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## 🎉 News ## 🎉 News
**•May 26, 2025: 🎉 We propose a novel puppeteer-style paradigm for multi-agent collaboration among large language model based agents. By leveraging a learnable central orchestrator optimized with reinforcement learning, our method dynamically activates and sequences agents to construct efficient, context-aware reasoning paths. This approach not only improves reasoning quality but also reduces computational costs, enabling scalable and adaptable multi-agent cooperation in complex tasks.** •**Sep 24, 2025: 🎉 Our paper [Multi-Agent Collaboration via Evolving Orchestration](https://arxiv.org/abs/2505.19591) has been accepted to NeurIPS 2025**. The implementation is available in the `puppeteer` branch of this repository.
**See our paper in [Multi-Agent Collaboration via Evolving Orchestration](https://arxiv.org/abs/2505.19591)**.
•May 26, 2025: 🎉 We propose a novel puppeteer-style paradigm for multi-agent collaboration among large language model based agents. By leveraging a learnable central orchestrator optimized with reinforcement learning, our method dynamically activates and sequences agents to construct efficient, context-aware reasoning paths. This approach not only improves reasoning quality but also reduces computational costs, enabling scalable and adaptable multi-agent cooperation in complex tasks.
See our paper in [Multi-Agent Collaboration via Evolving Orchestration](https://arxiv.org/abs/2505.19591).
<p align="center"> <p align="center">
<img src='./misc/puppeteer.png' width=800> <img src='./misc/puppeteer.png' width=800>
</p> </p>