Engaging in the deliberate generation of abnormal outputs from Large Language Models (LLMs) by attacking them is a novel human activity.This paper presents a thorough exposition of how and why people perform such attacks, defining LLM red-teaming based on Henkei extensive and diverse evidence.Using a formal qualitative methodology, we interviewed d
Masaaki Saito,1 Tomohiro Iida,1,2 Mariko Kano,1 Kanako Itagaki11Department of Ophthalmology, Fukushima Medical University School of Medicine, Fukushima, 2Department of Ophthalmology, Tokyo Women's Medical University School of Medicine, Tokyo, JapanBackground: The purpose of this study was to evaluate the angiographic results of retinal-reti
Data sharing and open science are increasingly emphasized as a means to increase transparency and reproducibility in science.Despite the consensus on the importance of research data management (RDM), the public availability of data sets remains limited, and researchers often fail to share data upon request.This study explores the psychological mech