🔗 Who cites «Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors»

43 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 «Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors»

1. 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
2. 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
3. Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student AttacksAnnual Meeting of the Association for Computational Linguistics (ACL)Jin Zhao, Marta Knežević, Tanja Käser2026 · 1 citation
4. PATS: Personality-Aware Teaching Strategies with Large Language Model TutorsFindings of the Association for Computational LinguisticsDonya Rooein, Sankalan Pal Chowdhury, Mariia Eremeeva, et al.2026 · 1 citation
5. Confirming Correct, Missing the Rest: LLM Tutoring Agents Struggle Where Feedback Matters MostWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Tahreem Yasir, Wenbo Li, Sam Gilson, et al.2026
6. Opportunities and Challenges of LLMs in Education: An NLP PerspectiveWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Sowmya Vajjala, Bashar Alhafni, Stefano Banno, et al.2026

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

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