English

Build Your Personalized Research Group: A Multiagent Framework for Continual and Interactive Science Automation

Artificial Intelligence 2025-10-20 v1 Computation and Language Machine Learning Multiagent Systems

Abstract

The automation of scientific discovery represents a critical milestone in Artificial Intelligence (AI) research. However, existing agentic systems for science suffer from two fundamental limitations: rigid, pre-programmed workflows that cannot adapt to intermediate findings, and inadequate context management that hinders long-horizon research. We present \texttt{freephdlabor}, an open-source multiagent framework featuring \textit{fully dynamic workflows} determined by real-time agent reasoning and a \coloremph{\textit{modular architecture}} enabling seamless customization -- users can modify, add, or remove agents to address domain-specific requirements. The framework provides comprehensive infrastructure including \textit{automatic context compaction}, \textit{workspace-based communication} to prevent information degradation, \textit{memory persistence} across sessions, and \textit{non-blocking human intervention} mechanisms. These features collectively transform automated research from isolated, single-run attempts into \textit{continual research programs} that build systematically on prior explorations and incorporate human feedback. By providing both the architectural principles and practical implementation for building customizable co-scientist systems, this work aims to facilitate broader adoption of automated research across scientific domains, enabling practitioners to deploy interactive multiagent systems that autonomously conduct end-to-end research -- from ideation through experimentation to publication-ready manuscripts.

Keywords

Cite

@article{arxiv.2510.15624,
  title  = {Build Your Personalized Research Group: A Multiagent Framework for Continual and Interactive Science Automation},
  author = {Ed Li and Junyu Ren and Xintian Pan and Cat Yan and Chuanhao Li and Dirk Bergemann and Zhuoran Yang},
  journal= {arXiv preprint arXiv:2510.15624},
  year   = {2025}
}

Comments

37 pages, 5 figures. Code: https://github.com/ltjed/freephdlabor

R2 v1 2026-07-01T06:43:12.793Z