Methodology of Adapting Large English Language Models for Specific Cultural Contexts

• URL: http://arxiv.org/abs/2406.18192v2
• Date: Thu, 27 Jun 2024 02:17:19 GMT
• Title: Methodology of Adapting Large English Language Models for Specific Cultural Contexts
• Authors: Wenjing Zhang, Siqi Xiao, Xuejiao Lei, Ning Wang, Huazheng Zhang, Meijuan An, Bikun Yang, Zhaoxiang Liu, Kai Wang, Shiguo Lian,
• Abstract summary: We propose a rapid adaptation method for large models in specific cultural contexts. The adapted LLM significantly enhances its capabilities in domain-specific knowledge and adaptability to safety values.
• Score: 10.151487049108626
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The rapid growth of large language models(LLMs) has emerged as a prominent trend in the field of artificial intelligence. However, current state-of-the-art LLMs are predominantly based on English. They encounter limitations when directly applied to tasks in specific cultural domains, due to deficiencies in domain-specific knowledge and misunderstandings caused by differences in cultural values. To address this challenge, our paper proposes a rapid adaptation method for large models in specific cultural contexts, which leverages instruction-tuning based on specific cultural knowledge and safety values data. Taking Chinese as the specific cultural context and utilizing the LLaMA3-8B as the experimental English LLM, the evaluation results demonstrate that the adapted LLM significantly enhances its capabilities in domain-specific knowledge and adaptability to safety values, while maintaining its original expertise advantages.

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