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Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
Top AI Repos tracks AI repositories on GitHub and answers two different questions about each one: is it moving right now, and would you bet a product on it.
A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents.
| Date | Stars |
|---|---|
| 2026-07-31 | 363 |
| 2026-08-06 | 363 |
Today
— stars today
This week
— stars this week
This month
— stars this month
Momentum
0.0
growth rate 0.00%/day
# Awesome-Self-Evolving-Agents
<div align="center">
<a href="https://awesome.re"><img src="https://awesome.re/badge.svg"/></a>
<a href="http://makeapullrequest.com"><img src="https://img.shields.io/badge/PRs-welcome-green.svg"/></a>
<a href="https://doi.org/10.36227/techrxiv.177203250.05832634/v2" target="_blank"><img src="https://img.shields.io/badge/Paper-Arxiv-red?logo=arxiv&style=flat-square" alt="arXiv:2602.05665"></a>
<a href="http://makeapullrequest.com"><img src="https://img.shields.io/github/stars/XMUDeepLIT/Awesome-Self-Evolving-Agents"/></a>
</div>
This repository provides a comprehensive collection of research papers, benchmarks, and open-source projects on **Self-Evolving Agents**. It includes contents from our survey paper 📖<em>"[**A Systematic Survey of Self-Evolving Agents: From Model-Centric to Environment-Driven Co-Evolution**](https://doi.org/10.36227/techrxiv.177203250.05832634/v2)"</em> and will be continuously updated.
🤗 **You're very welcome to contribute to this repository**. If you find any missing resources or come across interesting new research works, please don’t hesitate to launch an issue or submit a pull request!
📫 **Contact us via emails:** `{xiangzhishang,yangchengyi}@stu.xmu.edu.cn`, `[email protected]`
**📃 Please [cite our paper](#-citation)** if you find our survey or repository helpful!
```
@article{xiang2026systematic,
title={A Systematic Survey of Self-Evolving Agents: From Model-Centric to Environment-Driven Co-Evolution},
author={Xiang, Zhishang and Yang, Chengyi and Chen, Zerui and Wei, Zhimin and Tang, Yunbo and Teng, Zongpei and Peng, Zexi and Li, Zongxia and Huang, Chengsong and He, Yicheng and others},
journal={Available at SSRN 6626878},
year={2026}
}
```
---
# 🎉 News
- **[2026-03]** We release the [TTCS](https://arxiv.org/abs/2601.22628) and accepted by [ICLR 2026 Lifelong Agent(LLA)](https://iclr.cc/virtual/2026/workshop/10000805) workshop!
- **[2026-02]** We release the survey of [Self-Evolving Agents](https://github.com/XMUDeepLIT/Awesome-Agentic-Self-Evolution).
---
<div>
<h3 align="center">
<p align="center"><img width="100%" src="figs/intro.png" /></p>
<p align="center"><em>A Comprehensive Taxonomy of Self-Evolving Agents.</em></p>
</div>
Agentic Self-Evolving represents a paradigm shift in AI development, enabling systems to autonomously improve through three key dimensions:
- **Model-Centric Self-Evolution**: Focuses on improving the model itself through inference-based evolution (parallel sampling, sequential self-correction, structured reasoning) and training-based evolution (synthesis-driven offline and exploration-driven online self-evolving).
- **Environment-Centric Self-Evolution**: Enhances the agent's interaction with external knowledge and experience through static knowledge evolution, dynamic experience evolution, modular architecture evolution, and agentic topology evolution.
- **Model-Environment Co-Evolution**: Enables simultaneous evolution of both the model and its environment through environment training and multi-agent policy co-evolution.
## 📈 Trends
<div>
<h3 align="center">
<p align="center"><img width="100%" src="figs/trend.png" /></p>
<p align="center"><em>The Development Trends of Self-Evolving Agents with Representative Works.</em></p>
</div>
---
## Table of Content
- [🔥 News](#-news)
- [📚 Related Survey Papers](#-related-survey-papers)
- [📜 Research Papers](#-research-papers)
- [Model-Centric Self-Evolution](#model-centric-self-evolving)
- [Inference-Based Evolution](#inference-based-evolution)
- [Parallel Sampling](#parallel-sampling)
- [Sequential Self-Correction](#sequential-self-correction)
- [Structured Reasoning](#structured-reasoning)
- [Training-Based Evolution 🔥](#training-based-evolution)
- [Synthesis-Driven Offline Self-Evolving](#synthesis-driven-offline-self-evolving)
- [ExploratExcerpt of 55,970 characters
Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:64424206d381e049, llm:Repository description and topics: 'A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents.' Topics include agent, agent-skills, agent-survey, self-evolving-agents, self-evolution.
matched fp:64424206d381e049, llm:Repository description and topics: 'A Survey of Self-Evolving Agents | A curated list of resources (surveys, papers, benchmarks, and opensource projects) on Self-Evolving Agents.' Topics include agent, agent-skills, agent-survey, self-evolving-agents, self-evolution.