Tootfinder

Erkenntnis: auf #willhaben bringt es nix, einen sehr günstigen Fixpreis einzustellen. Die Leute wollen immer(!) verhandeln.
Ergo stelle ich ab sofort immer teurer rein und schreibe #Verhandlungsbasis dazu. 🙄
Also gleich mal ein Angebot von 30 auf 50€ raufsetzen...

»Syncthing‑Fork unter fremder Kontrolle? Community schluckt das nicht:
Das Repository des beliebten Syncthing-Forks für Android verschwand von GitHub und taucht unter zwielichten Umständen wieder auf – ist das ein Open-Source-Hack?«
Mist, nun muss ich gucken ob die @… Variante vom @…

Syncthing‑Fork unter fremder Kontrolle? Community schluckt das nicht
Das Repository des beliebten Syncthing-Forks für Android verschwand von GitHub und taucht unter zwielichten Umständen wieder auf – ist das ein Open-Source-Hack?

Revisiting Query Variants: The Advantage of Retrieval Over Generation of Query Variants for Effective QPP
Fangzheng Tian, Debasis Ganguly, Craig Macdonald
https://arxiv.org/abs/2510.02512

Revisiting Query Variants: The Advantage of Retrieval Over Generation of Query Variants for Effective QPP
Leveraging query variants (QVs), i.e., queries with potentially similar information needs to the target query, has been shown to improve the effectiveness of query performance prediction (QPP) approaches. Existing QV-based QPP methods generate QVs facilitated by either query expansion or non-contextual embeddings, which may introduce topical drifts and hallucinations. In this paper, we propose a method that retrieves QVs from a training set (e.g., MS MARCO) for a given target query of QPP. To a…

Deutsche Polizeibehörden wollen unbedingt ein Produkt einer Firma verwenden, deren Chef Kriegsverbrechen legalisieren will.
https://futurism.com/future-society/palantir-ceo-war-crimes

Palantir CEO Says Legalizing War Crimes Would Be Good for Business
Palantir CEO Alex Karp recently rhapsodized that US air strikes on Venezuelan civilians would be good for business, if only it were legal.

Sparse Representations Improve Adversarial Robustness of Neural Network Classifiers
Killian Steunou, Sigurd Saue, Th\'eo Druilhe
https://arxiv.org/abs/2509.21130 https://

Sparse Representations Improve Adversarial Robustness of Neural Network Classifiers
Deep neural networks perform remarkably well on image classification tasks but remain vulnerable to carefully crafted adversarial perturbations. This work revisits linear dimensionality reduction as a simple, data-adapted defense. We empirically compare standard Principal Component Analysis (PCA) with its sparse variant (SPCA) as front-end feature extractors for downstream classifiers, and we complement these experiments with a theoretical analysis. On the theory side, we derive exact robustnes…

Anti-Jamming Modulation for OFDM Systems under Jamming Attacks
Jaewon Yun, Joohyuk Park, Yo-Seb Jeon
https://arxiv.org/abs/2510.02640 https://arxiv.org/pdf…

Anti-Jamming Modulation for OFDM Systems under Jamming Attacks
In this paper, we propose an anti-jamming communication framework for orthogonal frequency-division multiplexing (OFDM) systems under jamming attacks. To this end, we first develop an anti-jamming modulation scheme that uses a spreading matrix to distribute each symbol across multiple subcarriers, enhancing robustness against jamming. For optimal demodulation at a receiver, we devise a maximum likelihood detection (MLD) method and its low-complexity variant tailored to our anti-jamming modulati…

Partial Bloch--Kato Selmer groups of $B$-pairs as delta functors
Rustam Steingart
https://arxiv.org/abs/2510.00775 https://arxiv.org/pdf/2510.00775

Partial Bloch--Kato Selmer groups of $B$-pairs as delta functors
In this article we revisit the partial Selmer groups introduced by Ding in cohomological degree one. On the subcategory of partially de Rham positive $B$-pairs we extend them to higher cohomological degree and show that the resulting groups form a cohomological delta functor satisfying a variant of the Euler--Poincaré characteristic formula and Tate duality.

TubeDAgger: Reducing the Number of Expert Interventions with Stochastic Reach-Tubes
Julian Lemmel, Manuel Kranzl, Adam Lamine, Philipp Neubauer, Radu Grosu, Sophie A. Neubauer
https://arxiv.org/abs/2510.00906

TubeDAgger: Reducing the Number of Expert Interventions with Stochastic Reach-Tubes
Interactive Imitation Learning deals with training a novice policy from expert demonstrations in an online fashion. The established DAgger algorithm trains a robust novice policy by alternating between interacting with the environment and retraining of the network. Many variants thereof exist, that differ in the method of discerning whether to allow the novice to act or return control to the expert. We propose the use of stochastic reachtubes - common in verification of dynamical systems - as a…

The Power Contamination Problem on Grids Revisited: Optimality, Combinatorics, and Links to Integer Sequences
El-Mehdi Mehiri, Mohammed L. Nadji
https://arxiv.org/abs/2509.12756

The Power Contamination Problem on Grids Revisited: Optimality, Combinatorics, and Links to Integer Sequences
This paper presents a combinatorial study of the power contamination problem, a dynamic variant of power domination modeled on grid graphs. We resolve a conjecture posed by Ainouche and Bouroubi (2021) by proving it is false and instead establish the exact value of the power contamination number on grid graphs. Furthermore, we derive recurrence relations for this number and initiate the enumeration of optimal contamination sets. We prove that the number of optimal solutions for specific grid fa…

Wie bereitet man sich optimal auf #Radtouren und #Wanderungen vor?
Ein gut ausgestattetes Erste-Hilfe-Set ist unerlässlich. Dabei ist es sinnvoll, separate Sets für #Fahrrad und