Tootfinder

We-Math 2.0: A Versatile MathBook System for Incentivizing Visual Mathematical Reasoning
Runqi Qiao, Qiuna Tan, Peiqing Yang, Yanzi Wang, Xiaowan Wang, Enhui Wan, Sitong Zhou, Guanting Dong, Yuchen Zeng, Yida Xu, Jie Wang, Chong Sun, Chen Li, Honggang Zhang
https://arxiv.org/abs/2508.10433

We-Math 2.0: A Versatile MathBook System for Incentivizing Visual Mathematical Reasoning
Multimodal Large Language Models (MLLMs) have demonstrated impressive capabilities across various tasks, but still struggle with complex mathematical reasoning. Existing research primarily focuses on dataset construction and method optimization, often overlooking two critical aspects: comprehensive knowledge-driven design and model-centric data space modeling. In this paper, we introduce We-Math 2.0, a unified system that integrates a structured mathematical knowledge system, model-centric data…

TikTok users are posting AI-generated videos, seemingly made with Google's Veo 3, depicting racist and antisemitic tropes that have garnered millions of views (Abbie Richards/Media Matters for America)
https://www.mediamatters.org/tiktok/racist

Racist AI-generated videos are the newest slop garnering millions of views on TikTok

A Mathematical Model of Wound Healing: Effects of Local and Systemic Factors
Alinafe Maenje, Joseph Malinzi
https://arxiv.org/abs/2509.12126 https://arxiv.…

A Mathematical Model of Wound Healing: Effects of Local and Systemic Factors
This study presents a mathematical model formulated as a system of first-order non-linear ordinary differential equations, aimed at examining the effects of different factors, classified as local and systemic factors on a wound healing process. Specifically, the model incorporates pathogens, inflammatory cells, fibroblast cells, collagen, and the initial wound size. The variables utilized in the model lack specific units since they represent combined responses of different cell types. As such, …

Multimodal Mathematical Reasoning with Diverse Solving Perspective
Wenhao Shi, Zhiqiang Hu, Yi Bin, Yang Yang, See-Kiong Ng, Heng Tao Shen
https://arxiv.org/abs/2507.02804

Multimodal Mathematical Reasoning with Diverse Solving Perspective
Recent progress in large-scale reinforcement learning (RL) has notably enhanced the reasoning capabilities of large language models (LLMs), especially in mathematical domains. However, current multimodal LLMs (MLLMs) for mathematical reasoning often rely on one-to-one image-text pairs and single-solution supervision, overlooking the diversity of valid reasoning perspectives and internal reflections. In this work, we introduce MathV-DP, a novel dataset that captures multiple diverse solution tra…

Estoy pasando mis notas del curro a limpio con #orgroam y se pueden hacer gršficos tan chulis y molones como este mediante #orgroamui

"In the first 21 months of war, 104 flights supplied the equivalent of just four days of food for Gaza, Israeli data shows, for a cost running to tens of millions of dollars. Spent on trucks, the same budget would deliver much more food"
#GazaGenocide
#GazaStarvation …

Centered Moments of Weighted One-Level Densities of $GL(2)$ $L$-Functions
Lawrence Dillon, Xiaoyao Huang, Say-Yeon Kwon, Meiling Laurence, Steven J. Miller, Vishal Muthuvel, Luke Rowen, Pramana Saldin, Steven Zanetti
https://arxiv.org/abs/2509.05810

Centered Moments of Weighted One-Level Densities of $GL(2)$ $L$-Functions
Katz and Sarnak conjectured that the behavior of zeros near the central point of any family of $L$-functions is well-modeled by the behavior of eigenvalues near $1$ of some classical compact group (either the symplectic, unitary, or even, odd, or full orthogonal group). In 2018, Knightly and Reno proved that the symmetry group can vary depending on how the $L$-functions in the family are weighted. They observed both orthogonal and symplectic symmetry in the one-level densities of families of cu…

Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks
Pietro Giuseppe Fr\'e, Federico Milanesio, Guido Sanguinetti, Matteo Santoro
https://arxiv.org/abs/2507.16871

Navigation through Non-Compact Symmetric Spaces: a mathematical perspective on Cartan Neural Networks
Recent work has identified non-compact symmetric spaces U/H as a promising class of homogeneous manifolds to develop a geometrically consistent theory of neural networks. An initial implementation of these concepts has been presented in a twin paper under the moniker of Cartan Neural Networks, showing both the feasibility and the performance of these geometric concepts in a machine learning context. The current paper expands on the mathematical structures underpinning Cartan Neural Networks, de…

Crosslisted article(s) found for q-fin.MF. https://arxiv.org/list/q-fin.MF/new
[1/1]:
- Optimal Risk Sharing Without Preference Convexity: An Aggregate Convexity Approach
Vasily Melnikov