3 papers
cs.CL2025
AnswerCarefully: A Dataset for Improving the Safety of Japanese LLM Output
Hisami Suzuki, Satoru Katsumata, Takashi Kodama +3
In this paper we present AnswerCarefully, a dataset for promoting the safety and appropriateness of Japanese LLM outputs. The dataset consists of 1,800 pairs of questions and refer…
cs.CL2024
LLM-jp: A Cross-organizational Project for the Research and Development of Fully Open Japanese LLMs
LLM-jp, :, Akiko Aizawa +80
This paper introduces LLM-jp, a cross-organizational project for the research and development of Japanese large language models (LLMs). LLM-jp aims to develop open-source and stron…
cs.CL2024
JAPAGEN: Efficient Few/Zero-shot Learning via Japanese Training Dataset Generation with LLM
Takuro Fujii, Satoru Katsumata
Recently some studies have highlighted the potential of Large Language Models (LLMs) as effective generators of supervised training data, offering advantages such as enhanced infer…