TS-HINT: Boosting Semiconductor Time Series Prediction with LLM Reasoning

This research introduces a novel approach to improving time series regression in the semiconductor industry by leveraging the reasoning capabilities of large language models. The use of attention hints from LLMs represents a potentially significant advancement in predictive modeling within a specialized field.

• •Applies LLM reasoning to time series forecasting in semiconductor manufacturing.
• •Utilizes attention mechanisms to guide the regression process.
• •Potentially improves accuracy and efficiency in predicting semiconductor trends.