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A Unified LLM-Adaptable Framework for Cold-Start Cognitive Diagnosis
arXiv:2505.21239v2 Announce Type: replace Abstract: Cognitive Diagnosis has become a critical task in AI-empowered education, supporting personalized learning by accurately assessing students' cognitive states. However, traditional cognitive diagnosis models (CDMs) often struggle in cold-start scenarios due to the lack of student-exercise interaction data. Recent NLP-based approaches leveraging pre-trained language models (PLMs) have shown promise by utilizing textual features, but they fail...