal, Zsolt Kira
https://arxiv.org/abs/2506.15635

FindingDory: A Benchmark to Evaluate Memory in Embodied Agents
Large vision-language models have recently demonstrated impressive performance in planning and control tasks, driving interest in their application to real-world robotics. However, deploying these models for reasoning in embodied contexts is limited by their ability to incorporate long-term experience collected across multiple days and represented by vast collections of images. Current VLMs typically struggle to process more than a few hundred images concurrently, highlighting the need for more…

Random walk with multiple memory channels: a new paradigm
Surajit Saha
https://arxiv.org/abs/2506.15145 https://arxiv.org/pdf/2506.15…

Random walk with multiple memory channels: a new paradigm
A new class of one-dimensional, discrete time random walk model with memory, termed "Random walk with $n$ memory channels" (RW$n$MC) is proposed. In this model the information of $n$ ($n\in \mathbb{Z}$) previous steps from the walker's entire history are needed to decide future step. Exact calculation of the mean and variance of position of the RW2MC ($n=2$) has been done which shows that it can lead to asymptotic diffusive and superdiffusive behavior in different parameter regimes. A connectio…

HOIDiNi: Human-Object Interaction through Diffusion Noise Optimization
Roey Ron, Guy Tevet, Haim Sawdayee, Amit H. Bermano
https://arxiv.org/abs/2506.15625

HOIDiNi: Human-Object Interaction through Diffusion Noise Optimization
We present HOIDiNi, a text-driven diffusion framework for synthesizing realistic and plausible human-object interaction (HOI). HOI generation is extremely challenging since it induces strict contact accuracies alongside a diverse motion manifold. While current literature trades off between realism and physical correctness, HOIDiNi optimizes directly in the noise space of a pretrained diffusion model using Diffusion Noise Optimization (DNO), achieving both. This is made feasible thanks to our ob…

Recent trends in socio-epidemic modelling: behaviours and their determinants
Daniele Proverbio, Riccardo Tessarin, Giulia Giordano
https://arxiv.org/abs/2506.13837

Recent trends in socio-epidemic modelling: behaviours and their determinants
The spreading dynamics of infectious diseases is influenced by individual behaviours, which are in turn affected by the level of awareness about the epidemic. Modelling the co-evolution of disease transmission and behavioural changes within a population enables better understanding, prediction and control of epidemics. Here, our primary goal is to provide an overview of the most popular modelling approaches, ranging from compartmental mean-field to agent-based models, with a particular focus on…

Benchmarks for protocol control in nonequilibrium statistical mechanics
Stephen Whitelam, Corneel Casert, Megan Engel, Isaac Tamblyn
https://arxiv.org/abs/2506.15122

Benchmarks for protocol control in nonequilibrium statistical mechanics
We present a set of computer codes designed to test methods for optimizing time-dependent control protocols in fluctuating nonequilibrium systems. Each problem consists of a stochastic model, an optimization objective, and C++ and Python implementations that can be run on Unix-like systems. These benchmark systems are simple enough to run on a laptop, but challenging enough to test the capabilities of modern optimization methods. This release includes five problems and a worked example. The pro…

BoxFusion: Reconstruction-Free Open-Vocabulary 3D Object Detection via Real-Time Multi-View Box Fusion
Yuqing Lan, Chenyang Zhu, Zhirui Gao, Jiazhao Zhang, Yihan Cao, Renjiao Yi, Yijie Wang, Kai Xu
https://arxiv.org/abs/2506.15610

BoxFusion: Reconstruction-Free Open-Vocabulary 3D Object Detection via Real-Time Multi-View Box Fusion
Open-vocabulary 3D object detection has gained significant interest due to its critical applications in autonomous driving and embodied AI. Existing detection methods, whether offline or online, typically rely on dense point cloud reconstruction, which imposes substantial computational overhead and memory constraints, hindering real-time deployment in downstream tasks. To address this, we propose a novel reconstruction-free online framework tailored for memory-efficient and real-time 3D detecti…

Quantum Radar and Research Assessment
Gaspare Galati, Gabriele Pavan, Frederick Daum
https://arxiv.org/abs/2506.13797 https://arxiv.o…

Quantum Radar and Research Assessment
Quantum Radar was studied in many Nations for about fifteen years with the production of some hundred publications. In the post 2020 literature, it is shown that, due to the exceedingly low transmitted power, Quantum Radar cannot produce neither significant results nor real world applications. Regrettably, most of the scientific community ignored this negative outcome: a fact worth of exam. A detailed study of such an assessment failure depicts the main shortcomings of the present situation, ca…

Generative thermodynamic computing
Stephen Whitelam
https://arxiv.org/abs/2506.15121 https://arxiv.org/pdf/2506.15121

Generative thermodynamic computing
We introduce a generative modeling framework for thermodynamic computing, in which structured data is synthesized from noise by the natural time evolution of a physical system governed by Langevin dynamics. While conventional diffusion models use neural networks to perform denoising, here the information needed to generate structure from noise is encoded by the dynamics of a thermodynamic system. Training proceeds by maximizing the probability with which the computer generates the reverse of a …

Belief propagation for networks with loops: The neighborhoods-intersections-based method
Pedro Hack
https://arxiv.org/abs/2506.13791 https://

Belief propagation for networks with loops: The neighborhoods-intersections-based method
In order to diminish the damaging effect of loops on belief propagation (BP), the first explicit version of generalized BP for networks, the KCN-method, was recently introduced. Despite its success, the KCN-method spends computational resources inefficiently. Such inefficiencies can quickly turn the exact application of the method unfeasible, since its time complexity increases exponentially with them. This affects for instance tree networks, for which, despite not offering any accuracy advanta…

High-Throughput Computation of Anharmonic Low-Frequency Protein Vibrations
Michael A. Sauer, Souvik Mondal, Madeline Cano, Matthias Heyden
https://arxiv.org/abs/2506.15109

High-Throughput Computation of Anharmonic Low-Frequency Protein Vibrations
At room temperature, low frequency vibrations at far-infrared frequencies are thermally excited ($k_B T > h ν$) and not restricted to harmonic fluctuations around a single potential energy minimum. For folded proteins, these intrinsically anharmonic vibrations can contain information on slow conformational transitions. Recently, we have developed FREquency-SElective ANharmonic (FRESEAN) mode analysis, a method based on time correlation functions that isolates low-frequency vibrational motions …

Infected Smallville: How Disease Threat Shapes Sociality in LLM Agents
Soyeon Choi, Kangwook Lee, Oliver Sng, Joshua M. Ackerman
https://arxiv.org/abs/2506.13783

Infected Smallville: How Disease Threat Shapes Sociality in LLM Agents
How does the threat of infectious disease influence sociality among generative agents? We used generative agent-based modeling (GABM), powered by large language models, to experimentally test hypotheses about the behavioral immune system. Across three simulation runs, generative agents who read news about an infectious disease outbreak showed significantly reduced social engagement compared to agents who received no such news, including lower attendance at a social gathering, fewer visits to th…

Quantum and Semi-Classical Signatures of Dissipative Chaos in the Steady State
Griffith Rufo, Sabrina Rufo, Pedro Ribeiro, Stefano Chesi
https://arxiv.org/abs/2506.14961

Quantum and Semi-Classical Signatures of Dissipative Chaos in the Steady State
We investigate the quantum-classical correspondence in open quantum many-body systems using the SU(3) Bose-Hubbard trimer as a minimal model. Combining exact diagonalization with semiclassical Langevin dynamics, we establish a direct connection between classical trajectories characterized by fixed-point attractors, limit cycles, or chaos and the spectral and structural properties of the quantum steady state. We show that classical dynamical behavior, as quantified by the sign of the Lyapunov ex…

[2025-06-19 Thu (UTC), 9 new articles found for cond-mat.stat-mech Statistical Mechanics]
toXiv_bot_toot

Ball path curvature and in-game free throw shooting proficiency in the National Basketball Association
Ruoqian Zhu, Dave Love, Scott Powers
https://arxiv.org/abs/2506.13779

Ball path curvature and in-game free throw shooting proficiency in the National Basketball Association
Basketball shooting coaches agree that smoother shooting motions are better, but there is less agreement about what "smooth" means quantitatively or what part of the shooting motion needs to be smooth. Using ball tracking data from the 2023-2024 National Basketball Association regular season, we explore the relationship between ball path curvature and free throw shooting performance. We fit Bézier curves to the ball tracking data in the sagittal plane and test different methods of calculating …

A Survey of Physics-Informed AI for Complex Urban Systems
En Xu, Huandong Wang, Yunke Zhang, Sibo Li, Yinzhou Tang, Zhilun Zhou, Yuming Lin, Yuan Yuan, Xiaochen Fan, Jingtao Ding, Yong Li
https://arxiv.org/abs/2506.13777

A Survey of Physics-Informed AI for Complex Urban Systems
Urban systems are typical examples of complex systems, where the integration of physics-based modeling with artificial intelligence (AI) presents a promising paradigm for enhancing predictive accuracy, interpretability, and decision-making. In this context, AI excels at capturing complex, nonlinear relationships, while physics-based models ensure consistency with real-world laws and provide interpretable insights. We provide a comprehensive review of physics-informed AI methods in urban applica…

From Attraction to Repulsion: Emergent Interactions in Harmonically Coupled Active Binary System
Ritwick Sarkar, Sreya Chatterjee, Urna Basu
https://arxiv.org/abs/2506.14484

From Attraction to Repulsion: Emergent Interactions in Harmonically Coupled Active Binary System
We investigate the emergent interactions between two active Brownian particles coupled by an attractive harmonic potential and in contact with a thermal reservoir. By analyzing the stationary distribution of their separation, we demonstrate that the effective interaction can be either attractive or repulsive, depending on the interplay between activity, coupling strength, and temperature. Notably, we find that an effective short-range repulsion emerges in the strong and moderate-coupling regime…

[2025-06-18 Wed (UTC), 10 new articles found for physics.soc-ph Physics and Society]
toXiv_bot_toot