Summary of Methodology Of Adapting Large English Language Models For Specific Cultural Contexts, by Wenjing Zhang and Siqi Xiao and Xuejiao Lei and Ning Wang and Huazheng Zhang and Meijuan An and Bikun Yang and Zhaoxiang Liu and Kai Wang and Shiguo Lian
Methodology of Adapting Large English Language Models for Specific Cultural Contexts
by Wenjing Zhang, Siqi Xiao, Xuejiao Lei, Ning Wang, Huazheng Zhang, Meijuan An, Bikun Yang, Zhaoxiang Liu, Kai Wang, Shiguo Lian
First submitted to arxiv on: 26 Jun 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed rapid adaptation method for large language models (LLMs) in specific cultural contexts leverages instruction-tuning based on specific cultural knowledge and safety values data. The method aims to address the limitations of current state-of-the-art LLMs, which are predominantly English-based and encounter difficulties when directly applied to tasks in specific cultural domains. 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. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary Large language models are getting smarter, but they’re mostly trained on English data. This can cause problems when they try to understand tasks or cultures from specific countries or regions. To fix this, researchers developed a new way to teach large models about specific cultural contexts, like Chinese. They used a big model called LLaMA3-8B as the starting point and added special instructions based on Chinese language and cultural values. The results show that this adapted model is much better at understanding Chinese culture and values than the original model. |
Keywords
* Artificial intelligence * Instruction tuning
