by js-lee-AI · Agent Tool · ★ 61
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🤖 Awesome LLM Agent Papers 200+ must-read papers, continuously growing: the annotated reading list for building LLM agents that plan, remember, use tools, and cooperate. Companion to the survey “LLM Agents: A Survey.” -- <img src="https://img.shields.io/github/stars/js-lee-AI/awesome-llm-agent-papers?style=flat-square&labelColor=2b2b2b&color=8B2635" alt="GitHub
| Stars | 61 |
| Forks | 15 |
| Language | Python |
| Category | Agent Tool |
| License | MIT |
| Quality Score | 57.1198901604346/100 |
| Last Updated | 2026-08-08 |
| Created | 2026-07-08 |
| Platforms | python |
| Est. Tokens | ~25k |
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awesome-llm-agent-papers is A curated, continuously updated reading list of 200+ papers on LLM agents: planning, memory, tool use, multi-agent, evaluation & safety. Companion to the survey 'LLM Agents: A Survey'.. It is categorized as a Agent Tool with 61 GitHub stars.
awesome-llm-agent-papers is primarily written in Python. It covers topics such as agent-benchmark, agent-survey, agents.
You can find installation instructions and usage details in the awesome-llm-agent-papers GitHub repository at github.com/js-lee-AI/awesome-llm-agent-papers. The project has 61 stars and 15 forks, indicating an active community.
awesome-llm-agent-papers is released under the MIT license, making it free to use and modify according to the license terms.
The top alternatives to awesome-llm-agent-papers on Agent Skills Hub include agentic-ai, Awesome-AI-For-Security, LiteMultiAgent. Each offers a different approach to the same problem space — compare them side-by-side by stars, quality score, and community activity.