Tootfinder

DMA: EU-Kommission prüft mögliche Mediendiskriminierung durch Google
Die EU-Kommission geht dem Verdacht nach, dass Google beim Ranking von Webseiten legitime Inhalte abwertet. Das soll unter anderem Medienangebote betreffen.

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration
Yue Zhou, Litong Feng, Mengcheng Lan, Xue Yang, Qingyun Li, Yiping Ke, Xue Jiang, Wayne Zhang
https://arxiv.org/abs/2509.10059

Multimodal Mathematical Reasoning Embedded in Aerial Vehicle Imagery: Benchmarking, Analysis, and Exploration
Mathematical reasoning is critical for tasks such as precise distance and area computations, trajectory estimations, and spatial analysis in unmanned aerial vehicle (UAV) based remote sensing, yet current vision-language models (VLMs) have not been adequately tested in this domain. To address this gap, we introduce AVI-Math, the first benchmark to rigorously evaluate multimodal mathematical reasoning in aerial vehicle imagery, moving beyond simple counting tasks to include domain-specific knowl…

Šita nuomonė LRT mane įtikino: https://www.lrt.lt/naujienos/nuomones/3/2709205/gediminas-karoblis-matematine-barbaryste

The Ethical and Sustainable Concerns Triangle: A Framework for Navigating Discourses in Mathematics and Its Education
Dennis M\"uller, Maurice Chiodo, Michael Meyer
https://arxiv.org/abs/2510.11327

The Ethical and Sustainable Concerns Triangle: A Framework for Navigating Discourses in Mathematics and Its Education
The literature on ethics and sustainability in mathematics and its education is increasingly complex and fragmented, potentially leading to communication breakdowns between different scholarly traditions. To address this, the paper introduces the "Ethical and Sustainable Concerns Triangle," a framework that maps discourses based on their relative concern for three areas (represented as three vertices in the triangle): "Mathematics", "Community", and "Society/Planet". By integrating a systems th…

Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum Physics
Marco Del Tredici, Jacob McCarran, Benjamin Breen, Javier Aspuru Mijares, Weichen Winston Yin, Jacob M. Taylor, Frank Koppens, Dirk Englund
https://arxiv.org/abs/2510.12787

Ax-Prover: A Deep Reasoning Agentic Framework for Theorem Proving in Mathematics and Quantum Physics
We present Ax-Prover, a multi-agent system for automated theorem proving in Lean that can solve problems across diverse scientific domains and operate either autonomously or collaboratively with human experts. To achieve this, Ax-Prover approaches scientific problem solving through formal proof generation, a process that demands both creative reasoning and strict syntactic rigor. Ax-Prover meets this challenge by equipping Large Language Models (LLMs), which provide knowledge and reasoning, wit…

Mathematical and numerical study of symmetry and positivity of the tensor-valued spring constant defined from P1-FEM for two- and three-dimensional linear elasticity
Oussama Ounissi, Masato Kimura, Hirofumi Notsu
https://arxiv.org/abs/2509.10335

Mathematical and numerical study of symmetry and positivity of the tensor-valued spring constant defined from P1-FEM for two- and three-dimensional linear elasticity
In this study, we consider a spring-block system that approximates a $d$-dimensional linear elastic body, where $d=2$ or $d=3$. We derive a $d\times d$ matrix as the spring constant using the P1 finite element method with a triangular mesh for the linear elasticity equations. We mathematically analyze the symmetry and positive-definiteness of the spring constant. Even if we assume full symmetry of the elasticity tensor, the symmetry of the matrix obtained as the spring constant is not trivial. …

A Mathematics-Guided Approach to Floating-Point Error Detection
Youshuai Tan, Zhanwei Zhang, Zishuo Ding, Lianyu Zheng, Jinfu Chen, Weiyi Shang
https://arxiv.org/abs/2510.10081 …

A Mathematics-Guided Approach to Floating-Point Error Detection
Floating-point program errors can lead to severe consequences, particularly in critical domains such as military applications. Only a small subset of inputs may induce substantial floating-point errors, prompting researchers to develop methods for identifying these error-inducing inputs. Although existing approaches have achieved some success, they still suffer from two major limitations: (1) High computational cost: The evaluation of error magnitude for candidate inputs relies on high-precisio…

»Zukunftssicher verschlüsseln: Post Quantum Cryptography«
Das ist ein Thema mit dem ich mir beschäftige. Nicht mathematisch aber bin am Tool zu erstellen, das uns heute so wie zukünftig im Web sicher(er) macht.
📺 https://www.youtube.com/watch?v=G1bWdLVEHYM

CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images
Chengqi Duan, Kaiyue Sun, Rongyao Fang, Manyuan Zhang, Yan Feng, Ying Luo, Yufang Liu, Ke Wang, Peng Pei, Xunliang Cai, Hongsheng Li, Yi Ma, Xihui Liu
https://arxiv.org/abs/2510.11718

CodePlot-CoT: Mathematical Visual Reasoning by Thinking with Code-Driven Images
Recent advances in Large Language Models (LLMs) and Vision Language Models (VLMs) have shown significant progress in mathematical reasoning, yet they still face a critical bottleneck with problems requiring visual assistance, such as drawing auxiliary lines or plotting functions to solve the problems. Most LLMs and VLMs are constrained to text-only reasoning chains, while multimodal unified models that can generate interleaved text and images lack the necessary precision and controllability for…

Towards a Common Framework for Autoformalization
Agnieszka Mensfelt, David Tena Cucala, Santiago Franco, Angeliki Koutsoukou-Argyraki, Vince Trencsenyi, Kostas Stathis
https://arxiv.org/abs/2509.09810 …

Towards a Common Framework for Autoformalization
Autoformalization has emerged as a term referring to the automation of formalization - specifically, the formalization of mathematics using interactive theorem provers (proof assistants). Its rapid development has been driven by progress in deep learning, especially large language models (LLMs). More recently, the term has expanded beyond mathematics to describe the broader task of translating informal input into formal logical representations. At the same time, a growing body of research explo…