DeepTutor: Towards Agentic Personalized Tutoring
Education is one of the most promising real-world applications for Large Language Models (LLMs). However, current LLMs rely on static pre-training knowledge and lack adaptation to individual learners, while existing RAG systems fall short in delivering personalized, guided feedback. To bridge this gap, we present DeepTutor, a fully open-source agentic framework that unifies citation-grounded problem tutoring with difficulty-calibrated question generation. A hybrid personalization engine couples static knowledge grounding with dynamic learner memory, continuously adapting each interaction to the student's evolving needs. The same personalization substrate further extends to adaptive learni...
| Authors | Bingxi Zhao, Jiahao Zhang, Xubin Ren et al. |
|---|---|
| Primary category | cs.CY |
| Published | 10 April 2026 |
| Last updated at source | 9 July 2026 |
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