🧑‍🔬 Who cites Jakub Macina

216 citations of their works from 140 papers of our library (of the 149,439 whose bibliographies we read) · 38 with a page here, the most cited first · ← Jakub Macina

1. Challenges and Applications of Large Language ModelsarXiv:2307.10169Jean Kaddour, Joshua Harris, Maximilian Mozes, et al.2023 · 301 citations
2. Distilling Reasoning Capabilities into Smaller Language ModelsFindings of the Association for Computational LinguisticsKumar Shridhar, Alessandro Stolfo, Mrinmaya Sachan2023 · 219 citations
3. MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning ProblemsFindings of the Association for Computational LinguisticsJakub Macina, Nico Daheim, Sankalan Chowdhury, et al.2023 · 131 citations
4. CLASS: A Design Framework for Building Intelligent Tutoring Systems Based on Learning Science principlesFindings of the Association for Computational Linguistics: EMNLP 2023Shashank Sonkar, Naiming Liu, Debshila Mallick, et al.2023 · 71 citations
5. AutoTutor meets Large Language Models: A Language Model Tutor with Rich Pedagogy and GuardrailsACM Conference on Learning @ Scale (L@S)Sankalan Pal Chowdhury, Vilém Zouhar, Mrinmaya Sachan2024 · 66 citations
6. Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI TutorsConference of the North American Chapter of the Association for Computational Linguistics (NAACL)Kaushal Kumar Maurya, Kv Aditya Srivatsa, Kseniia Petukhova, et al.2025 · 53 citations
7. Towards responsible development of generative AI for education: An evaluation-driven approachJurenka2024 · 53 citations
8. Plug-and-Play Policy Planner for Large Language Model Powered Dialogue AgentsarXiv:2311.00262Yang Deng, Wenxuan Zhang, Wai Lam, et al.2023 · 48 citations
9. Training LLM-Based Tutors to Improve Student Learning Outcomes in DialoguesLecture notes in computer scienceAlexander Scarlatos, Naiming Liu, Jaewook Lee, et al.2025 · 38 citations
10. Can Language Models Employ the Socratic Method? Experiments with Code DebuggingACM Technical Symposium on Computer Science Education (SIGCSE)Erfan Al-Hossami, Razvan Bunescu, Justin Smith, et al.2023 · 38 citations
11. Exploring the Numerical Reasoning Capabilities of Language Models: A Comprehensive Analysis on Tabular DataFindings of the Association for Computational LinguisticsMubashara Akhtar, Abhilash Shankarampeta, Vivek Gupta, et al.2023 · 38 citations
12. Stepwise Verification and Remediation of Student Reasoning Errors with Large Language Model TutorsConference on Empirical Methods in Natural Language Processing (EMNLP)Nico Daheim, Jakub Macina, Manu Kapur, et al.2024 · 35 citations
13. Socratic Questioning of Novice Debuggers: A Benchmark Dataset and Preliminary EvaluationsWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Erfan Al-Hossami, Razvan Bunescu, Ryan Teehan, et al.2023 · 34 citations
14. MathTutorBench: A Benchmark for Measuring Open-ended Pedagogical Capabilities of LLM TutorsConference on Empirical Methods in Natural Language Processing (EMNLP)Jakub Macina, Nico Daheim, Ido Hakimi, et al.2025 · 33 citations
15. Language Models as Science TutorsarXiv:2402.11111Alexis Chevalier, Jiayi Geng, Alexander Wettig, et al.2024 · 30 citations
16. Can Language Models Solve Olympiad Programming?arXiv:2404.10952Quan Shi, Michael Tang, Karthik Narasimhan, et al.2024 · 28 citations
17. 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
18. Improving Socratic Question Generation using Data Augmentation and Preference OptimizationWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Nischal Ashok Kumar, Andrew Lan2024 · 16 citations
19. MathChat: Benchmarking Mathematical Reasoning and Instruction Following in Multi-Turn InteractionsarXiv:2405.19444Zhenwen Liang, Dian Yu, Wenhao Yu, et al.2024 · 16 citations
20. EducationQ: Evaluating LLMs' Teaching Capabilities Through Multi-Agent Dialogue FrameworkAnnual Meeting of the Association for Computational Linguistics (ACL)Yao Shi, Rongkeng Liang, Yong Xu2025 · 14 citations
21. Embracing Imperfection: Simulating Students with Diverse Cognitive Levels Using LLM-based AgentsAnnual Meeting of the Association for Computational Linguistics (ACL)Tao Wu, Jingyuan Chen, Wang Lin, et al.2025 · 13 citations
22. 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
23. BIPED: Pedagogically Informed Tutoring System for ESL EducationAnnual Meeting of the Association for Computational Linguistics (ACL)Soonwoo Kwon, Sojung Kim, Minju Park, et al.2024 · 9 citations
24. 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
25. Decision-Making with Deliberation: Meta-reviewing as a Document-grounded DialogueConference of the European Chapter of the Association for Computational Linguistics (EACL)Sukannya Purkayastha, Nils Dycke, Anne Lauscher, et al.2026 · 2 citations
26. SHAPE: Unifying Safety, Helpfulness and Pedagogy for Educational LLMsAnnual Meeting of the Association for Computational Linguistics (ACL)Sihang Zhao, Kangrui Yu, Youliang Yuan, et al.2026 · 2 citations
27. 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
28. 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
29. Towards Reward Modeling for AI Tutors in Math Mistake RemediationLanguage Resources and Evaluation Conference (LREC)Kseniia Petukhova, Ekaterina Kochmar2026 · 1 citation
30. Building Common Ground in Dialogue: A SurveyLUHME WorkshopTatiana Anikina, Alina Leippert, Simon Ostermann2025 · 1 citation
31. Beyond Accuracy: Alignment and Error Detection across Languages in the Bi-GSM8K Math-Teaching BenchmarkFindings of the Association for Computational LinguisticsJieun Park, KyungTae Lim, Joon-ho Lim2026
32. 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
33. 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
34. 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
35. 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
36. Tackling the Root of Misinformation by Teaching Laypeople about Logical Fallacies via Socratic Questioning and Critical ArgumentationAnnual Meeting of the Association for Computational Linguistics (ACL)Minjing Shi, Junling Wang, Jingwei Ni, et al.2026
37. The Aftermath of DrawEduMath: Vision Language Models Underperform with Struggling Students and Misdiagnose ErrorsWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Li Lucy, Albert Zhang, Nathan Anderson, et al.2026
38. Towards Pedagogically Aligned LLM Tutors for Math Mistake RemediationWorkshop on Innovative Use of NLP for Building Educational Applications (BEA)Kseniia Petukhova, Tien Dat Nguyen, Ekaterina Kochmar2026

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