Tootfinder

Sen. Dick Durbin reveals that AG Pam Bondi “pressured” roughly 1,000 FBI personnel to sift through tens of thousands of Epstein documents to flag all mentions of Donald Trump
https://dailycast.news/america-demands-answers/

America demands answers - Dailycast Newstalk Radio
Senator Dick Durbin drops a massive bombshell and reveals that Attorney General Pam Bondi “pressured” roughly 1,000 FBI personnel to sift through tens of thousands of Epstein documents to flag all mentions...

The amount of pointless, useless, overly-complex indirection I see in so many well-established, popular projects makes me very sad.
Except when I am trying to debug it; then it makes me very angry.
#PHP #Programming

Counting Answer Sets of Disjunctive Answer Set Programs
Mohimenul Kabir, Supratik Chakraborty, Kuldeep S Meel
https://arxiv.org/abs/2507.11655 https://

Counting Answer Sets of Disjunctive Answer Set Programs
Answer Set Programming (ASP) provides a powerful declarative paradigm for knowledge representation and reasoning. Recently, counting answer sets has emerged as an important computational problem with applications in probabilistic reasoning, network reliability analysis, and other domains. This has motivated significant research into designing efficient ASP counters. While substantial progress has been made for normal logic programs, the development of practical counters for disjunctive logic pr…

Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QA
Kaiwei Zhang, Qi Jia, Zijian Chen, Wei Sun, Xiangyang Zhu, Chunyi Li, Dandan Zhu, Guangtao Zhai
https://arxiv.org/abs/2508.13743

Sycophancy under Pressure: Evaluating and Mitigating Sycophantic Bias via Adversarial Dialogues in Scientific QA
Large language models (LLMs), while increasingly used in domains requiring factual rigor, often display a troubling behavior: sycophancy, the tendency to align with user beliefs regardless of correctness. This tendency is reinforced by preference-based alignment techniques that optimize for user satisfaction but can undermine truthfulness. While relatively benign in casual dialogue, sycophancy poses serious risks in high-stakes settings such as scientific question answering (QA), where model ou…

Risikomanagement und Resilienz in der IT-Sicherheit: IT-Sicherheitstag Dortmund
Das Programm zur eintägigen Konferenz an der FH Dortmund am 16.09. ist online. Die Vorträge aus Forschung und Wirtschaft reichen von Hacking bis LLM-Angriffen.

"In theory, AI model makers could eliminate hallucinations by using a dataset that contains no errors."
I think someone has fundamentally misunderstood the technology. Developing a model using a 100% correct training dataset does not mean that the resulting AI will be able to correctly answer questions that were not in the training data.
Over-fitting is a thing.

OpenAI says models are programmed to make stuff up instead of admitting ignorance
: Even a wrong answer is right some of the time

Free Software is inherently political. It always has been.
https://peakd.com/programming/@crell/free-software-is-political

Anthem 2.0: Automated Reasoning for Answer Set Programming
Jorge Fandinno, Christoph Glinzer, Zachary Hansen, Jan Heuer, Yuliya Lierler, Vladimir Lifschitz, Torsten Schaub, Tobias Stolzmann
https://arxiv.org/abs/2507.11704

Anthem 2.0: Automated Reasoning for Answer Set Programming
Anthem 2.0 is a tool to aid in the verification of logic programs written in an expressive fragment of Clingo's input language named mini-gringo, which includes arithmetic operations and simple choice rules but not aggregates. It can translate logic programs into formula representations in the logic of here-and-there, and analyze properties of logic programs such as tightness. Most importantly, Anthem 2.0 can support program verification by invoking first-order theorem provers to confirm that a…

A Multi-To-One Interview Paradigm for Efficient MLLM Evaluation
Ye Shen, Junying Wang, Farong Wen, Yijin Guo, Qi Jia, Zicheng Zhang, Guangtao Zhai
https://arxiv.org/abs/2509.14886

A Multi-To-One Interview Paradigm for Efficient MLLM Evaluation
The rapid progress of Multi-Modal Large Language Models (MLLMs) has spurred the creation of numerous benchmarks. However, conventional full-coverage Question-Answering evaluations suffer from high redundancy and low efficiency. Inspired by human interview processes, we propose a multi-to-one interview paradigm for efficient MLLM evaluation. Our framework consists of (i) a two-stage interview strategy with pre-interview and formal interview phases, (ii) dynamic adjustment of interviewer weights …