Stanford team turns research papers into interactive AI agents
A Stanford Medicine team led by Jiacheng Miao and James Zou developed Paper2Agent, an AI system that transforms full manuscripts — including text, figures and data — into interactive agents that can answer questions, reproduce research in simulated environments, and interact with other paper agents. Worker agents attempt to reproduce experiments and capture procedural know-how, storing it in a model context protocol (MCP); agents can also question human authors for undocumented judgment calls. Published Sept. 16 in Nature, the team showed agent-to-agent discovery by linking a genome prediction tool to an ADHD dataset via a variant near MPHOSPH9, while noting attribution and safety limits.
Paper2Agent converts manuscripts into interactive AI agents.
Context
Researchers built an AI pipeline that turns papers into interactive agents. They published results and demonstrated cross-paper discovery. Next steps include scaling agent numbers and improving safety and attribution.
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