LLM-derived measurement semantics enable a lightweight pre-inference correction step that reduces industrial prediction MAE by 30.7% on real tests and 80.3% under controlled sensor corruption.
Hybrid grid search and Bayesian optimization-based random forest regression for predicting material compression pressure in manufacturing processes,
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LLM-Guided Measurement Credibility Correction for Trustworthy Industrial Process Inference
LLM-derived measurement semantics enable a lightweight pre-inference correction step that reduces industrial prediction MAE by 30.7% on real tests and 80.3% under controlled sensor corruption.