Tootfinder

Nach Kritik: Larian verzichtet bei „Divinity“ auf Concept Art von KI
Für die Entwicklung von „Divinity“ wollte Larian ursprünglich KI einsetzen, um etwa Concept Art zu zeichnen. Nach Kritik haben sich die Pläne nun geändert.

FACE: Faithful Automatic Concept Extraction
Dipkamal Bhusal, Michael Clifford, Sara Rampazzi, Nidhi Rastogi
https://arxiv.org/abs/2510.11675 https://arxiv.…

FACE: Faithful Automatic Concept Extraction
Interpreting deep neural networks through concept-based explanations offers a bridge between low-level features and high-level human-understandable semantics. However, existing automatic concept discovery methods often fail to align these extracted concepts with the model's true decision-making process, thereby compromising explanation faithfulness. In this work, we propose FACE (Faithful Automatic Concept Extraction), a novel framework that augments Non-negative Matrix Factorization (NMF) with…

Madrid – Calle de Concepción Jerónima
#kamafotos

A Systematic Study on Generating Web Vulnerability Proof-of-Concepts Using Large Language Models
Mengyao Zhao, Kaixuan Li, Lyuye Zhang, Wenjing Dang, Chenggong Ding, Sen Chen, Zheli Liu
https://arxiv.org/abs/2510.10148

A Systematic Study on Generating Web Vulnerability Proof-of-Concepts Using Large Language Models
Recent advances in Large Language Models (LLMs) have brought remarkable progress in code understanding and reasoning, creating new opportunities and raising new concerns for software security. Among many downstream tasks, generating Proof-of-Concept (PoC) exploits plays a central role in vulnerability reproduction, comprehension, and mitigation. While previous research has focused primarily on zero-day exploitation, the growing availability of rich public information accompanying disclosed CVEs…

"Do your own research" is counter productive when you don't know how to research...
https://www.vice.com/en/article/scientists-explain-why-doing-your-own-research-leads-to-buying-conspiracies/

Scientists Explain Why ‘Doing Your Own Research’ Leads to Believing Conspiracies
Researchers found that people searching misinformation online risk falling into “data voids” that increase belief in conspiracies.

From points to complexes: a concept of unexpectedness for simplicial complexes
Thiago Holleben
https://arxiv.org/abs/2510.10884 https://arxiv.org/pdf/2510.…

From points to complexes: a concept of unexpectedness for simplicial complexes
In 2018, Cook, Harbourne, Migliore and Nagel introduced the concept of unexpected hypersurfaces, which connects the study of Lefschetz properties of artinian algebras defined by powers of linear forms, to a family of interpolation problems. In this paper, inspired by the theory of unexpected hypersurfaces, we introduce the concept of unexpected systems of parameters for squarefree monomial ideals. Similarly to the setting of points, we show that the existence of an unexpected system of paramete…

Does AI as a concept have an unsubscribe button

A US judge rules that Apple and OpenAI must answer to a lawsuit filed by X and xAI accusing them of conspiring to thwart competition in emerging markets in AI (Madlin Mekelburg/Bloomberg)
https://www.bloomberg.com/news/articles/20

Bifurcation Curves in Semipositone Problems with Geometrically Concave and Concave Nonlinearities
Shao-Yuan Huang
https://arxiv.org/abs/2510.10412 https://…

Bifurcation Curves in Semipositone Problems with Geometrically Concave and Concave Nonlinearities
In this paper, we study the exact multiplicity and bifurcation curves of positive solutions for the semipositone problem defined on the interval from minus one to one, with zero boundary conditions at both ends. The function f is twice continuously differentiable on the positive real line, and there exist two positive numbers such that f is positive between them and negative outside this range. We allow f at zero from the right to be negative infinity and provide many examples to illustrate the…

Online Allocation with Concave, Diminishing-Returns Objectives
Kalen Patton
https://arxiv.org/abs/2510.11266 https://arxiv.org/pdf/2510.11266

Online Allocation with Concave, Diminishing-Returns Objectives
Online resource allocation problems are central challenges in economics and computer science, modeling situations in which $n$ items arriving one at a time must each be immediately allocated among $m$ agents. In such problems, our objective is to maximize a monotone reward function $f(\mathbf{x})$ over the allocation vector $\mathbf{x} = (x_{ij})_{i, j}$, which describes the amount of each item given to each agent. In settings where $f$ is concave and has "diminishing returns" (monotone decreas…