Cognitive Kernel-Pro: A Framework for Deep Research Agents and Agent Foundation Models Training
Tianqing Fang, Zhisong Zhang, Xiaoyang Wang, Rui Wang, Can Qin, Yuxuan Wan, Jun-Yu Ma, Ce Zhang, Jiaqi Chen, Xiyun Li, Hongming Zhang, Haitao Mi, Dong Yu
2025-08-04
Summary
This paper talks about Cognitive Kernel-Pro, an open-source AI agent framework designed to help build smarter and more reliable AI systems that can perform complex research tasks, interact with the web, write code, and think deeply.
What's the problem?
The problem is that many current AI agent systems are either closed-source or rely heavily on expensive tools, making it hard for researchers to access, test, and improve them. This limits the development and sharing of advanced AI technologies.
What's the solution?
Cognitive Kernel-Pro solves this by providing a free, modular framework with multiple specialized sub-agents that handle tasks like web browsing, file processing, and reasoning. It uses high-quality training data and new testing methods like reflection and voting to make the agents more robust and effective, all while being open and accessible to everyone.
Why it matters?
This matters because it allows more people to develop and improve powerful AI agents, driving faster innovation and enabling AI to help solve complex problems more reliably and transparently.
Abstract
Cognitive Kernel-Pro is an open-source multi-module agent framework that enhances AI agent robustness and performance through data curation and novel test-time strategies, achieving state-of-the-art results.