Japanese Text

Research on Japanese text focuses on improving natural language processing (NLP) capabilities for this morphologically rich and typologically distinct language. Current efforts concentrate on developing high-quality corpora and training large language models (LLMs) using various architectures, including transformer-based models and those incorporating techniques like SimCSE for sentence embedding. These advancements are crucial for bridging the language gap in applications like machine translation, question answering, and AI-assisted education, particularly given the limitations of existing multilingual models in handling the nuances of Japanese. Furthermore, research is actively addressing challenges specific to Japanese, such as word segmentation, honorifics, and the handling of different writing systems.