This repository organizes research by thematic areas that integrate reasoning with action, including planning, tool use, search, self-evolution through memory and feedback, multi-agent systems, and real-world applications and benchmarks.
📄 Based on the survey: Agentic Reasoning for Large Language Models: A Survey
[01/21/26] 🚀 We have released a comprehensive survey on Agentic Reasoning for Large Language Models! The paper is now available on arxiv and HuggingFace. We welcome contributions from the community to help expand and improve our survey 🤗!
- 🔔 News
- 📋 Table of Contents
- 🌟 Introduction
- 🤝 Contributing
- 📝 Citation
- 🏗️ Foundational Agentic Reasoning
- 🧬 Self-evolving Agentic Reasoning
- 👥 Collective Multi-agent Reasoning
- 🎨 Applications
- 📊 Benchmarks
Bridging thought and action through autonomous agents that reason, act, and learn via continual interaction with their environments. The goal is to enhance agent capabilities by grounding reasoning in action.
We organize agentic reasoning into three layers, each corresponding to a distinct reasoning paradigm under different environmental dynamics:
🔹 Foundational Reasoning. Core single-agent abilities (planning, tool-use, search) in environments
🔹 Self-Evolving Reasoning. Adaptation through feedback, memory, and learning in dynamic settings
🔹 Collective Reasoning. Multi-agent coordination, role specialization, and collaborative intelligence
Across these layers, we further identify complementary reasoning paradigms defined by their optimization settings.
🔸 In-Context Reasoning. Test-time scaling through structured orchestration and adaptive workflows
🔸 Post-Training Reasoning. Behavior optimization via RL and supervised fine-tuning
This collection is an ongoing effort. We are actively expanding and refining its coverage, and welcome contributions from the community. You can:
- Submit a pull request to add papers or resources
- Open an issue to suggest additional papers or resources
- Email us at twei10@illinois.edu, twli@illinois.edu, liu326@illinois.edu
We regularly update the repository to include new research.
If you find this repository or paper useful, please consider citing the survey paper:
@article{wei2026agentic,
title={Agentic Reasoning for Large Language Models},
author={Wei, Tianxin and Li, Ting-Wei and Liu, Zhining and Ning, Xuying and Yang, Ze and Zou, Jiaru and Zeng, Zhichen and Qiu, Ruizhong and Lin, Xiao and Fu, Dongqi and others},
journal={arXiv preprint arXiv:2601.12538},
year={2026}
}
Here are the extracted citation tables grouped by their respective sections.
This repository is licensed under the MIT License.