Tootfinder

Formalising Software Requirements using Large Language Models
Arshad Beg, Diarmuid O'Donoghue, Rosemary Monahan
https://arxiv.org/abs/2506.10704 https:…

Formalising Software Requirements using Large Language Models
This paper is a brief introduction to our recently initiated project named VERIFAI: Traceability and verification of natural language requirements. The project addresses the challenges in the traceability and verification of formal specifications through providing support for the automatic generation of the formal specifications and the traceability of the requirements from the initial software design stage through the systems implementation and verification. Approaches explored in this project…

Articles like this remind me that #ferrari is a long way away from winning a championship. It's all about the BS around the #F1, not F1 racing itself.

‘I’m from the land of slow food and fast cars’ – Chef Massimo Bottura on taking over Ferrari’s famous Ristorante Cavallino | Formula 1®
“In my veins there’s balsamic vinegar, my muscles are parmigiano-reggiano, but in my DNA there’s a 12 cylinder engine,” he says.

Formel-1-Pilot gesteht - Wechsel zu Red Bull? „Fühle mich nicht bereit!“ #News #Nachrichten

Formalizing Neuromorphic Control Systems: A General Proposal and A Rhythmic Case Study
Taisia Medvedeva, Alessio Franci, Fernando Casta\~nos
https://arxiv.org/abs/2506.10203

Formalizing Neuromorphic Control Systems: A General Proposal and A Rhythmic Case Study
Neuromorphic control is receiving growing attention due to the multifaceted advantages it brings over more classical control approaches, including: sparse and on-demand sensing, information transmission, and actuation; energy-efficient designs and realizations in neuromorphic hardware; event-based signal processing and control signal computation. However, a general control-theoretical formalization of what "neuromorphic control systems" are and how we can rigorously analyze, design, and control…

Corrections to Friis noise factor formulas for cascade networks
Ankitha E Bangera
https://arxiv.org/abs/2506.09900 https://arxiv.org/…

Corrections to Friis noise factor formulas for cascade networks
The signal-to-noise ratio of a multistage cascade network is often estimated using the well-known Friis' formulas for noise factors (or the noise figures in decibels). However, this article addresses the major errors in Friis' noise factor formulas for higher stages. Additionally, we re-derive the correct formulas to calculate the stage-wise noise factors for cascade networks from the basic definition of noise factors. We then present a comparison of our derived formulas with Friis' noise facto…

StepProof: Step-by-step verification of natural language mathematical proofs
Xiaolin Hu, Qinghua Zhou, Bogdan Grechuk, Ivan Y. Tyukin
https://arxiv.org/abs/2506.10558

StepProof: Step-by-step verification of natural language mathematical proofs
Interactive theorem provers (ITPs) are powerful tools for the formal verification of mathematical proofs down to the axiom level. However, their lack of a natural language interface remains a significant limitation. Recent advancements in large language models (LLMs) have enhanced the understanding of natural language inputs, paving the way for autoformalization - the process of translating natural language proofs into formal proofs that can be verified. Despite these advancements, existing aut…

Jedes Schild äh jede Formular-Checkbox hat ihre Geschichte…

A multi-scale loss formulation for learning a probabilistic model with proper score optimisation
Simon Lang, Martin Leutbecher, Pedro Maciel
https://arxiv.org/abs/2506.10868

A multi-scale loss formulation for learning a probabilistic model with proper score optimisation
We assess the impact of a multi-scale loss formulation for training probabilistic machine-learned weather forecasting models. The multi-scale loss is tested in AIFS-CRPS, a machine-learned weather forecasting model developed at the European Centre for Medium-Range Weather Forecasts (ECMWF). AIFS-CRPS is trained by directly optimising the almost fair continuous ranked probability score (afCRPS). The multi-scale loss better constrains small scale variability without negatively impacting forecast …

An $O(n$)-Algorithm for the Higher-Order Kinematics and Inverse Dynamics of Serial Manipulators using Spatial Representation of Twists
Andreas Mueller
https://arxiv.org/abs/2506.10686

An $O(n$)-Algorithm for the Higher-Order Kinematics and Inverse Dynamics of Serial Manipulators using Spatial Representation of Twists
Optimal control in general, and flatness-based control in particular, of robotic arms necessitate to compute the first and second time derivatives of the joint torques/forces required to achieve a desired motion. In view of the required computational efficiency, recursive $O(n)$-algorithms were proposed to this end. Aiming at compact yet efficient formulations, a Lie group formulation was recently proposed, making use of body-fixed and hybrid representation of twists and wrenches. In this paper…

Cotangent Bundles as Coadjoint Orbits and Asymptotic Character Formulas
Michael Gjertsen, Alexander Schmeding
https://arxiv.org/abs/2506.10519 https://

Cotangent Bundles as Coadjoint Orbits and Asymptotic Character Formulas
The present article presents geometric quantization on cotangent bundles as a special instance of Kirillov's orbit method. To this end, the cotangent bundle is realized as a coadjoint orbit of an infinite-dimensional Lie group constructed from the diffeomorphism group. We also develop two asymptotic character formulas by employing the tangent groupoid.