4 papers
Can Large Language Models Imitate Human Speech for Clinical Assessment? LLM-Driven Data Augmentation for Cognitive Score Prediction
Si-Belkacem Yamine Ketir, Lenard Paulo Tamayo, Shohei Hisada +3
Accurate assessment of cognitive decline from spontaneous speech remains challenging due to limited dataset size and class imbalance. In this work, we propose a large language mode…
Filling in the Clinical Gaps in Benchmark: Case for HealthBench for the Japanese medical system
Shohei Hisada, Endo Sunao, Himi Yamato +2
This study investigates the applicability of HealthBench, a large-scale, rubric-based medical benchmark, to the Japanese context. Although robust evaluation frameworks are essentia…
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…
Annotation-Scheme Reconstruction for "Fake News" and Japanese Fake News Dataset
Taichi Murayama, Shohei Hisada, Makoto Uehara +2
Fake news provokes many societal problems; therefore, there has been extensive research on fake news detection tasks to counter it. Many fake news datasets were constructed as reso…