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• A general method for constructing high-quality synthetic instruction data for any domain is proposed, starting from domain-specific vocabulary.method 95%
• The proposed method was applied to the Japanese financial domain to construct a large-scale instruction dataset.method 95%
• The constructed financial instruction dataset contains approximately 9.5 billion tokens.technical 95%
• The constructed dataset includes Chain-of-Thought reasoning traces.technical 95%
• Evaluation results confirmed performance improvements over baseline models on financial benchmarks.result 95%
• The study reports findings on the impact of reasoning trace length on performance.result 90%
• The study identifies limitations related to the impact of reasoning trace length on performance.limitation 90%
• The models and datasets are open-sourced on Hugging Face.technical 95%

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