Tootfinder

A US judge sentences Terraform Labs co-founder Do Kwon to 15 years in prison; Kwon pleaded guilty to conspiracy and wire fraud charges in August (Cheyenne Ligon/CoinDesk)
https://www.coindesk.com/policy/2025/12/10/terraform-s-do-kwon-s…

Terra Creator Do Kwon Sentenced to 15 Years in Prison
The Terraform Labs co-founder pleaded guilty to conspiracy and wire fraud in August.

"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.

CDE: Concept-Driven Exploration for Reinforcement Learning
Le Mao, Andrew H. Liu, Renos Zabounidis, Zachary Kingston, Joseph Campbell
https://arxiv.org/abs/2510.08851 https://…

CDE: Concept-Driven Exploration for Reinforcement Learning
Intelligent exploration remains a critical challenge in reinforcement learning (RL), especially in visual control tasks. Unlike low-dimensional state-based RL, visual RL must extract task-relevant structure from raw pixels, making exploration inefficient. We propose Concept-Driven Exploration (CDE), which leverages a pre-trained vision-language model (VLM) to generate object-centric visual concepts from textual task descriptions as weak, potentially noisy supervisory signals. Rather than direct…

Everybody Hates Candace (Will Sommer/The Bulwark)
https://www.thebulwark.com/p/candace-owens-conspiracy-theories-charlie-kirk-right-wing-media
http://www.memeorandum.com/251211/p70#a251211p70

Concept-Based Generic Programming in C
Bjarne Stroustrup
https://arxiv.org/abs/2510.08969 https://arxiv.org/pdf/2510.08969…

Concept-Based Generic Programming in C++
We present programming techniques to illustrate the facilities and principles of C++ generic programming using concepts. Concepts are C++'s way to express constraints on generic code. As an initial example, we provide a simple type system that eliminates narrowing conversions and provides range checking without unnecessary notational or run-time overheads. Concepts are used throughout to provide user-defined extensions to the type system. The aim is to show their utility and the fundamental ide…

A thread dumping some (non-obvious?) notes about #firewalld - I think I've got it doing what I want, but it's been a bit of a fight, and I made a bunch of wrong turns.
It's a layer on top of nftables or iptables; is XML based but you can just drive it from a command line tool firewall-cmd and avoid the XML.
It's main idea is a graph of 'zones' where a 'zo…

Does AI as a concept have an unsubscribe button

Enhancing Concept Localization in CLIP-based Concept Bottleneck Models
R\'emi Kazmierczak, Steve Azzolin, Elo\"ise Berthier, Goran Frehse, Gianni Franchi
https://arxiv.org/abs/2510.07115

Enhancing Concept Localization in CLIP-based Concept Bottleneck Models
This paper addresses explainable AI (XAI) through the lens of Concept Bottleneck Models (CBMs) that do not require explicit concept annotations, relying instead on concepts extracted using CLIP in a zero-shot manner. We show that CLIP, which is central in these techniques, is prone to concept hallucination, incorrectly predicting the presence or absence of concepts within an image in scenarios used in numerous CBMs, hence undermining the faithfulness of explanations. To mitigate this issue, we …

A reverse entropy power inequality for i.i.d. log-concave random variables
Zhen Fu, Jiange Li
https://arxiv.org/abs/2510.09206 https://arxiv.org/pdf/2510.0…

A reverse entropy power inequality for i.i.d. log-concave random variables
Let $X$ and $Y$ be independent identically distributed log-concave random variables. We show that $h_\infty(X+Y)-h_\infty(X)$ is maximized when $X$ and $Y$ have exponential distributions. Here, $h_\infty(\cdot)$ is the Rényi entropy of order $\infty$. Analogs for integer-valued log-concave random variables are also obtained.

Post-hoc Stochastic Concept Bottleneck Models
Wiktor Jan Hoffmann, Sonia Laguna, Moritz Vandenhirtz, Emanuele Palumbo, Julia E. Vogt
https://arxiv.org/abs/2510.08219 https://

Post-hoc Stochastic Concept Bottleneck Models
Concept Bottleneck Models (CBMs) are interpretable models that predict the target variable through high-level human-understandable concepts, allowing users to intervene on mispredicted concepts to adjust the final output. While recent work has shown that modeling dependencies between concepts can improve CBM performance, especially under interventions, such approaches typically require retraining the entire model, which may be infeasible when access to the original data or compute is limited. I…