Tootfinder

Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh
Soumita Roy, Md Muntasir Kamal Dihan, Tasnimah Haque, Nafisa Nomani, Sadia Islam Preety
https://arxiv.org/abs/2507.21254

Determinants of Saving Behavior Among Employees in Dhaka, Bangladesh
Purpose With an emphasis on elements like financial knowledge, financial attitude, social influence, financial self-efficacy, and financial management practices, this study explores the factors that influence employees' saving behavior in Dhaka, Bangladesh. We also welcome others to work on saving behavior, which is the main reason for publishing. The purpose is to make others aware of the methods for quantitative financial behavior analysis in Bangladesh. Design/methodology/approach The study …

Integrating an ISO 30401-compliant Knowledge Management System with the processes of an Integrated Management System
Patrick Prieur, Aline Belloni
https://arxiv.org/abs/2507.18201

Integrating an ISO 30401-compliant Knowledge Management System with the processes of an Integrated Management System
With the evolution of process approaches within organizations, the increasing importance of quality management systems (like ISO 9001) and the recent introduction of ISO 30401 for knowledge management, we examine how these different elements converge within the framework of an Integrated Management System. The article specifically demonstrates how an ISO30401-compliant knowledge management system can be implemented by deploying the mechanisms of the SECI model through the steps of the PDCA cycl…

AutoGraph: A Knowledge-Graph Framework for Modeling Interface Interaction and Automating Procedure Execution in Digital Nuclear Control Rooms
Xingyu Xiao, Jiejuan Tong, Jun Sun, Zhe Sui, Jingang Liang, Hongru Zhao, Jun Zhao, Haitao Wang
https://arxiv.org/abs/2506.18727

AutoGraph: A Knowledge-Graph Framework for Modeling Interface Interaction and Automating Procedure Execution in Digital Nuclear Control Rooms
Digitalization in nuclear power plant (NPP) control rooms is reshaping how operators interact with procedures and interface elements. However, existing computer-based procedures (CBPs) often lack semantic integration with human-system interfaces (HSIs), limiting their capacity to support intelligent automation and increasing the risk of human error, particularly under dynamic or complex operating conditions. In this study, we present AutoGraph, a knowledge-graph-based framework designed to form…

This https://arxiv.org/abs/2505.07843 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_csGR_…

PosterO: Structuring Layout Trees to Enable Language Models in Generalized Content-Aware Layout Generation
In poster design, content-aware layout generation is crucial for automatically arranging visual-textual elements on the given image. With limited training data, existing work focused on image-centric enhancement. However, this neglects the diversity of layouts and fails to cope with shape-variant elements or diverse design intents in generalized settings. To this end, we proposed a layout-centric approach that leverages layout knowledge implicit in large language models (LLMs) to create posters…

Polynomial fingerprinting for trees and formulas
Mihai Prunescu
https://arxiv.org/abs/2506.21114 https://arxiv.org/pdf/2506.21114

Polynomial fingerprinting for trees and formulas
To cater to the needs of (Zero Knowledge) proofs for (mathematical) proofs, we describe a method to transform formal sentences in 2x2 - matrices over multivariate polynomials with integer coefficients, such that usual proof-steps like modus-ponens or the substitution are easy to compute from the matrices corresponding to the terms or formulas used as arguments. By evaluating the polynomial variables in random elements of a suitably chosen finite field, the proof is replaced by a numeric sequenc…

Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
Felipe Olivares, Massimiliano Zanin
https://arxiv.org/abs/2507.20927 h…

Beyond Classical Models: Statistical Physics Tools for the Analysis of Time Series in Modern Air Transport
Within the continuous endeavour of improving the efficiency and resilience of air transport, the trend of using concepts and metrics from statistical physics has recently gained momentum. This scientific discipline, which integrates elements from physics and statistics, aims at extracting knowledge about the microscale rules governing a (potentially complex) system when only its macroscale is observable. Translated to air transport, this entails extracting information about how individual opera…

A Survey of Link Prediction in N-ary Knowledge Graphs
Jiyao Wei, Saiping Guan, Da Li, Xiaolong Jin, Jiafeng Guo, Xueqi Cheng
https://arxiv.org/abs/2506.08970

A Survey of Link Prediction in N-ary Knowledge Graphs
N-ary Knowledge Graphs (NKGs) are a specialized type of knowledge graph designed to efficiently represent complex real-world facts. Unlike traditional knowledge graphs, where a fact typically involves two entities, NKGs can capture n-ary facts containing more than two entities. Link prediction in NKGs aims to predict missing elements within these n-ary facts, which is essential for completing NKGs and improving the performance of downstream applications. This task has recently gained significan…

From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training
Mingyang Yao, Ke Chen
https://arxiv.org/abs/2506.17497 ht…

From Generality to Mastery: Composer-Style Symbolic Music Generation via Large-Scale Pre-training
Despite progress in controllable symbolic music generation, data scarcity remains a challenge for certain control modalities. Composer-style music generation is a prime example, as only a few pieces per composer are available, limiting the modeling of both styles and fundamental music elements (e.g., melody, chord, rhythm). In this paper, we investigate how general music knowledge learned from a broad corpus can enhance the mastery of specific composer styles, with a focus on piano piece genera…

Data Verbalisation: What is Text Doing in a Data Visualisation?
Paul Murrell
https://arxiv.org/abs/2506.15129 https://arxiv.org/pdf/2…

Data Verbalisation: What is Text Doing in a Data Visualisation?
This article discusses the role that text elements play in a data visualisation. We argue that there is a need for a simple, coherent explanation of text elements similar to the understanding that already exists for non-text elements like bars, points, and lines. We explore examples of how text is used within a data visualisation and use existing knowledge and assessment techniques to evaluate when text is effective and when it is not. The result is a framework that aims to be easy to understan…

State Space Models Naturally Produce Traveling Waves, Time Cells, and Scale to Abstract Cognitive Functions
Sen Lu, Xiaoyu Zhang, Mingtao Hu, Eric Yeu-Jer Lee, Soohyeon Kim, Wei D. Lu
https://arxiv.org/abs/2507.13638

State Space Models Naturally Produce Traveling Waves, Time Cells, and Scale to Abstract Cognitive Functions
A grand challenge in modern neuroscience is to bridge the gap between the detailed mapping of microscale neural circuits and a mechanistic understanding of cognitive functions. While extensive knowledge exists about neuronal connectivity and biophysics, a significant gap remains in how these elements combine to produce flexible, learned behaviors. Here, we propose that a framework based on State-Space Models (SSMs), an emerging class of deep learning architectures, can bridge this gap. We argue…

Structured Graph Representations for Visual Narrative Reasoning: A Hierarchical Framework for Comics
Yi-Chun Chen
https://arxiv.org/abs/2506.10008 https://…

Structured Graph Representations for Visual Narrative Reasoning: A Hierarchical Framework for Comics
This paper presents a hierarchical knowledge graph framework for the structured understanding of visual narratives, focusing on multimodal media such as comics. The proposed method decomposes narrative content into multiple levels, from macro-level story arcs to fine-grained event segments. It represents them through integrated knowledge graphs that capture semantic, spatial, and temporal relationships. At the panel level, we construct multimodal graphs that link visual elements such as charact…

Distillation of atomistic foundation models across architectures and chemical domains
John L. A. Gardner, Daniel F. Thomas du Toit, Chiheb Ben Mahmoud, Zo\'e Faure Beaulieu, Veronika Juraskova, Laura-Bianca Pa\c{s}ca, Louise A. M. Rosset, Fernanda Duarte, Fausto Martelli, Chris J. Pickard, Volker L. Deringer
https://arxiv.or…

Distillation of atomistic foundation models across architectures and chemical domains
Machine-learned interatomic potentials have transformed computational research in the physical sciences. Recent atomistic `foundation' models have changed the field yet again: trained on many different chemical elements and domains, these potentials are widely applicable, but comparably slow and resource-intensive to run. Here we show how distillation via synthetic data can be used to cheaply transfer knowledge from atomistic foundation models to a range of different architectures, unlocking mu…

Next-to-leading-order prediction for the neutrinoless double-beta decay
Y. L. Yang, P. W. Zhao
https://arxiv.org/abs/2505.24121 https://

Next-to-leading-order prediction for the neutrinoless double-beta decay
The neutrinoless double-beta decay ($0νββ$) of two neutrons$nn \rightarrow ppee$ is the elementary subprocess of $0νββ$ decay in nuclei. Accurate knowledge of the $nn \rightarrow ppee$ amplitude is required to pin down the short-range contributions in the nuclear matrix elements of the candidate nuclei for large-scale $0νββ$ searches. In this Letter, we report the first next-to-leading-order prediction of the nn \rightarrow ppee amplitude, with Bayesian uncertainty quantification. This…