Tootfinder

I wished I could disagree with this post but sadly I cannot. I had high hopes for Matrix and still use it but boy is it not fixing the core and conceptual issues.
https://shkspr.mobi/blog/2025/07/im-never-going-back-to-matrix/

I'm never going back to Matrix
I should love Matrix. It is a decentralised, privacy preserving, multi-platform chat tool. Goodbye Slack and your ridiculous free limits. Adiós Discord and your weird gamification. Suck it IRC with your obscure syntax and faint stench of BO. WhatsApp and Telegram can stick their heads in a bucket of lukewarm sick and sing sea shanties! Let's join the future! The problem is - Matrix is shit. Not …

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
Yidong Zhou, Su I Iao, Hans-Georg M\"uller
https://arxiv.org/abs/2509.23544 https://

End-to-End Deep Learning for Predicting Metric Space-Valued Outputs
Many modern applications involve predicting structured, non-Euclidean outputs such as probability distributions, networks, and symmetric positive-definite matrices. These outputs are naturally modeled as elements of general metric spaces, where classical regression techniques that rely on vector space structure no longer apply. We introduce E2M (End-to-End Metric regression), a deep learning framework for predicting metric space-valued outputs. E2M performs prediction via a weighted Fréchet me…

Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
Aleksandar Terzi\'c, Nicolas Menet, Michael Hersche, Thomas Hofmann, Abbas Rahimi
https://arxiv.org/abs/2509.22284

Structured Sparse Transition Matrices to Enable State Tracking in State-Space Models
Modern state-space models (SSMs) often utilize transition matrices which enable efficient computation but pose restrictions on the model's expressivity, as measured in terms of the ability to emulate finite-state automata (FSA). While unstructured transition matrices are optimal in terms of expressivity, they come at a prohibitively high compute and memory cost even for moderate state sizes. We propose a structured sparse parametrization of transition matrices in SSMs that enables FSA state tra…

On the non-existence of perfect codes in the sum-rank metric
Giuseppe Del Prete, Antonio Roccolano, Ferdinando Zullo
https://arxiv.org/abs/2508.20940 https://

On the non-existence of perfect codes in the sum-rank metric
We study perfect codes in the sum-rank metric, a generalization of both the Hamming and rank metrics relevant in multishot network coding and space-time coding. A perfect code attains equality in the sphere-packing bound, corresponding to a partition of the ambient space into disjoint metric balls. While perfect codes in the Hamming and rank metrics are completely classified, the existence of nontrivial perfect codes in the sum-rank metric remains largely open. In this paper, we investigate lin…

Interesting numbers about US top websites.
https://pressgazette.co.uk/media-audience-and-business-data/media_metrics/most-popular-websites-news-us-monthly-3/

Top 50 news websites in the US: AP shrugs off Trump row with huge traffic boost
Press Gazette lists the top 50 biggest websites for news in the US. Monthly updated top 50 listing based on data from Similarweb.

Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions
Luisa Geiger, Mareike Hartmann, Michael Sullivan, Alexander Koller
https://arxiv.org/abs/2509.24792

Evaluating Spatiotemporal Consistency in Automatically Generated Sewing Instructions
In this paper, we propose a novel, automatic tree-based evaluation metric for LLM-generated step-by-step assembly instructions, that more accurately reflects spatiotemporal aspects of construction than traditional metrics such as BLEU and BERT similarity scores. We apply our proposed metric to the domain of sewing instructions, and show that our metric better correlates with manually-annotated error counts as well as human quality ratings, demonstrating our metric's superiority for evaluating t…

Continuity Norm Framework for the Evolution of Nonsingular Matrices
L. Yildiz, D. Kayki, E. Gudekli
https://arxiv.org/abs/2507.20742 https://arxiv.org/pdf/…

Continuity Norm Framework for the Evolution of Nonsingular Matrices
Matrix theory, foundational in diverse fields such as mathematics, physics, and computational sciences, typically categorizes matrices based strictly on their invertibility-determined by a sharply defined singular or nonsingular classification. However, such binary classifications become inadequate in describing matrices whose elements vary continuously over time, thereby transitioning through intermediate states near singular configurations. To address this fundamental limitation, we develop a…

A near real-time #bolide detection software suite ingests data from the Geostationary Lightning Mapper (GLM) instrument onboard the Geostationary Operational Environmental Satellites (GOES) and applies anomaly detection algorithms to distinguish between bolide events and the many lightning detections GLM was originally designed to characterize: https://www.usu.edu/today/story/space-dynamics-lab-shares-open-source-software-to-detect-potentially-dangerous-meteors - the GLM sensor takes 500 images of Earth every second, and StarFall analyzes the meteors’ light curves, or changes in brightness over time, as they pass through the atmosphere.

Ukraine picks '2,000 Meters to Andriivka' as its 2026 Oscars contender: https://benborges.xyz/2025/08/28/ukraine-picks-meters-to-andriivka.html

Higher order linear differential equations for unitary matrix integrals: applications and generalisations
Peter J. Forrester, Fei Wei
https://arxiv.org/abs/2508.20797 https://…

Higher order linear differential equations for unitary matrix integrals: applications and generalisations
We consider characterisations of the class of unitary matrix integrals $ \langle (\det U)^q e^{s^{1/2} {\rm Tr}(U + U^\dagger)} \rangle_{U(l)}$ in terms of a first order matrix linear differential equation for a vector function of size $l+1$, and in terms of a scalar linear differential equation of degree $l+1$. It will be shown that the latter follows from the former. The matrix linear differential equation provides an efficient way to compute the power series expansion of the matrix integrals…