The Rise and Potential of Large Language Model Based Agents: A Survey
VerifiedSurvey and curated paper list on LLM-based AI agents.
What is The Rise and Potential of Large Language Model Based Agents: A Survey?
The project centers on a comprehensive survey paper that examines how LLMs can serve as the foundation for autonomous agents. It organizes existing research around a general architecture and extends the discussion to real-world uses and societal implications.
Readers follow the progression from basic agent construction through domain-specific deployments and finally to collective behaviors that arise when multiple agents interact. Regular updates add new papers and related tools as the field evolves.
The resource is intended for researchers and developers who need a structured entry point into LLM agent literature and want to stay current with key publications and open questions.
What you can build with The Rise and Potential of Large Language Model Based Agents: A Survey
Single-agent applications
Explore how individual LLM agents handle tasks in isolated environments using the surveyed brain-perception-action structure.
Multi-agent scenarios
Review research on coordinated groups of agents that collaborate or compete within shared settings.
Human-agent cooperation
Study designs where humans and LLM agents work together, drawing from the documented cooperation examples.
Install The Rise and Potential of Large Language Model Based Agents: A Survey
- 1Visit the GitHub repository linked in the project page.
- 2Read the main survey paper hosted on arXiv.
- 3Browse the categorized paper list for relevant sections.
- 4Check the news section for recent additions and related frameworks.
- 5Submit contributions via pull requests or issues to expand coverage.
The Rise and Potential of Large Language Model Based Agents: A Survey: pros & cons
Pros
- +Centralized collection of must-read papers on LLM agents
- +Clear high-level framework that organizes diverse research
- +Active maintenance with frequent paper and tool updates
- +Open invitation for community contributions
Cons
- –Many paper summaries remain placeholders
- –Primarily a literature resource rather than runnable code
- –Scope limited to published work at the time of each update
Frequently asked questions
It provides a survey and ongoing list of papers on agents powered by large language models.
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