Tootfinder

I think this is a really good post on the cost of AI from my friend.
I'm anti-AI but I do think I need to better understand how it works and how others use it or I can't really contribute to the conversation.
AI might be able to make you more "efficient" but if you don't care about the content you make no one else will either.

Looks like someone cut a Yugo in half.
Yugos were basically Fiats that Fiat no longer wanted to make. https://mstdn.social/@bweller/114770694902314410

Evaluation of gamma-ray response of the AstroPix4 HV-CMOS active pixel sensor
Yusuke Suda, Regina Caputo, Daniel Violette, Grant Sommer, Nicolas Striebig, Manoj Jadhav, Yasushi Fukazawa, Carolyn Kierans, Richard Leys, Jessica Metcalfe, Norito Nakano, Ivan Peri\'c, Jeremy S. Perkins, Hiroyasu Tajima
https://arxiv.org/abs/2507.21618

Evaluation of gamma-ray response of the AstroPix4 HV-CMOS active pixel sensor
AstroPix is a novel high-voltage CMOS active pixel sensor being developed for a next generation gamma-ray space telescope, AMEGO-X. To meet AMEGO-X instrument requirements, AstroPix must achieve full depletion of its $500~\rm{μm}$ thick, $500~\rm{μm}$-pitch pixels. It must be sensitive to gamma rays in the range of $25-700$ keV, with the energy resolution at 122 keV of $<10$%. Furthermore, given the space-based nature of AMEGO-X, the power consumption of AstroPix needs to be lower than $1.5~\…

Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark
Chihiro Taguchi, Seng Mai, Keita Kurabe, Yusuke Sakai, Georgina Agyei, Soudabeh Eslami, David Chiang
https://arxiv.org/abs/2508.20511

Languages Still Left Behind: Toward a Better Multilingual Machine Translation Benchmark
Multilingual machine translation (MT) benchmarks play a central role in evaluating the capabilities of modern MT systems. Among them, the FLORES+ benchmark is widely used, offering English-to-many translation data for over 200 languages, curated with strict quality control protocols. However, we study data in four languages (Asante Twi, Japanese, Jinghpaw, and South Azerbaijani) and uncover critical shortcomings in the benchmark's suitability for truly multilingual evaluation. Human assessments…

Yikes, 2nd dump of breached Tea data reported by @….
A few useful thoughts that crossed my TL re the first breach:
- Many posts blame “vibe coding,” but unclear gen AI is to blame here?? At least some of the app/data appears to predate. We need the firsthand inside scoop on dev process.
- Firebase’s security model is a booby trap (still, alas)
1/2
https://www.404media.co/a-second-tea-breach-reveals-users-dms-about-abortions-and-cheating/

LLMs-guided adaptive compensator: Bringing Adaptivity to Automatic Control Systems with Large Language Models
Zhongchao Zhou, Yuxi Lu, Yaonan Zhu, Yifan Zhao, Bin He, Liang He, Wenwen Yu, Yusuke Iwasawa
https://arxiv.org/abs/2507.20509

LLMs-guided adaptive compensator: Bringing Adaptivity to Automatic Control Systems with Large Language Models
With rapid advances in code generation, reasoning, and problem-solving, Large Language Models (LLMs) are increasingly applied in robotics. Most existing work focuses on high-level tasks such as task decomposition. A few studies have explored the use of LLMs in feedback controller design; however, these efforts are restricted to overly simplified systems, fixed-structure gain tuning, and lack real-world validation. To further investigate LLMs in automatic control, this work targets a key subfiel…

Schema-Guided Response Generation using Multi-Frame Dialogue State for Motivational Interviewing Systems
Jie Zeng, Yukiko I. Nakano
https://arxiv.org/abs/2508.20635 https://

Schema-Guided Response Generation using Multi-Frame Dialogue State for Motivational Interviewing Systems
The primary goal of Motivational Interviewing (MI) is to help clients build their own motivation for behavioral change. To support this in dialogue systems, it is essential to guide large language models (LLMs) to generate counselor responses aligned with MI principles. By employing a schema-guided approach, this study proposes a method for updating multi-frame dialogue states and a strategy decision mechanism that dynamically determines the response focus in a manner grounded in MI principles.…

Simultaneously Fair Allocation of Indivisible Items Across Multiple Dimensions
Yasushi Kawase, Bodhayan Roy, Mohammad Azharuddin Sanpui
https://arxiv.org/abs/2506.21727

Simultaneously Fair Allocation of Indivisible Items Across Multiple Dimensions
This paper explores the fair allocation of indivisible items in a multidimensional setting, motivated by the need to address fairness in complex environments where agents assess bundles according to multiple criteria. Such multidimensional settings are not merely of theoretical interest but are central to many real-world applications. For example, cloud computing resources are evaluated based on multiple criteria such as CPU cores, memory, and network bandwidth. In such cases, traditional one d…

Why Are Parsing Actions for Understanding Message Hierarchies Not Random?
Daichi Kato, Ryo Ueda, Yusuke Miyao
https://arxiv.org/abs/2506.22366 https://

Why Are Parsing Actions for Understanding Message Hierarchies Not Random?
If humans understood language by randomly selecting parsing actions, it might have been necessary to construct a robust symbolic system capable of being interpreted under any hierarchical structure. However, human parsing strategies do not seem to follow such a random pattern. Why is that the case? In fact, a previous study on emergent communication using models with hierarchical biases have reported that agents adopting random parsing strategies$\unicode{x2013}$ones that deviate significantly …

Metaverse Support Groups for LGBTQ Youth: An Observational Study on Safety, Self-Expression, and Early Intervention
Joe Hasei, Yosuke Matsumoto, Hiroki Kawai, Yuko Okahisa, Manabu Takaki, Toshifumi Ozaki
https://arxiv.org/abs/2507.21079

Metaverse Support Groups for LGBTQ+ Youth: An Observational Study on Safety, Self-Expression, and Early Intervention
This study assessed metaverse-based support groups designed to reduce social isolation and suicide risk among LGBTQ+ youths. Using the Cluster platform, enhanced anonymity, avatar-based self-expression, and accessibility were provided. Key findings showed that 79.2% chose avatars matching their gender identity, reporting high satisfaction (mean: 4.10/5) and low discomfort (mean: 1.79/5). Social confidence significantly improved in virtual spaces compared to real-world interactions (p<0.001), pa…