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What is Tacit Knowledge Extraction Via Logic Augmented Generation and Active Inference about?

This paper presents a neuro-symbolic framework for extracting and enriching tacit knowledge in procedural domains, focusing on the challenges of capturing implicit assumptions and contextual constraints. The proposed approach combines Logic-Augmented Generation and Active-Inference-inspired strategies to construct ontology-grounded Knowledge Graphs from instructional videos, particularly in manufacturing contexts. Evaluation results indicate that this method enhances the completeness and semantic quality of

Author

ankitk.connect

Language

EN