Unveiling the Competitive Dynamics: A Comparative Evaluation of American and Chinese LLMs

• URL: http://arxiv.org/abs/2405.06713v2
• Date: Tue, 21 May 2024 05:37:58 GMT
• Title: Unveiling the Competitive Dynamics: A Comparative Evaluation of American and Chinese LLMs
• Authors: Zhenhui Jiang, Jiaxin Li, Yang Liu,
• Abstract summary: This study provides a comparative evaluation of American and Chinese Large Language Models (LLMs) in both English and Chinese contexts. We proposed a comprehensive evaluation framework that encompasses natural language proficiency, disciplinary expertise, and safety and responsibility. Our key findings show that GPT 4-Turbo is at the forefront in English contexts, whereas Ernie-Bot 4 stands out in Chinese contexts.
• Score: 13.112787482203286
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: The strategic significance of Large Language Models (LLMs) in economic expansion, innovation, societal development, and national security has been increasingly recognized since the advent of ChatGPT. This study provides a comprehensive comparative evaluation of American and Chinese LLMs in both English and Chinese contexts. We proposed a comprehensive evaluation framework that encompasses natural language proficiency, disciplinary expertise, and safety and responsibility, and systematically assessed 16 prominent models from the US and China under various operational tasks and scenarios. Our key findings show that GPT 4-Turbo is at the forefront in English contexts, whereas Ernie-Bot 4 stands out in Chinese contexts. The study also highlights disparities in LLM performance across languages and tasks, stressing the necessity for linguistically and culturally nuanced model development. The complementary strengths of American and Chinese LLMs point to the value of Sino-US collaboration in advancing LLM technology. The research presents the current LLM competition landscape and offers valuable insights for policymakers and businesses regarding strategic LLM investments and development. Future work will expand on this framework to include emerging LLM multimodal capabilities and business application assessments.

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