# A Survey on LLM-Based Agentic Workflows and LLM-Profiled Components

**Authors:** Xinzhe Li  
**arXiv:** [2406.05804](https://arxiv.org/abs/2406.05804)  
**Date:** 2024-06-09  
**Summary page:** https://www.summarizepaper.com/fr/paper/2406.05804v1/

## Abstract

Recent advancements in Large Language Models (LLMs) have catalyzed the development of sophisticated agentic workflows, offering improvements over traditional single-path, Chain-of-Thought (CoT) prompting techniques. This survey summarize the common workflows, with the particular focus on LLM-Profiled Components (LMPCs) and ignorance of non-LLM components. The reason behind such exploration is to facilitate a clearer understanding of LLM roles and see how reusabile of the LMPCs.