PaperPulse releases multi-agent paper auditing tool
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Developer OwiiiP has released PaperPulse, a multi-agent AI system orchestrated with LangGraph, designed to automatically audit the methodological rigor, statistical validity, and code-paper consistency of scientific papers, news, and web content. The system chains four agents in sequence—general extraction, GitHub code location, statistical critique, and citation traceability synthesis—searching official GitHub repositories and flagging reproducibility gaps with precise citations, ultimately outputting a structured JSON report rendered as Markdown in a Chrome extension sidebar.
AI overview based on source reports · Updated 2 hr ago
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- Hacker News AIMulti-agent AI (LangGraph) to audit AI papers for reproducibility
PaperPulse is a browser-integrated, multi-agent AI system that audits scientific papers, news articles, and web content for methodological rigor, statistical validity, and code-to-paper alignment. It uses a LangGraph orchestrator with four agents—a universal extractor, a GitHub/code grounder, a statistical critic, and a citation-grounded synthesizer—to cross-reference claims, search GitHub for official repositories, and flag reproducibility gaps with exact citations, returning a structured JSON report rendered as Markdown in a Chrome extension.
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