Tootfinder

Goodness, does this mean we can expect a strongly-worded letter next? https://mastodon.social/@EndIsraeliApartheid/114675920702558762

Sources: Palmer Luckey's stablecoin startup Atticus raised ~$250M at a $2.25B valuation, and will merge into Erebor, formed by Luckey to get a banking license (Axios)
https://www.axios.com/pro/fintech-deals/2025/06/13/palmer-luckey-er…

Scoop: New details on Palmer Luckey's crypto unicorn
Atticus will merge into Erebor, recently formed by Luckey with plans to get a banking license.

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Ashley Samuelson, Andrew K. Hirsch, Ethan Cecchetti
https://arxiv.org/abs/2506.10913 h…

Choreographic Quick Changes: First-Class Location (Set) Polymorphism
Choreographic programming is a promising new paradigm for programming concurrent systems where a developer writes a single centralized program that compiles to individual programs for each node. Existing choreographic languages, however, lack critical features integral to modern systems, like the ability of one node to dynamically compute who should perform a computation and send that decision to others. This work addresses this gap with $λ_{QC}$, the first typed choreographic language with \e…

Counting Small Cycle Double Covers
Jorik Jooken, Ben Seamone, Carol T. Zamfirescu
https://arxiv.org/abs/2506.10604 https://arxiv.org/…

Counting Small Cycle Double Covers
A theorem due to Seyffarth states that every planar $4$-connected $n$-vertex graph has a cycle double cover (CDC) containing at most $n-1$ cycles (a "small" CDC). We extend this theorem by proving that, in fact, such a graph must contain linearly many small CDCs (in terms of $n$), and provide stronger results in the case of planar $4$-connected triangulations. We complement this result with constructions of planar $4$-connected graphs which contain at most polynomially many small CDCs. Thereaft…

Vib2Move: In-Hand Object Reconfiguration via Fingertip Micro-Vibrations
Xili Yi, Nima Fazeli
https://arxiv.org/abs/2506.10923 https://

Vib2Move: In-Hand Object Reconfiguration via Fingertip Micro-Vibrations
We introduce Vib2Move, a novel approach for in-hand object reconfiguration that uses fingertip micro-vibrations and gravity to precisely reposition planar objects. Our framework comprises three key innovations. First, we design a vibration-based actuator that dynamically modulates the effective finger-object friction coefficient, effectively emulating changes in gripping force. Second, we derive a sliding motion model for objects clamped in a parallel gripper with two symmetric, variable-fricti…

On the Constant-Factor Approximability of Minimum Cost Constraint Satisfaction Problems
Ian DeHaan, Neng Huang, Euiwoong Lee
https://arxiv.org/abs/2507.08693

On the Constant-Factor Approximability of Minimum Cost Constraint Satisfaction Problems
We study minimum cost constraint satisfaction problems (MinCostCSP) through the algebraic lens. We show that for any constraint language $Γ$ which has the dual discriminator operation as a polymorphism, there exists a $|D|$-approximation algorithm for MinCostCSP$(Γ)$ where $D$ is the domain. Complementing our algorithmic result, we show that any constraint language $Γ$ where MinCostCSP$(Γ)$ admits a constant-factor approximation must have a \emph{near-unanimity} (NU) polymorphism …

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Ulzee An, Moonseong Jeong, Simon A. Lee, Aditya Gorla, Yuzhe Yang, Sriram Sankararaman
https://arxiv.org/abs/2507.08254

Raptor: Scalable Train-Free Embeddings for 3D Medical Volumes Leveraging Pretrained 2D Foundation Models
Current challenges in developing foundational models for volumetric imaging data, such as magnetic resonance imaging (MRI), stem from the computational complexity of training state-of-the-art architectures in high dimensions and curating sufficiently large datasets of volumes. To address these challenges, we introduce Raptor (Random Planar Tensor Reduction), a train-free method for generating semantically rich embeddings for volumetric data. Raptor leverages a frozen 2D foundation model, pretra…

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Marcos Abel Zuzu\'arregui, Mustafa Melih Toslak, Stefano Carpin
https://arxiv.org/abs/2506.10106

One For All: LLM-based Heterogeneous Mission Planning in Precision Agriculture
Artificial intelligence is transforming precision agriculture, offering farmers new tools to streamline their daily operations. While these technological advances promise increased efficiency, they often introduce additional complexity and steep learning curves that are particularly challenging for non-technical users who must balance tech adoption with existing workloads. In this paper, we present a natural language (NL) robotic mission planner that enables non-specialists to control heterogen…

Structural Parameterizations of $k$-Planarity
Tatsuya Gima, Yasuaki Kobayashi, Yuto Okada
https://arxiv.org/abs/2506.10717 https://ar…

Structural Parameterizations of $k$-Planarity
The concept of $k$-planarity is extensively studied in the context of Beyond Planarity. A graph is $k$-planar if it admits a drawing in the plane in which each edge is crossed at most $k$ times. The local crossing number of a graph is the minimum integer $k$ such that it is $k$-planar. The problem of determining whether an input graph is $1$-planar is known to be NP-complete even for near-planar graphs [Cabello and Mohar, SIAM J. Comput. 2013], that is, the graphs obtained from planar graphs by…

H-Planarity and Parametric Extensions: when Modulators Act Globally
Fedor V. Fomin, Petr A. Golovach, Laure Morelle, Dimitrios M. Thilikos
https://arxiv.org/abs/2507.08541

H-Planarity and Parametric Extensions: when Modulators Act Globally
We introduce a series of graph decompositions based on the modulator/target scheme of modification problems that enable several algorithmic applications that parametrically extend the algorithmic potential of planarity. In the core of our approach is a polynomial time algorithm for computing planar H-modulators. Given a graph class H, a planar H-modulator of a graph G is a set X \subseteq V(G) such that the ``torso'' of X is planar and all connected components of G - X belong to H. Here, the to…