Awesome-Agent-Papers

Awesome Agent Papers

This repository is dedicated to providing an extensive collection of research papers related to Large Language Model (LLM) agents. It aims to keep track of the rapidly evolving landscape, organizing papers into key categories such as:

• Agent Construction: Methodologies and architectures for building LLM agents.
• Agent Collaboration: Frameworks for multi-agent interaction and cooperation.
• Agent Evolution: Self-improvement and learning capabilities of agents.
• Tools: Integration of external tools and APIs with LLM agents.
• Security: Security concerns and protections for LLM agent systems.
• Benchmarks: Evaluation frameworks and datasets for assessing agent capabilities.
• Applications: Real-world implementations and use cases.

The repository features a structured taxonomy that helps researchers and developers navigate the connections between various research threads concerning agent design principles and the emergent behaviors of LLMs.

Regular updates ensure that the collection remains current with the latest influential research publications, encouraging contributions from the community to enhance the available resources.