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Achieving 13.8x compression on LLMs while improving accuracy by 3.70 percentage points could redefine on-device inference for IIoT applications.
Achieving 92.61% accuracy in bearing fault diagnosis with just 10% labeled data reveals a transformative approach to predictive maintenance in industrial settings.
Achieving 98.49% diagnostic accuracy with a 12.6-fold reduction in computational cost, this framework revolutionizes real-time bearing fault diagnosis.
