How Do Large Language Models Capture the Ever-changing World Knowledge? A Review of Recent Advances
Zihan Zhang, Meng Fang, Ling Chen, Mohammad‐Reza Namazi‐Rad, Jun Wang · 2023
Although large language models (LLMs) are impressive in solving various tasks, they can quickly be outdated after deployment.Maintaining their up-to-date status is a pressing concern in the current era.This paper provides a comprehensive review of recent advances in aligning LLMs with the ever-changing world knowledge without re-training from scratch.We categorize research works systemically and provide in-depth comparisons and discussion.We also discuss existing challenges and highlight future directions to facilitate research in this field 1 .