RoMathExam supplies a century-long collection of Romanian math exams together with a new intrinsic complexity metric that correlates across frontier models at r > 0.72.
Text-based approaches to item difficulty modeling in large-scale assessments: A systematic review.arXiv preprint arXiv:2509.23486,
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Epi2Diff extracts cognitive episode sequences from LRM reasoning traces and combines them with semantic features to predict human item difficulty, outperforming baselines on four educational datasets.
Fine-tuned transformers with multi-task learning recover substantial wording-derived signal for item difficulty at small sample sizes typical in applied testing.
citing papers explorer
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RoMathExam: A Longitudinal Dataset of Romanian Math Exams (1895-2025) with a Seven-Decade Core (1957-2025)
RoMathExam supplies a century-long collection of Romanian math exams together with a new intrinsic complexity metric that correlates across frontier models at r > 0.72.
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Cognitive Episodes in LLM Reasoning Traces Enable Interpretable Human Item Difficulty Prediction
Epi2Diff extracts cognitive episode sequences from LRM reasoning traces and combines them with semantic features to predict human item difficulty, outperforming baselines on four educational datasets.
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Response-free item difficulty modelling for multiple-choice items with fine-tuned transformers: Component-wise representation and multi-task learning
Fine-tuned transformers with multi-task learning recover substantial wording-derived signal for item difficulty at small sample sizes typical in applied testing.