A comprehensive collection of research papers on Large Language Model (LLM) agents, covering core areas including agent construction, collaboration mechanisms, evolution, tools, security, benchmarks, and applications.
One-Minute Overview#
This is a carefully curated collection of research papers on Large Language Model (LLM) agents, designed to provide researchers and developers with structured literature resources. The repository not only collects the latest research findings but also offers a classification framework to help understand this rapidly evolving field.
Core Value: Systematically organizes fragmented LLM agent research to help researchers quickly grasp the full scope of the field and identify research directions.
Quick Start#
Installation Difficulty: Low - This is a pure Markdown document repository that requires no installation - content can be accessed directly
# Clone the repository locally
git clone https://github.com/luo-junyu/Awesome-Agent-Papers.git
Is this suitable for my scenario?
- ✅ Researchers: Academics who need a systematic understanding of the LLM agent research landscape
- ✅ Developers: Application developers looking to understand the latest technical implementations of LLM agents
- ✅ Students: Scholars seeking entry points and in-depth resources on LLM agents
- ❌ Non-AI professionals: Those without basic knowledge of NLP or AI may find some content difficult to understand
Core Capabilities (Optional)#
1. Systematic Literature Classification - Solving Research Fragmentation#
- Papers are systematically classified into 8 core areas including agent construction, collaboration, evolution, tools, and security Actual Value: Helps researchers quickly locate areas of interest and avoid getting lost in the vast literature
2. Research Trend Tracking - Understanding Field Development Dynamics#
- Collects the rapidly growing body of research papers since 2023 Actual Value: Understands the latest research hotspots and development trends in the LLM agent field
3. Cross-Domain Connection Display - Discovering Research Relationships#
- Shows connections between different research directions and potential collaboration opportunities Actual Value: Inspires cross-domain research ideas and identifies new research directions
4. Authoritative Literature Curation - Ensuring Content Quality#
- Curates high-quality, influential research papers and surveys Actual Value: Saves screening time by directly connecting with the most important research findings in the field
Technology Stack & Integration (Optional)#
Development Language: Markdown Data Format: Plain text with structured organization Access Method: GitHub repository, supports web browsing and local cloning
Maintenance Status (Optional)#
- Development Activity: Actively maintained - Recent continuous updates show regular addition of new research papers
- Recent Updates: Recently active - Content expansion continues, reflecting the rapid development of the field
- Community Response: Good - Open contribution mechanism encourages researchers to submit new papers
Documentation & Learning Resources (Optional)#
- Documentation Quality: Comprehensive - As an academic resource repository, it provides systematic literature classification and detailed descriptions
- Official Documentation: https://github.com/luo-junyu/Awesome-Agent-Papers
- Sample Code: Not applicable - This is a literature repository, not a code project