Korean Data

Research on Korean data focuses on developing and applying machine learning models to diverse Korean datasets, addressing the scarcity of resources in this language. Current efforts involve training large language models (LLMs) on Korean text and multimodal data, including historical maps, using architectures like transformers and employing techniques such as masked language modeling and encoder-decoder models for tasks ranging from music restoration to legal document analysis and precipitation forecasting. This work is significant because it expands the capabilities of LLMs to a less-represented language, improving the accuracy and cultural sensitivity of AI applications while also providing valuable benchmark datasets for future research.