Application of LLM in the Context of Industrial Product Classification

To address the challenges of insufficient data, poor generalization performance, and low accuracy in traditional industrial product classification techniques, this paper proposes a novel classification model that combines large language models (LLMs) with deep learning for text classification. By leveraging LLMs for data augmentation and calibration of classification results, the model optimizes the traditional technical framework. Experimental results show that compared with the original model, the new model achieves significant improvements in accuracy, recall, and precision.