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Knowledge-guided multimodal LLM with mixture-of-experts for interpretable defect detection and fault diagnosis: An industrial AI copilot

Xinyue Guo et al.

Journal of Manufacturing Systems2026https://doi.org/10.1016/j.jmsy.2026.02.017article
AJG 1ABDC B
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0.50

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https://doi.org/https://doi.org/10.1016/j.jmsy.2026.02.017

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@article{xinyue2026,
  title        = {{Knowledge-guided multimodal LLM with mixture-of-experts for interpretable defect detection and fault diagnosis: An industrial AI copilot}},
  author       = {Xinyue Guo et al.},
  journal      = {Journal of Manufacturing Systems},
  year         = {2026},
  doi          = {https://doi.org/https://doi.org/10.1016/j.jmsy.2026.02.017},
}

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Knowledge-guided multimodal LLM with mixture-of-experts for interpretable defect detection and fault diagnosis: An industrial AI copilot

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Evidence weight

0.50

Balanced mode · F 0.40 / M 0.15 / V 0.05 / R 0.40

F · citation impact0.50 × 0.4 = 0.20
M · momentum0.50 × 0.15 = 0.07
V · venue signal0.50 × 0.05 = 0.03
R · text relevance †0.50 × 0.4 = 0.20

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