Tootfinder

Polymarket raised "double-digit millions" from 1789 Capital, which Donald Trump Jr. joined as a partner in 2024; Trump Jr. will join Polymarket's advisory board (Dan Primack/Axios)
https://www.axios.com/2025/08/26/trump-jr-vc-fund-polymarket

Scoop: Donald Trump Jr.'s VC firm bets on Polymarket
1789 Capital invested double-digit millions of dollars into Polymarket

🪙 Polymer-protected DNA sensors enable two-month storage for 50-cent disease diagnostics
#dna…

Polymer-protected DNA sensors enable two-month storage for 50-cent disease diagnostics
Using an inexpensive electrode coated with DNA, MIT researchers have designed disposable diagnostics that could be adapted to detect a variety of diseases, including cancer or infectious diseases such as influenza and HIV.

Varje gång jag ser ett bi eller en humla på min balkong blir jag glad. #pollineramera #photography

STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner
Zhou Tianxing, Wang Zhirui, Ao Haojia, Chen Guangyan, Xing Boyang, Cheng Jingwen, Yang Yi, Yue Yufeng
https://arxiv.org/abs/2506.21030

STEP Planner: Constructing cross-hierarchical subgoal tree as an embodied long-horizon task planner
The ability to perform reliable long-horizon task planning is crucial for deploying robots in real-world environments. However, directly employing Large Language Models (LLMs) as action sequence generators often results in low success rates due to their limited reasoning ability for long-horizon embodied tasks. In the STEP framework, we construct a subgoal tree through a pair of closed-loop models: a subgoal decomposition model and a leaf node termination model. Within this framework, we develo…

Largest planar graphs of diameter $3$ and fixed maximum degree -- connection with fractional matchings
Antoine Dailly, Sasha Darmon, Ugo Giocanti, Claire Hilaire, Petru Valicov
https://arxiv.org/abs/2507.18797

Largest planar graphs of diameter $3$ and fixed maximum degree -- connection with fractional matchings
The degree diameter problem asks for the maximum possible number of vertices in a graph of maximum degree $Δ$ and diameter $D$. In this paper, we focus on planar graphs of diameter $3$. Fellows, Hell and Seyffarth (1995) proved that for all $Δ\geq 8$, the maximum number $\mathrm{np}_{Δ, D}$ of vertices of a planar graph with maximum degree at most $Δ$ and diameter at most 3 satisfies $\frac{9}{2}Δ- 3 \leq \mathrm{np}_{Δ,3} \leq 8 Δ+ 12$. We show that the lower bound they gave is optimal,…

MAGA Candidate Torches the Quran in Deranged Flamethrower Ad (Ewan Palmer/The Daily Beast)
https://www.thedailybeast.com/maga-candidate-valentina-gomez-flamethrowers-the-quran-in-deranged-campaign-ad/
http://www.memeorandum.com/250826/p79#a250826p79

Diverse polymorphs and phase transitions in van der Waals In$_2$Se$_3$
Mingfeng Liu, Jiantao Wang, Peitao Liu, Qiang Wang, Zhibo Liu, Yan Sun, Xing-Qiu Chen
https://arxiv.org/abs/2506.21248

Diverse polymorphs and phase transitions in van der Waals In$_2$Se$_3$
Van der Waals In$_2$Se$_3$ has garnered significant attention due to its unique properties and wide applications associated with its rich polymorphs and polymorphic phase transitions. Despite extensive studies, the vast complex polymorphic phase space remains largely unexplored, and the underlying microscopic mechanism for their phase transformations remains elusive. Here, we develop a highly accurate, efficient, and reliable machine-learning potential (MLP), which not only facilitates accurate…

Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks
Hugo Attali, Thomas Papastergiou, Nathalie Pernelle, Fragkiskos D. Malliaros
https://arxiv.org/abs/2508.19071

Dynamic Triangulation-Based Graph Rewiring for Graph Neural Networks
Graph Neural Networks (GNNs) have emerged as the leading paradigm for learning over graph-structured data. However, their performance is limited by issues inherent to graph topology, most notably oversquashing and oversmoothing. Recent advances in graph rewiring aim to mitigate these limitations by modifying the graph topology to promote more effective information propagation. In this work, we introduce TRIGON, a novel framework that constructs enriched, non-planar triangulations by learning to…

IMA-Catcher: An IMpact-Aware Nonprehensile Catching Framework based on Combined Optimization and Learning
Francesco Tassi (Human-Robot Interfaces and Interaction Lab., Istituto Italiano di Tecnologia, Italy), Jianzhuang Zhao (Human-Robot Interfaces and Interaction Lab., Istituto Italiano di Tecnologia, Italy), Gustavo J. G. Lahr (Human-Robot Interfaces and Interaction Lab., Istituto Italiano di Tecnologia, Italy), Luna Gava (Event-Driven Perception for Robotics Lab, Istituto Italiano d…

IMA-Catcher: An IMpact-Aware Nonprehensile Catching Framework based on Combined Optimization and Learning
Robotic catching of flying objects typically generates high impact forces that might lead to task failure and potential hardware damages. This is accentuated when the object mass to robot payload ratio increases, given the strong inertial components characterizing this task. This paper aims to address this problem by proposing an implicitly impact-aware framework that accomplishes the catching task in both pre- and post-catching phases. In the first phase, a motion planner generates optimal tra…

A Fast and Light-weight Non-Iterative Visual Odometry with RGB-D Cameras
Zheng Yang, Kuan Xu, Shenghai Yuan, Lihua Xie
https://arxiv.org/abs/2507.18886 https://

A Fast and Light-weight Non-Iterative Visual Odometry with RGB-D Cameras
In this paper, we introduce a novel approach for efficiently estimating the 6-Degree-of-Freedom (DoF) robot pose with a decoupled, non-iterative method that capitalizes on overlapping planar elements. Conventional RGB-D visual odometry(RGBD-VO) often relies on iterative optimization solvers to estimate pose and involves a process of feature extraction and matching. This results in significant computational burden and time delays. To address this, our innovative method for RGBD-VO separates the …