#automated-grading2 articles

2 articles

AINeutralarXiv – CS AI · 4h ago1

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Confusion-Aware Rubric Optimization for LLM-based Automated Grading

Researchers introduce CARO (Confusion-Aware Rubric Optimization), a new framework that improves LLM-based automated grading by using confusion matrices to separate and fix specific error patterns instead of aggregating all errors together. This approach prevents conflicting constraints and significantly outperforms existing methods in teacher education and STEM datasets.

AINeutralarXiv – CS AI · 4h ago1

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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.