AINeutralarXiv – CS AI · 3h ago6/10
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From paper to benchmark: agentic, framework-based reproduction of under-specified methods in machine health intelligence
Researchers introduce an agentic, framework-based approach to reproducibly translate machine learning papers—specifically in Prognostics and Health Management (PHM)—into executable, comparable benchmark implementations. By mapping papers onto a shared framework with structured slot-binding interfaces, the method addresses critical reproducibility gaps caused by incomplete documentation, implicit design choices, and restricted dataset access.