Optimizing In-Context Demonstrations for LLM-based Automated Grading

Researchers introduce GUIDE, a new framework for improving automated grading of student responses using large language models. The system addresses key limitations in current LLM-based grading by optimizing the selection of training examples and generating better explanations for scoring decisions.