让研究者用更少精力把理论假说变成可投稿的论文初稿。
pAI/MSc: ML Theory Research with Humans on the Loop
- 多智能体系统辅助科研，聚焦机器学习理论与量化领域。
- 将假说转化为文献支持、数学证明、实验验证的初稿，大幅减少人工操作。
- 开源可定制，适合想高效推进理论研究的研究者使用。
我们提出pAI/MSc，一个开源、可定制、模块化的多智能体系统，用于学术研究工作流。目标并非实现自主科学构想或完全自动化研究，而是更聚焦且实用：将指定的科学假说转化为基于文献、数学严谨、实验支持、可投稿的论文初稿，所需的人工引导减少数个数量级。pAI/MSc当前重点服务于机器学习理论及相邻定量领域。
原文摘要 · Abstract (English)
We present pAI/MSc, an open-source, customizable, modular multi-agent system for academic research workflows. Our goal is not autonomous scientific ideation, nor fully automated research. It is narrower and more practical: to reduce by orders of magnitude the human steering required to turn a specified hypothesis into a literature-grounded, mathematically established, experimentally supported, submission-oriented manuscript draft. pAI/MSc is built with a current emphasis on machine learning theory and adjacent quantitative fields.
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