Data to 7 Oct 2026

LeafTutor: An AI Agent for Programming Assignment Tutoring

arXiv 2601.02375 ↗First posted 12 Dec 2025cs.CY cs.AI cs.SEcited by 0

On the map: LLM agents and tool use → Educational agents and math problem solving

Abstract (arXiv)

High enrollment in STEM-related degree programs has created increasing demand for scalable tutoring support, as universities experience a shortage of qualified instructors and teaching assistants (TAs). To address this challenge, LeafTutor, an AI tutoring agent powered by large language models (LLMs), was developed to provide step-by-step guidance for students. LeafTutor was evaluated through real programming assignments. The results indicate that the system can deliver step-by-step programming guidance comparable to human tutors. This work demonstrates the potential of LLM-driven tutoring solutions to enhance and personalize learning in STEM education. If any reader is interested in collaboration with our team to improve or test LeafTutor, please contact Pu Tian ([email protected]) or Yalong Wu ([email protected]).

Key facts. No citing papers in the map yet (data through 7 Oct 2026). Placed in Educational agents and math problem solving, one of 16 directions in LLM agents and tool use. Builds on 3 of its 8 references that are in the map. First posted on arXiv 12 Dec 2025.

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3 of 8 references.

References · 3

2023GPT-4 Technical Reportcited by 18,132
2023Generative Agents: Interactive Simulacra of Human Behaviorcited by 3,500
2024Gemini 1.5: Unlocking multimodal understanding across millions of tokens of contextcited by 3,175

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