State Aware Guideline

State-aware guidelines aim to improve the performance and reliability of AI models, particularly large language models (LLMs), by providing explicit instructions tailored to specific contexts or states within a task. Current research focuses on automatically generating these guidelines from data, optimizing their selection for various applications (e.g., time series analysis, named entity recognition), and evaluating their impact on model accuracy and efficiency. This work is significant because effective guidelines can enhance model generalization, reduce reliance on extensive training data, and improve the trustworthiness and explainability of AI systems across diverse fields, from healthcare to education.