🔗 Who cites «MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors»

16 papers of our library cite it (of the 149,439 whose bibliographies we read) · 6 with a page here, the most cited first · ← back to «MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM Tutors»

1. From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement LearningConference on Empirical Methods in Natural Language Processing (EMNLP)David Dinucu-Jianu, Jakub Macina, Nico Daheim, et al.2025 · 19 citations
2. Position: LLMs Can be Good Tutors in English EducationConference on Empirical Methods in Natural Language Processing (EMNLP)Jingheng Ye, Shen Wang, Deqing Zou, et al.2025 · 9 citations
3. AITutor-EvalKit: Exploring the Capabilities of AI TutorsConference of the European Chapter of the Association for Computational Linguistics (EACL)Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, et al.2026 · 2 citations
4. Towards Reward Modeling for AI Tutors in Math Mistake RemediationLanguage Resources and Evaluation Conference (LREC)Kseniia Petukhova, Ekaterina Kochmar2026 · 1 citation
5. Consistency of LLMs to Comparative Statements in Mathematical Reasoning TasksLanguage Resources and Evaluation Conference (LREC)Aidan W. San, Daniel Juyoung Son, Xiaodong Liu, et al.2026
6. MMTutorBench: The First Multimodal Benchmark for AI Math TutoringAnnual Meeting of the Association for Computational Linguistics (ACL)Tengchao Yang, Sichen Guo, Mengzhao Jia, et al.2026

10 more papers of our library cite it; they have no page here yet.

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