This repository serves as a curated collection of essential academic papers on Large Language Model (LLM) Agents, targeting researchers and practitioners in the AI field. It aims to provide a comprehensive overview of the rapidly evolving landscape of LLM-powered agents, covering key areas like planning, memory, tool use, and multi-agent interactions, thereby accelerating research and development in autonomous AI systems.

How It Works

The project functions as a living bibliography, meticulously categorizing and listing influential research papers. It organizes papers by sub-topics such as Agent Personality, Memory, Planning, Tool Use, and Multi-Agent Communication, facilitating targeted exploration. Each entry typically includes a link to the paper's abstract or full text, enabling users to access the foundational research directly.

Quick Start & Requirements

This is a static resource; no installation or execution is required. Access is via web browser to the GitHub repository.

Highlighted Details

• Comprehensive categorization of papers across 10+ key LLM agent research areas.
• Includes links to abstracts and, where available, code repositories for many papers.
• Features a "News" section for recent publications and a "Contribution" section for community input.
• Lists popular frameworks and tools relevant to LLM agent development.

Maintenance & Community

The repository is actively maintained, with recent updates noted in March 2024. It encourages community contributions to expand and refine the paper list.

Licensing & Compatibility

The repository content is typically governed by the GitHub repository's license, which is often permissive (e.g., MIT), allowing for broad use and distribution of the curated list. Specific paper licenses vary.

Limitations & Caveats

This is a curated list of papers and does not provide any executable code or models. The rapid pace of LLM agent research means the list may not be exhaustive or immediately up-to-date with the very latest publications.