Tootfinder

Discrete-event Tensor Factorization: Learning a Smooth Embedding for Continuous Domains
Joey De Pauw, Bart Goethals
https://arxiv.org/abs/2508.04221 https://

Discrete-event Tensor Factorization: Learning a Smooth Embedding for Continuous Domains
Recommender systems learn from past user behavior to predict future user preferences. Intuitively, it has been established that the most recent interactions are more indicative of future preferences than older interactions. Many recommendation algorithms use this notion to either drop older interactions or to assign them a lower weight, so the model can focus on the more informative, recent information. However, very few approaches model the flow of time explicitly. This paper analyzes how ti…

This https://arxiv.org/abs/2407.03078 has been replaced.
initial toot: https://mastoxiv.page/@arXiv_mat…

Counting Rational Points In Non-Isotropic Neighborhoods of Manifolds
In this manuscript, we initiate the study of the number of rational points with bounded denominators, contained in a non-isotropic $δ_1\times\ldots\times δ_R$ neighborhood of a compact submanifold $\mathcal{M}$ of codimension $R$ in $\mathbb{R}^{M}$. We establish an upper bound for this counting function which holds when $\mathcal{M}$ satisfies a strong curvature condition, first introduced by Schindler-Yamagishi in \cite{schindler2022density}. Further, even in the isotropic case when $δ_1=\…

Hole spin qubits in unstrained Germanium layers
Lorenzo Mauro, Mauricio J. Rodriguez, Esteban A. Rodriguez-Mena, Yann-Michel Niquet
https://arxiv.org/abs/2506.04977

Hole spin qubits in unstrained Germanium layers
Strained germanium heterostructures are one of the most promising material for hole spin qubits but suffer from the strong anisotropy of the gyromagnetic factors that hinders the optimization of the magnetic field orientation. The figures of merit (Rabi frequencies, lifetimes...) can indeed vary by an order of magnitude within a few degrees around the heterostructure plane. We propose to address this issue by confining the holes at the interface of an unstrained, bulk Ge substrate or thick buff…

Efficient DFT of Zadoff-Chu Sequences using lmFH Pattern
Fanping Du
https://arxiv.org/abs/2507.23200 https://arxiv.org/pdf/2507.23200

Efficient DFT of Zadoff-Chu Sequences using lmFH Pattern
Having established that Zadoff-Chu (ZC) sequences are inherently linear micro-frequency hopping (lmFH) symbols, this paper first presents an intuitive and visual exposition of the computation of the DFT and IDFT of ZC sequences using the lmFH pattern. This yields interesting results. Subsequently, an alternative form for computing the cumulative sum of ZC sequences using the Generalized Quadratic Gauss Sum is introduced. Furthermore, building on the micro-frequency hopping (mFH) concept, this p…

In-between Motion Generation Based Multi-Style Quadruped Robot Locomotion
Yuanhao Chen, Liu Zhao, Ji Ma, Peng Lu
https://arxiv.org/abs/2507.23053 https://a…

In-between Motion Generation Based Multi-Style Quadruped Robot Locomotion
Quadruped robots face persistent challenges in achieving versatile locomotion due to limitations in reference motion data diversity. To address these challenges, this approach introduces an in-between motion generation based multi-style quadruped robot locomotion framework, integrating synergistic advances in motion generation and imitation learning. Our approach establishes a unified pipeline addressing two fundamental aspects: First, we propose a CVAE based motion generator, synthesizing mult…

Beyond the LUMIR challenge: The pathway to foundational registration models
Junyu Chen, Shuwen Wei, Joel Honkamaa, Pekka Marttinen, Hang Zhang, Min Liu, Yichao Zhou, Zuopeng Tan, Zhuoyuan Wang, Yi Wang, Hongchao Zhou, Shunbo Hu, Yi Zhang, Qian Tao, Lukas F\"orner, Thomas Wendler, Bailiang Jian, Benedikt Wiestler, Tim Hable, Jin Kim, Dan Ruan, Frederic Madesta, Thilo Sentker, Wiebke Heyer, Lianrui Zuo, Yuwei Dai, Jing Wu, Jerry L. Prince, Harrison Bai, Yong Du, Yihao Liu, Alessa He…

Beyond the LUMIR challenge: The pathway to foundational registration models
Medical image challenges have played a transformative role in advancing the field, catalyzing algorithmic innovation and establishing new performance standards across diverse clinical applications. Image registration, a foundational task in neuroimaging pipelines, has similarly benefited from the Learn2Reg initiative. Building on this foundation, we introduce the Large-scale Unsupervised Brain MRI Image Registration (LUMIR) challenge, a next-generation benchmark designed to assess and advance u…

Do Riemannian Submersions Preserve Positive Intermediate Ricci Curvature?
Hasan M. El-Hasan, Russell Phelan, Frederick Wilhelm
https://arxiv.org/abs/2507.17839 https://

Do Riemannian Submersions Preserve Positive Intermediate Ricci Curvature?
Pro and the third author showed that there are Riemannian submersions $π: M \to B$ with $M$ a compact manifold with positive Ricci curvature, whose base $B$, has Ricci curvatures with both signs. Thus, Riemannian submersions need not preserve positive Ricci curvature. In this note we establish the degree to which this result extends into the setting of positive intermediate Ricci curvature. It is an immediate consequence of the Gray--O'Neill Horizontal curvature equation that if $π: M\to B$…

Causality in the human niche: lessons for machine learning
Richard D. Lange, Konrad P. Kording
https://arxiv.org/abs/2506.13803 https://

Causality in the human niche: lessons for machine learning
Humans interpret the world around them in terms of cause and effect and communicate their understanding of the world to each other in causal terms. These causal aspects of human cognition are thought to underlie humans' ability to generalize and learn efficiently in new domains, an area where current machine learning systems are weak. Building human-like causal competency into machine learning systems may facilitate the construction of effective and interpretable AI. Indeed, the machine learnin…

AI Governance InternationaL Evaluation Index (AGILE Index) 2025
Yi Zeng, Enmeng Lu, Xiaoyang Guo, Cunqing Huangfu, Jiawei Xie, Yu Chen, Zhengqi Wang, Dongqi Liang, Gongce Cao, Jin Wang, Zizhe Ruan, Xin Guan, Ammar Younas
https://arxiv.org/abs/2507.11546

AI Governance InternationaL Evaluation Index (AGILE Index) 2025
The year 2024 witnessed accelerated global AI governance advancements, marked by strengthened multilateral frameworks and proliferating national regulatory initiatives. This acceleration underscores an unprecedented need to systematically track governance progress--an imperative that drove the launch of the AI Governance InternationaL Evaluation Index (AGILE Index) project since 2023. The inaugural AGILE Index, released in February 2024 after assessing 14 countries, established an operational a…

Investigating the Perception of Translational Shape-Changing Haptic Interfaces
Qihan Yang, Xin Zhou, Adam J. Spiers
https://arxiv.org/abs/2506.09801 https:…

Investigating the Perception of Translational Shape-Changing Haptic Interfaces
Shape-changing haptic interfaces (SCHIs) are a promising and emerging field. However, compared to more established stimulus modalities, such as vibration, there is sparse literature on the perception of dynamic shapes. Furthermore, the influence of properties such as grasp types and displacement magnitude/direction has not been formally evaluated. This work attempts to initiate a formal perceptual evaluation of SCHIs via a psychophysical user study involving a 1-DOF translational shape-changing…