Japanese Dataset

Research on Japanese datasets focuses on developing and improving large language models (LLMs) for various domains, including biomedical applications, finance, and general-purpose tasks. Current efforts center on creating high-quality, domain-specific datasets to train and evaluate these models, often employing techniques like continual pre-training and instruction tuning to enhance performance. These advancements are crucial for improving the accuracy and efficiency of natural language processing (NLP) in Japanese, with implications for applications ranging from financial analysis to healthcare and information extraction.