Tootfinder

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https://www.noz.de/lokales/osnabrueck/artikel/was-ist-das-fuer-eine-saeule-an-der-uhlhornstrasse-in-osnabrueck-48696820
Um Neunzehnhundert waren die Straßenvekehrsverhältnisse in

Great insights in this talk:
The Hidden Reason You Feel Empty & Lost — And How To Finally Find Meaning | Alain de Botton
https://www.youtube.com/watch?v=lKlKUylCDHs&ab_channel=DrRanganChatterjee

Bonjour,
Je viens de signer la pétition « Déchéance du Titre de Docteur décerné Š Mr Idriss ABERKANE par l'université de Paris-Saclay ». Cette cause me tient Š cœur et j’aimerais que le plus de monde possible soit au courant et signe cette pétition.
Voici le lien:

[Pétition] Déchéance du Titre de Docteur décerné à Mr Idriss ABERKANE par l'université de Paris-Saclay
TITLE : Withdrawal of the title of Doctor awarded to Mr Idriss ABERKANE by the University of Paris-SaclayTo: French minister of National Education, Higher Education and Research; President of Universi

Extendible cardinals, and Laver-generic large cardinal axioms for extendibility
Saka\'e Fuchino
#toXiv_bot_toot

Online Performance Assessment of Multi-Source-Localization for Autonomous Driving Systems Using Subjective Logic
Stefan Orf, Sven Ochs, Marc Ren\'e Zofka, J. Marius Z\"ollner
https://arxiv.org/abs/2506.02932

Online Performance Assessment of Multi-Source-Localization for Autonomous Driving Systems Using Subjective Logic
Autonomous driving (AD) relies heavily on high precision localization as a crucial part of all driving related software components. The precise positioning is necessary for the utilization of high-definition maps, prediction of other road participants and the controlling of the vehicle itself. Due to this reason, the localization is absolutely safety relevant. Typical errors of the localization systems, which are long term drifts, jumps and false localization, that must be detected to enhance s…

Improving LLM-Based Fault Localization with External Memory and Project Context
Inseok Yeo, Duksan Ryu, Jongmoon Baik
https://arxiv.org/abs/2506.03585 http…

Improving LLM-Based Fault Localization with External Memory and Project Context
Fault localization, the process of identifying the software components responsible for failures, is essential but often time-consuming. Recent advances in Large Language Models (LLMs) have enabled fault localization without extensive defect datasets or model fine-tuning. However, existing LLM-based methods rely only on general LLM capabilities and lack integration of project-specific knowledge, resulting in limited effectiveness, especially for complex software. We introduce MemFL, a novel ap…

Great possibility to renew my travel outfit. I wonder whether they sell to non-locals.

Localised and Delocalised Charge Distribution in a Diamine Cation and Rydberg Excited State: A Challenging Test for Density Functionals
Benedikt O. Birgisson, Marta Ga{\l}y\'nska, Hemanadhan Myneni, Elvar \"O. J\'onsson, Ragnar Bjornsson, Hannes J\'onsson
https://arxiv.org/abs/2506.05077

Localised and Delocalised Charge Distribution in a Diamine Cation and Rydberg Excited State: A Challenging Test for Density Functionals
The balance between localised and delocalised electron distribution in the N,N'-dimethylpiperazine (DMP) molecule in the 3s Rydberg excited state and in the fully ionised DMP$^+$ provides a valuable test of density functionals, in particular the weight of Fock exchange (FE) in hybrid functionals and the scaling of explicit orbital-based self-interaction correction (SIC) applied to less elaborate functionals. We present results of calculations using density functionals of all rungs of Jacob's la…

Benchmarking Time-localized Explanations for Audio Classification Models
Cecilia Bola\~nos, Leonardo Pepino, Martin Meza, Luciana Ferrer
https://arxiv.org/abs/2506.04391

Benchmarking Time-localized Explanations for Audio Classification Models
Most modern approaches for audio processing are opaque, in the sense that they do not provide an explanation for their decisions. For this reason, various methods have been proposed to explain the outputs generated by these models. Good explanations can result in interesting insights about the data or the model, as well as increase trust in the system. Unfortunately, evaluating the quality of explanations is far from trivial since, for most tasks, there is no clear ground truth explanation to u…

Fault Localisation and Repair for DL Systems: An Empirical Study with LLMs
Jinhan Kim, Nargiz Humbatova, Gunel Jahangirova, Shin Yoo, Paolo Tonella
https://arxiv.org/abs/2506.03396

Fault Localisation and Repair for DL Systems: An Empirical Study with LLMs
Numerous Fault Localisation (FL) and repair techniques have been proposed to address faults in Deep Learning (DL) models. However, their effectiveness in practical applications remains uncertain due to the reliance on pre-defined rules. This paper presents a comprehensive evaluation of state-of-the-art FL and repair techniques, examining their advantages and limitations. Moreover, we introduce a novel approach that harnesses the power of Large Language Models (LLMs) in localising and repairing …