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The paper proposes AICG, an AI-aware cognitive-supervised two-branch framework for automated mathematical short-answer grading that combines RoBERTa-based scoring with Q-matrix skill prediction and a Gen-AI detector to weight unreliable responses, reducing MAE by 50.3% and improving QWK from 0.798 to 0.927 over RoBERTa regression.