Tootfinder

Metrizability, connectedness, completeness and boundedness of generalized $u$-topology and $m$-topology in $C(X)$
Soumajit Dey, Sudip Kumar Acharyya, Dhananjoy Mandal
https://arxiv.org/abs/2508.14651

Metrizability, connectedness, completeness and boundedness of generalized $u$-topology and $m$-topology in $C(X)$
If $I$ is an ideal in the ring $C(X)$ of all real valued continuous functions defined over a Tychonoff space $X$, then $X$ is called $I$-$pseudocompact$ if the set $X\setminus \bigcap Z[I]$ is a bounded subset of $X$. Corresponding to $I$, the $m^I$-topology and $u^I$-topology on $C(X)$, generalizing the well-known $m$-topology and $u$-topology in $C(X)$ respectively are already there in the literature. It is proved amongst others that the $m^I$-topology is first countable if and only if the $u…

From de Sitter to Anti-de Sitter singularity regularization: theory and phenomenology
Julio Arrechea, Stefano Liberati, Hooman Neshat, Vania Vellucci
https://arxiv.org/abs/2509.13421

From de Sitter to Anti-de Sitter singularity regularization: theory and phenomenology
Recent investigations of vacuum polarization in extremely compact stars suggest that, in such regimes, the effective matter content of spacetime may acquire a vacuum-energy equation of state with negative energy density, mimicking a negative cosmological constant. Motivated by this observation, we introduce a general algorithm to modify well-known spherically symmetric regular black hole metrics by replacing their usual de Sitter cores (dSC) with Anti-de Sitter cores (AdSC). Like their dSC coun…

DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
Daniel Pulido-Cort\'azar, Daniel Gibert, Felip Many\`a
https://arxiv.org/abs/2510.12310

DeepTrust: Multi-Step Classification through Dissimilar Adversarial Representations for Robust Android Malware Detection
Over the last decade, machine learning has been extensively applied to identify malicious Android applications. However, such approaches remain vulnerable against adversarial examples, i.e., examples that are subtly manipulated to fool a machine learning model into making incorrect predictions. This research presents DeepTrust, a novel metaheuristic that arranges flexible classifiers, like deep neural networks, into an ordered sequence where the final decision is made by a single internal model…

Vectorized 3D mesh refinement and implementation of primal hybrid FEM in MATLAB
Harish Nagula Mallesham, Sharat Gaddam, Jan Valdman, Sanjib Kumar Acharya
https://arxiv.org/abs/2509.11133

Vectorized 3D mesh refinement and implementation of primal hybrid FEM in MATLAB
In this article, we introduce a Face-to-Tetrahedron connectivity in MATLAB together with a vectorized 3D uniform mesh refinement technique. We introduce a MATLAB vectorized assembly of 3D lowest-order primal hybrid finite element matrices for a second-order elliptic problem. We introduce a parallel solver and a vectorized Schur complement solver to solve the associated linear problem. The numerical results illustrate the software's runtime performance.

LLM Robustness Leaderboard v1 --Technical report
Pierre Peign\'e - Lefebvre, Quentin Feuillade-Montixi, Tom David, Nicolas Miailhe
https://arxiv.org/abs/2508.06296 https://

LLM Robustness Leaderboard v1 --Technical report
This technical report accompanies the LLM robustness leaderboard published by PRISM Eval for the Paris AI Action Summit. We introduce PRISM Eval Behavior Elicitation Tool (BET), an AI system performing automated red-teaming through Dynamic Adversarial Optimization that achieves 100% Attack Success Rate (ASR) against 37 of 41 state-of-the-art LLMs. Beyond binary success metrics, we propose a fine-grained robustness metric estimating the average number of attempts required to elicit harmful behav…

Replaced article(s) found for cs.SC. https://arxiv.org/list/cs.SC/new
[1/1]:
- Exact Algorithms for Computing Generalized Eigenspaces of Matrices via Jordan-Krylov Basis
Shinichi Tajima, Katsuyoshi Ohara, Akira Terui

State Field Coverage: A Metric for Oracle Quality
Facundo Molina, Nazareno Aguirre, Alessandra Gorla
https://arxiv.org/abs/2510.03071 https://arxiv.org/pdf…

State Field Coverage: A Metric for Oracle Quality
The effectiveness of testing in uncovering software defects depends not only on the characteristics of the test inputs and how thoroughly they exercise the software, but also on the quality of the oracles used to determine whether the software behaves as expected. Therefore, assessing the quality of oracles is crucial to improve the overall effectiveness of the testing process. Existing metrics have been used for this purpose, but they either fail to provide a comprehensive basis for guiding or…

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Metric:
🎵 Sick Muse
#NowPlaying #Metric
https://stateazure.bandcamp.com/track/metric-sick-muse-state-azure-mix
https://open.spotify.com/track/2uxLjFYEoQ7xsqfMPuwTQ9

Efficiently Ranking Software Variants with Minimal Benchmarks
Th\'eo Matricon, Mathieu Acher, Helge Spieker, Arnaud Gotlieb
https://arxiv.org/abs/2509.06716 https://

Efficiently Ranking Software Variants with Minimal Benchmarks
Benchmarking is a common practice in software engineering to assess the qualities and performance of software variants, coming from multiple competing systems or from configurations of the same system. Benchmarks are used notably to compare and understand variant performance, fine-tune software, detect regressions, or design new software systems. The execution of benchmarks to get a complete picture of software variants is highly costly in terms of computational resources and time. In this pape…