Tootfinder

AgriEval: A Comprehensive Chinese Agricultural Benchmark for Large Language Models
Lian Yan, Haotian Wang, Chen Tang, Haifeng Liu, Tianyang Sun, Liangliang Liu, Yi Guan, Jingchi Jiang
https://arxiv.org/abs/2507.21773

AgriEval: A Comprehensive Chinese Agricultural Benchmark for Large Language Models
In the agricultural domain, the deployment of large language models (LLMs) is hindered by the lack of training data and evaluation benchmarks. To mitigate this issue, we propose AgriEval, the first comprehensive Chinese agricultural benchmark with three main characteristics: (1) Comprehensive Capability Evaluation. AgriEval covers six major agriculture categories and 29 subcategories within agriculture, addressing four core cognitive scenarios: memorization, understanding, inference, and genera…

"Airdrops would usually be ordered as a last resort to feed people in emergency situations where hostile armed forces or geography make road deliveries impossible. In Gaza the only obstacles to driving aid across the border are restrictions imposed by Israel, an ally of many western nations including Britain, and armed with British and US weapons"
#GazaGenocide

#caturday

One of my many simultaneous ongoing #HamRadio projects are a set of bandpass filters. I forgot until now that my uSimmics work with various filters counts as @…

Warner Bros. Motion Picture Group is undergoing 10% cuts across multiple divisions to transition "toward a fully global structure" (Pamela McClintock/The Hollywood Reporter)
https://www.hollywoodreporter.com/movies/movie-new…

Layoffs Strike Warner Bros. Motion Picture Group
Studio heads Michael De Luca and Pamela Abdy announced the shift in direction in a memo to staff.

Going to be playing with two former Temptations on 16 August, so I'm doing a little bit of background prep and I came across this video. So many bands just become part of the firmament, but we are not familiar with them at their visceral best. This is/was epic!
#music #SoulMusic

A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks
Zhuocheng Liu, Zhishu Shen, Qiushi Zheng, Tiehua Zhang, Zheng Lei, Jiong Jin
https://arxiv.org/abs/2507.22339

A Semi-Supervised Federated Learning Framework with Hierarchical Clustering Aggregation for Heterogeneous Satellite Networks
Low Earth Orbit (LEO) satellites are emerging as key components of 6G networks, with many already deployed to support large-scale Earth observation and sensing related tasks. Federated Learning (FL) presents a promising paradigm for enabling distributed intelligence in these resource-constrained and dynamic environments. However, achieving reliable convergence, while minimizing both processing time and energy consumption, remains a substantial challenge, particularly in heterogeneous and partia…

DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Hossein Mirzaei, Zeinab Taghavi, Sepehr Rezaee, Masoud Hadi, Moein Madadi, Mackenzie W. Mathis
https://arxiv.org/abs/2507.22813

DISTIL: Data-Free Inversion of Suspicious Trojan Inputs via Latent Diffusion
Deep neural networks have demonstrated remarkable success across numerous tasks, yet they remain vulnerable to Trojan (backdoor) attacks, raising serious concerns about their safety in real-world mission-critical applications. A common countermeasure is trigger inversion -- reconstructing malicious "shortcut" patterns (triggers) inserted by an adversary during training. Current trigger-inversion methods typically search the full pixel space under specific assumptions but offer no assurances tha…

AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini
Jill Walker Rettberg, Hermann Wigers
https://arxiv.org/abs/2507.22445

AI-generated stories favour stability over change: homogeneity and cultural stereotyping in narratives generated by gpt-4o-mini
Can a language model trained largely on Anglo-American texts generate stories that are culturally relevant to other nationalities? To find out, we generated 11,800 stories - 50 for each of 236 countries - by sending the prompt "Write a 1500 word potential {demonym} story" to OpenAI's model gpt-4o-mini. Although the stories do include surface-level national symbols and themes, they overwhelmingly conform to a single narrative plot structure across countries: a protagonist lives in or returns hom…