Reproduce “History, Development, and Principles of Large Language Models-An Introductory Survey” on OpenResearch

About this paper

Zichong Wang, Zhibo Chu, Thang Viet Doan, Shiwen Ni, Min Yang, Wenbin Zhang

This survey paper from Florida International University and Shenzhen Institutes of Advanced Technology offers an accessible overview of Large Language Models, detailing their historical progression, foundational principles, and diverse applications. It critically examines the factors driving their rapid development and addresses inherent drawbacks such as privacy, fairness, and safety, aiming to equip a broad audience with fundamental knowledge.

Key insights

• The rapid advancement of LLMs is largely attributable to the confluence of vast data diversity, exponential computational growth, and algorithmic innovations like the Transformer architecture.
• LLMs exhibit emergent abilities and adaptability, often achieved through alignment with human values rather than extensive domain-specific fine-tuning.
• Despite their broad capabilities, LLMs face substantial challenges related to privacy risks, fairness issues stemming from inherited biases, safety concerns like 'hallucination,' and complex intellectual property considerations.

Summary by alphaXiv.