Tootfinder

SafeBimanual: Diffusion-based Trajectory Optimization for Safe Bimanual Manipulation
Haoyuan Deng, Wenkai Guo, Qianzhun Wang, Zhenyu Wu, Ziwei Wang
https://arxiv.org/abs/2508.18268

SafeBimanual: Diffusion-based Trajectory Optimization for Safe Bimanual Manipulation
Bimanual manipulation has been widely applied in household services and manufacturing, which enables the complex task completion with coordination requirements. Recent diffusion-based policy learning approaches have achieved promising performance in modeling action distributions for bimanual manipulation. However, they ignored the physical safety constraints of bimanual manipulation, which leads to the dangerous behaviors with damage to robots and objects. To this end, we propose a test-time tr…

Minimal value set binomials and Frobenius nonclassical curves
Tiago Aprigio, Jo\~ao Paulo Guardieiro
https://arxiv.org/abs/2508.16541 https://arxiv.org/pdf…

Minimal value set binomials and Frobenius nonclassical curves
In this paper, we characterize all minimal value set binomials over $\mathbb{F}_q$, that is, binomials whose size of the set of images is the smallest possible. With this information, we also classify all quadrinomial curves with separated variables that are $\mathbb{F}_q$-Frobenius nonclassical for the morphism of lines.

Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality
Daniele De Sensi, Saverio Pasqualoni, Lorenzo Piarulli, Tommaso Bonato, Seydou Ba, Matteo Turisini, Jens Domke, Torsten Hoefler
https://arxiv.org/abs/2508.17311

Bine Trees: Enhancing Collective Operations by Optimizing Communication Locality
Communication locality plays a key role in the performance of collective operations on large HPC systems, especially on oversubscribed networks where groups of nodes are fully connected internally but sparsely linked through global connections. We present Bine (binomial negabinary) trees, a family of collective algorithms that improve communication locality. Bine trees maintain the generality of binomial trees and butterflies while cutting global-link traffic by up to 33%. We implement eight Bi…

“sinds kort hebben Duitsers in ons land een nieuwe trekpleister gevonden: het op één na drukste fietspad en de grootste fietsenstalling ter wereld. Steeds meer oosterburen komen speciaal naar Utrecht om zich te vergapen aan de eindeloze stroom fietsers.”
https://www.

Duitse toeristen stromen massaal naar Utrecht om zich te vergapen aan fietsfiles
Natuurlijk, ze zijn dol op Scheveningen, Frau Antje en de bloembollenvelden. Maar sinds kort hebben Duitsers in ons land een nieuwe trekpleister gevonden: het op één na drukste fietspad en de grootste fietsenstalling ter wereld. Steeds meer oosterburen komen speciaal naar Utrecht om zich te vergapen aan de eindeloze stroom fietsers.

Geen verrassing....
https://www.ad.nl/binnenland/sterke-signalen-dat-russen-achter-hack-om-zitten-zaten-mogelijk-weken-in-systeem~a6bd3c60/

Sterke signalen dat Russen achter hack OM zitten, zaten mogelijk weken in systeem
Er zijn sterke aanwijzingen dat de hack bij het Openbaar Ministerie gelinkt is aan Rusland. Dat zeggen goed ingevoerde bronnen binnen justitie tegen deze site. De hackers hebben mogelijk wekenlang toegang gehad tot computers van justitie.

Deep Pre-trained Time Series Features for Tree Species Classification in the Dutch Forest Inventory
Takayuki Ishikawa, Carmelo Bonannella, Bas J. W. Lerink, Marc Ru{\ss}wurm
https://arxiv.org/abs/2508.18829

Deep Pre-trained Time Series Features for Tree Species Classification in the Dutch Forest Inventory
National Forest Inventory (NFI)s serve as the primary source of forest information, providing crucial tree species distribution data. However, maintaining these inventories requires labor-intensive on-site campaigns. Remote sensing approaches, particularly when combined with machine learning, offer opportunities to update NFIs more frequently and at larger scales. While the use of Satellite Image Time Series has proven effective for distinguishing tree species through seasonal canopy reflectanc…

Ich gehe gerne in die Tiefe, ich bin ein echter Tiefenerder.

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives
Huayi Zhou, Kui Jia
https://arxiv.org/abs/2509.21256 https://arxiv.org/pdf…

BiNoMaP: Learning Category-Level Bimanual Non-Prehensile Manipulation Primitives
Non-prehensile manipulation, encompassing ungraspable actions such as pushing, poking, and pivoting, represents a critical yet underexplored domain in robotics due to its contact-rich and analytically intractable nature. In this work, we revisit this problem from two novel perspectives. First, we move beyond the usual single-arm setup and the strong assumption of favorable external dexterity such as walls, ramps, or edges. Instead, we advocate a generalizable dual-arm configuration and establis…

Universal Matrices for Counting Fibonomial and $C$-nomial Coefficients by their $p$-adic Valuations
Arav Chand
https://arxiv.org/abs/2508.18461 https://arx…

Universal Matrices for Counting Fibonomial and $C$-nomial Coefficients by their $p$-adic Valuations
Rowland found a matrix product formula for generating functions counting binomial coefficients by their $p$-adic valuations. A natural generalization of binomial coefficients was introduced by Knuth and Wilf defined by a sequence $C$. We obtain analogous matrix product formulas counting these $C$-nomial coefficients when $C$ is a strong divisibility sequence. Surprisingly, the matrices are universal in the sense that they are independent of $C$. We further extend this product to $C$-multinomial…

ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation
Jason Chen, I-Chun Arthur Liu, Gaurav Sukhatme, Daniel Seita
https://arxiv.org/abs/2509.19454 https://…

ROPA: Synthetic Robot Pose Generation for RGB-D Bimanual Data Augmentation
Training robust bimanual manipulation policies via imitation learning requires demonstration data with broad coverage over robot poses, contacts, and scene contexts. However, collecting diverse and precise real-world demonstrations is costly and time-consuming, which hinders scalability. Prior works have addressed this with data augmentation, typically for either eye-in-hand (wrist camera) setups with RGB inputs or for generating novel images without paired actions, leaving augmentation for eye…