AINeutralarXiv – CS AI · May 116/10
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Tacit Knowledge Extraction via Logic Augmented Generation and Active Inference
Researchers introduce a neuro-symbolic framework combining Logic-Augmented Generation and Active Inference to extract and formalize tacit knowledge into machine-interpretable Knowledge Graphs. The approach addresses a critical gap in knowledge engineering by capturing implicit assumptions and contextual expertise from procedural domains like manufacturing, demonstrated through analysis of assembly repair videos.