Tootfinder

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En zie daar het grote verschil dat Nieuwsuur maakt vandaag. Daar een lang item over een Israëlische vrouw em een Palestijnse man die Eem paar km uit elkaar wonen..
Achteraan ook bovenstaand stukje.
De bijeenkomst werd gehouden door de Israëlische ambassade en CJO.
Zeker zolang Israel genocide pleegt is het onbestaanbaar dat Schoof zich daar vertoont.
#RodeLijn #NLpol #Gaza

from my link log —
Nullable vs nullable in C#.
https://einarwh.no/blog/2025/08/25/nullable-vs-nullable/
saved 2025-08-25

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/7]:
- NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions
Elliot Gestrin, Marco Kuhlmann, Jendrik Seipp

LLM-Based Repair of Static Nullability Errors
Nima Karimipour, Michael Pradel, Martin Kellogg, Manu Sridharan
https://arxiv.org/abs/2507.20674 https://arxi…

LLM-Based Repair of Static Nullability Errors
Modern Java projects increasingly adopt static analysis tools that prevent null-pointer exceptions by treating nullness as a type property. However, integrating such tools into large, existing codebases remains a significant challenge. While annotation inference can eliminate many errors automatically, a subset of residual errors -- typically a mix of real bugs and false positives -- often persist and can only be resolved via code changes. Manually addressing these errors is tedious and error-p…

NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting
Kuangshi Ai, Kaiyuan Tang, Chaoli Wang
https://arxiv.org/abs/2507.12621

NLI4VolVis: Natural Language Interaction for Volume Visualization via LLM Multi-Agents and Editable 3D Gaussian Splatting
Traditional volume visualization (VolVis) methods, like direct volume rendering, suffer from rigid transfer function designs and high computational costs. Although novel view synthesis approaches enhance rendering efficiency, they require additional learning effort for non-experts and lack support for semantic-level interaction. To bridge this gap, we propose NLI4VolVis, an interactive system that enables users to explore, query, and edit volumetric scenes using natural language. NLI4VolVis int…

Replaced article(s) found for cs.AI. https://arxiv.org/list/cs.AI/new
[1/7]:
- NL2Plan: Robust LLM-Driven Planning from Minimal Text Descriptions
Elliot Gestrin, Marco Kuhlmann, Jendrik Seipp

Uiteraard valt t kwartje niet in Israel.
(Maar we gaan eerst maar zien wat er aan daadwerkelijke maatregelen genomen worden.)
Gejat bij de buren (bs, ‪@drjohamsterdam.bsky.social)
@nlpol
#RedLine #RodeLijn

Heisenberg Translation Flows
Francisco Arana-Herrera, Jayadev Athreya, Giovanni Forni
https://arxiv.org/abs/2509.21803 https://arxiv.org/pdf/2509.21803

Heisenberg Translation Flows
We study ergodic theoretical properties of flows on circle bundles over translation surfaces that arise via prequantization, generalizing the theory of Heisenberg nilflows to base surfaces more general than tori; these flows are among the most fundamental examples of parabolic dynamical systems with non-trivial central directions. In particular, we show that such flows are relatively mixing, i.e., they exhibit decay of correlations in the orthogonal complement of functions constant along fibers…

🇺🇦 #NowPlaying on KEXP's #VarietyMix
Quadeca:
🎵 GODSTAINED
#Quadeca
https://quadecax8.bandcamp.com/track/godstained
https://open.spotify.com/track/2IbtNIdNlVelpPNaRYEZdJ

A Comparative Analysis of Robust and Reliable Designs Using the Compromised Design Support Problem: A Case Study in Hot Rod Rolling Processes
Maryam Ghasemzadeh, H M Dilshad Alam Digonta, Anand Balu Nellippallil, Anton van Beek
https://arxiv.org/abs/2509.09422

A Comparative Analysis of Robust and Reliable Designs Using the Compromised Design Support Problem: A Case Study in Hot Rod Rolling Processes
Design under uncertainty is a challenging problem, as a systems performance can be highly sensitive to variations in input parameters and model uncertainty. A conventional approach to addressing such problems is robust optimization, which seeks to enhance design performance by reducing sensitivity to uncertainty. Alternatively, reliability-based design focuses on optimizing performance while ensuring that failure constraints are satisfied with a specified probability. While both methods are wel…