Large Language Model Agent: A Survey on Methodology, Applications and Challenges

This application showcases papers from our comprehensive survey on Large Language Model (LLM) agents. We organize papers across key categories including agent construction, collaboration mechanisms, evolution, tools, security, benchmarks, and applications.

About the Survey

The era of intelligent agents is upon us, driven by revolutionary advancements in large language models. Large Language Model (LLM) agents, with goal-driven behaviors and dynamic adaptation capabilities, potentially represent a critical pathway toward artificial general intelligence.

This survey systematically deconstructs LLM agent systems through a methodology-centered taxonomy, linking architectural foundations, collaboration mechanisms, and evolutionary pathways. We unify fragmented research threads by revealing fundamental connections between agent design principles and their emergent behaviors in complex environments.

View the full paper on arXiv
Explore our GitHub repository

Submit Your Paper

We welcome contributions to expand our collection. To submit your paper:

• Email us at luo.junyu@outlook.com with your paper details
• Create a pull request on our GitHub repository

Collection Overview

• Total Papers: 270
• Categories: 10
• Year Range: 2019 - 2025