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Stanford's Paper2Agent turns papers into interactive AI agents
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Fusion42 · 18 September 2026 · Fusion42 review
Stanford researchers developed Paper2Agent, a framework that transforms research papers and their codebases into interactive AI agents that can be queried in natural language, achieving over 91% accuracy on computational biology benchmarks. The system enables AI agents derived from different papers to interact, revealing potential novel scientific findings.
This Wire brief sits within Fusion42's coverage of AI & ML, and 3 sources have reported it between 16 Sep 2026 and 27 Sep 2026.
◆ ◆ The Wire takeaway
You can now build AI that turns research papers into interactive assistants, opening routes to automated knowledge extraction and faster discovery in life sciences. This shifts how your AI product could access and apply scientific data without manual parsing of papers.
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3 sources · first reported 16 Sep 2026 · latest 27 Sep 2026
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