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MiroFlow: Towards High-Performance and Robust Open-Source Agent Framework for General Deep Research Tasks
arXiv – CS AI|Shiqian Su, Sen Xing, Xuan Dong, Muyan Zhong, Bin Wang, Xizhou Zhu, Yuntao Chen, Wenhai Wang, Yue Deng, Pengxiang Zhu, Ziyuan Liu, Tiantong Li, Jiaheng Yu, Zhe Chen, Lidong Bing, Jifeng Dai||4 views
🤖AI Summary
Researchers have released MiroFlow, an open-source AI agent framework designed to overcome limitations of current LLM-based systems in complex real-world tasks. The framework features agent graph orchestration, deep reasoning capabilities, and robust workflow execution, achieving state-of-the-art performance across multiple benchmarks including GAIA and FutureX.
Key Takeaways
- →MiroFlow addresses key limitations of existing agent frameworks including naive workflows and unstable performance.
- →The framework incorporates agent graph orchestration and optional deep reasoning mode for enhanced capabilities.
- →MiroFlow achieved state-of-the-art results across multiple agent benchmarks including GAIA, BrowseComp, and FutureX.
- →The open-source nature reduces dependency on expensive commercial APIs that plague current solutions.
- →The framework aims to provide an accessible baseline for deep research community development.
Read Original →via arXiv – CS AI
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