5 papers · 1 filter
EmplifAI: a Fine-grained Dataset for Japanese Empathetic Medical Dialogues in 28 Emotion Labels
Wan Jou She, Lis Kanashiro Pereira, Fei Cheng +3
This paper introduces EmplifAI, a Japanese empathetic dialogue dataset designed to support patients coping with chronic medical conditions. They often experience a wide range of po…
Causal Tree Extraction from Medical Case Reports: A Novel Task for Experts-like Text Comprehension
Sakiko Yahata, Zhen Wan, Fei Cheng +3
Extracting causal relationships from a medical case report is essential for comprehending the case, particularly its diagnostic process. Since the diagnostic process is regarded as…
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…
MELD-ST: An Emotion-aware Speech Translation Dataset
Sirou Chen, Sakiko Yahata, Shuichiro Shimizu +4
Emotion plays a crucial role in human conversation. This paper underscores the significance of considering emotion in speech translation. We present the MELD-ST dataset for the emo…
Rapidly Developing High-quality Instruction Data and Evaluation Benchmark for Large Language Models with Minimal Human Effort: A Case Study on Japanese
Yikun Sun, Zhen Wan, Nobuhiro Ueda +4
The creation of instruction data and evaluation benchmarks for serving Large language models often involves enormous human annotation. This issue becomes particularly pronounced wh…