Constructing Synthetic Instruction Datasets for Improving Reasoning in Domain-Specific LLMs: A Case Study in the Japanese Financial Domain

Researchers developed a method for creating synthetic instruction datasets to improve domain-specific LLMs, demonstrating with a 9.5 billion token Japanese financial dataset. The approach enhances both domain expertise and reasoning capabilities, with models and datasets being open-sourced for broader use.