Tootfinder

This is part of the overall assault on knowledge that the administration is undertaking.
Everything that has made this nation a shining beacon in any way whatsoever is being dismantled
-- with the worst aspects of American history being held up as aspirational.
Please call Congress if you are able.
🛰️🧪

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Humza Ashraf, Syed Muhammad Danish, Aris Leivadeas, Yazan Otoum, Zeeshan Sattar
https://arxiv.org/abs/2508.08332

Energy-Aware Code Generation with LLMs: Benchmarking Small vs. Large Language Models for Sustainable AI Programming
Large Language Models (LLMs) are widely used for code generation. However, commercial models like ChatGPT require significant computing power, which leads to high energy use and carbon emissions. This has raised concerns about their environmental impact. In this study, we evaluate open-source Small Language Models (SLMs) trained explicitly for code generation and compare their performance and energy efficiency against large LLMs and efficient human-written Python code. The goal is to investigat…

A Classification-Driven Likelihood Ratio Method for Familial DNA Testing
Akaraphon Jantaraphum, Chanagarn Laoiam, Budsaba Rerkamnuaychoke, Jittima Shotivaranon, Monchai Kooakachai
https://arxiv.org/abs/2508.15579

A Classification-Driven Likelihood Ratio Method for Familial DNA Testing
Background: Familial DNA search relies on statistical methods to infer genetic relationships, often using the likelihood ratio (LR) as the test statistic. This approach involves calculating the probability of observed DNA profiles under various scenarios, traditionally assuming a uniform genetic background for all individuals. However, this assumption is unrealistic in practice due to population substructure, where allele frequencies differ among subpopulations. To address this, modified LR-bas…