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

2024-05-09 · Zhenhui Jiang, Jiaxin Li, Yang Liu

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.

📄 PDF Abstract BibTeX arXiv:2405.06713

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Linear Layer A Linear Layer is a projection $\mathbf{XW + b}$.
Discriminative Fine-Tuning Discriminative Fine-Tuning is a fine-tuning strategy that is used for ULMFiT type models. Instead of using the same learning rate…
Multi-Head Attention 설명 없음
Layer Normalization Unlike batch normalization, Layer Normalization directly estimates the normalization statistics from the summed inputs…
Dense Connections Dense Connections, or Fully Connected Connections, are a type of layer in a deep neural network that use a linear operation where every input is connected to every output…

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