Enhancing Japanese Large Language Models with Reasoning Vectors

Carolina Minami Oguchi; Leo Wei; Koyo Kobayashi; Hsin-Tai Wu; Dipak Ghosal

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arXiv · 2508.02913

Enhancing Japanese Large Language Models with Reasoning Vectors

Carolina Minami Oguchi·Leo Wei·Koyo Kobayashi·Hsin-Tai Wu·Dipak Ghosal

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Abstract

Post-training methods have improved the performance and enhanced the reasoning capability for mainstream large language models (LLMs), but the same is challenging for Japanese LLMs to achieve due to the amount of resources required. Inspired by task vectors that extract the change of weights before and after training, specifically for a certain task, we obtain reasoning vectors from reasoning LLMs and apply them to Japanese LLMs to boost their performance. While the resources available present a challenge to improve Japanese LLMs, we present a simple and effective way to obtain high improvement and hope to inspire for other languages.

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Carolina Minami Oguchi, Leo Wei, Koyo Kobayashi, Hsin-Tai Wu, Dipak Ghosal. 2025-08-04. Enhancing Japanese Large Language Models with Reasoning Vectors. https://arxiv.org/abs/2508.02913

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