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OAK -- Onboarding with Actionable Knowledge
June 25, 2025 Β· Declared Dead Β· π arXiv.org
"No code URL or promise found in abstract"
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Authors
Steve Devènes, Marine Capallera, Robin Cherix, Elena Mugellini, Omar Abou Khaled, Francesco Carrino
arXiv ID
2507.02914
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.AI,
cs.LG
Citations
0
Venue
arXiv.org
Last Checked
5 months ago
Abstract
The loss of knowledge when skilled operators leave poses a critical issue for companies. This know-how is diverse and unstructured. We propose a novel method that combines knowledge graph embeddings and multi-modal interfaces to collect and retrieve expertise, making it actionable. Our approach supports decision-making on the shop floor. Additionally, we leverage LLMs to improve query understanding and provide adapted answers. As application case studies, we developed a proof-of-concept for quality control in high precision manufacturing.
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