Intelligence shouldn’t be limited to a specific domain or task, but rather encompass a broad range
of cognitive skills and abilities [31]. The remarkable nature of the human brain is largely attributed
to its high degree of plasticity and adaptability. It can continuously adjust its structure and function
in response to external stimuli and internal needs, thereby adapting to different environments and
tasks. These years, plenty of research indicates that pre-trained models on large-scale corpora can
learn universal language representations [36; 261; 262]. Leveraging the power of pre-trained models,
with only a small amount of data for fine-tuning, LLMs can demonstrate excellent performance in
downstream tasks [263]. There is no need to train new models from scratch, which saves a lot of
computation resources. However, through this task-specific fine-tuning, the models lack versatility
and struggle to be generalized to other tasks. Instead of merely functioning as a static knowledge
TheRiseandPotentialofLargeLanguageModel BasedAgents