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REAT: A Reflective Experience-Augmented Tutoring Framework for Multi-turn Mathematical Instruction
Current Large Language Models (LLMs) excel at solving complex mathematical problems, yet this proficiency does not inherently translate into effective tutoring. While advanced LLM tutors may leverage multi-agent frameworks or fine-tuning, most still lack a mechanism to systematically accumulate and
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