---
title: "Who cites Anaïs Tack — 280 papers of our library"
description: "280 papers of the Elamur Research library cite the works of Anaïs Tack, found in their bibliographies; the most cited first."
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# Who cites Anaïs Tack

342 citations of their works from 280 papers of our library (of the 149,439 whose bibliographies we read) · 46 with a page here, the most cited first · [← Anaïs Tack](https://md.research.elamur.ai/free/en/authors/anais-tack/)

1. [**ChatGPT for Good? On Opportunities and Challenges of Large Language Models for Education**Enkelejda Kasneci, Kathrin Seßler, Stefan Küchemann, et al.*2023 · 7,440 citations*](https://md.research.elamur.ai/free/en/papers/kasneci-2023-chatgpt-good-opportunities-challenges-large/)
2. [**Evaluating Large Language Models: A Comprehensive Survey arXiv:2310.19736**Zishan Guo, Renren Jin, Chuang Liu, et al.*2023 · 182 citations*](https://md.research.elamur.ai/free/en/papers/guo-2023-evaluating-large-language-models-comprehensive/)
3. **[MathDial: A Dialogue Tutoring Dataset with Rich Pedagogical Properties Grounded in Math Reasoning Problems](https://md.research.elamur.ai/free/en/papers/macina-2023-mathdial-dialogue-tutoring-dataset-rich/) [Findings of the Association for Computational Linguistics](https://md.research.elamur.ai/free/en/venues/findings/)**Jakub Macina, Nico Daheim, Sankalan Chowdhury, et al.*2023 · 131 citations*
4. **[MUSS: Multilingual Unsupervised Sentence Simplification by Mining Paraphrases](https://md.research.elamur.ai/free/en/papers/martin-2022-muss-multilingual-unsupervised-sentence-simplification/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Louis Martin, Angela Fan, Éric de la Clergerie, et al.*2022 · 117 citations*
5. [**EduChat: A Large-Scale Language Model-based Chatbot System for Intelligent Education arXiv:2308.02773**Yuhao Dan, Zhikai Lei, Yiyang Gu, et al.*2023 · 58 citations*](https://md.research.elamur.ai/free/en/papers/dan-2023-educhat-large-scale-language-model/)
6. **[Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors](https://md.research.elamur.ai/free/en/papers/maurya-2025-unifying-ai-tutor-evaluation-evaluation/) [Conference of the North American Chapter of the Association for Computational Linguistics (NAACL)](https://md.research.elamur.ai/free/en/venues/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 approach**Jurenka*2024 · 53 citations*](https://md.research.elamur.ai/free/en/papers/jurenka-2024-responsible-development-generative-ai-education/)
8. **[Opportunities and Challenges in Neural Dialog Tutoring](https://md.research.elamur.ai/free/en/papers/macina-2023-opportunities-challenges-neural-dialog-tutoring/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Jakub Macina, Nico Daheim, Lingzhi Wang, et al.*2023 · 51 citations*
9. **[The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues](https://md.research.elamur.ai/free/en/papers/tack-2023-bea-2023-shared-task-generating/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Anaïs Tack, Ekaterina Kochmar, Zheng Yuan, et al.*2023 · 51 citations*
10. **[Predicting Lexical Complexity in English Texts: The Complex 2.0 Dataset](https://md.research.elamur.ai/free/en/papers/shardlow-2021-predicting-lexical-complexity-english-texts/) [Language Resources and Evaluation](https://md.research.elamur.ai/free/en/venues/language-resources-and-evaluation/)**Matthew Shardlow, Richard Evans, Marcos Zampieri*2021 · 49 citations*
11. **[EFLLex: A Graded Lexical Resource for Learners of English as a Foreign Language](https://md.research.elamur.ai/free/en/papers/durlich-2018-efllex-graded-lexical-resource-learners/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Luise Dürlich, Thomas François*2018 · 46 citations*
12. **[Can Language Models Employ the Socratic Method? Experiments with Code Debugging](https://md.research.elamur.ai/free/en/papers/al-hossami-2023-language-models-employ-socratic-method/) [ACM Technical Symposium on Computer Science Education (SIGCSE)](https://md.research.elamur.ai/free/en/venues/acm-technical-symposium-on-computer-science-education-sigcse/)**Erfan Al-Hossami, Razvan Bunescu, Justin Smith, et al.*2023 · 38 citations*
13. **[Socratic Questioning of Novice Debuggers: A Benchmark Dataset and Preliminary Evaluations](https://md.research.elamur.ai/free/en/papers/hossami-2023-socratic-questioning-novice-debuggers-benchmark/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/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 Tutors](https://md.research.elamur.ai/free/en/papers/macina-2025-mathtutorbench-benchmark-measuring-open-ended/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Jakub Macina, Nico Daheim, Ido Hakimi, et al.*2025 · 33 citations*
15. **[The SAMER Arabic Text Simplification Corpus](https://md.research.elamur.ai/free/en/papers/alhafni-2024-samer-arabic-text-simplification-corpus/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Bashar Alhafni, Reem Hazim, Juan David Pineros Liberato, et al.*2024 · 30 citations*
16. **[Arabic Word-level Readability Visualization for Assisted Text Simplification](https://md.research.elamur.ai/free/en/papers/hazim-2022-arabic-word-level-readability-visualization/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**Reem Hazim, Hind Saddiki, Bashar Alhafni, et al.*2022 · 29 citations*
17. **[From Problem-Solving to Teaching Problem-Solving: Aligning LLMs with Pedagogy using Reinforcement Learning](https://md.research.elamur.ai/free/en/papers/jianu-2025-problem-solving-teaching-problem-solving/) [Conference on Empirical Methods in Natural Language Processing (EMNLP)](https://md.research.elamur.ai/free/en/venues/emnlp/)**David Dinucu-Jianu, Jakub Macina, Nico Daheim, et al.*2025 · 19 citations*
18. **[MinT: Boosting Generalization in Mathematical Reasoning via Multi-view Fine-tuning](https://md.research.elamur.ai/free/en/papers/liang-2024-mint-boosting-generalization-mathematical-reasoning/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Zhenwen Liang, Dian Yu, Xiaoman Pan, et al.*2024 · 19 citations*
19. **[Controllable Lexical Simplification for English](https://md.research.elamur.ai/free/en/papers/sheang-2022-controllable-lexical-simplification-english/) [Workshop on Text Simplification, Accessibility and Readability](https://md.research.elamur.ai/free/en/venues/tsar/)**Kim Cheng Sheang, Daniel Ferrés, Horacio Saggion*2022 · 16 citations*
20. **[Findings of the BEA 2026 Shared Task on Vocabulary Difficulty Prediction for English Learners](https://md.research.elamur.ai/free/en/papers/felice-2026-findings-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Mariano Felice, Lucy Skidmore*2026 · 9 citations*
21. **[BIPED: Pedagogically Informed Tutoring System for ESL Education](https://md.research.elamur.ai/free/en/papers/kwon-2024-biped-pedagogically-informed-tutoring-system/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Soonwoo Kwon, Sojung Kim, Minju Park, et al.*2024 · 9 citations*
22. **[MWE for Essay Scoring English as a Foreign Language](https://md.research.elamur.ai/free/en/papers/wilkens-2022-mwe-essay-scoring-english-as/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Rodrigo Wilkens, Daiane Seibert, Xiaoou Wang, et al.*2022 · 3 citations*
23. **[katildakat at SemEval-2021 Task 1: Lexical Complexity Prediction of Single Words and Multi-Word Expressions in English](https://md.research.elamur.ai/free/en/papers/voskoboinik-2021-katildakat-semeval-2021-task-1/) [International Workshop on Semantic Evaluation (SemEval)](https://md.research.elamur.ai/free/en/venues/semeval/)**Katja Voskoboinik*2021 · 3 citations*
24. **[AITutor-EvalKit: Exploring the Capabilities of AI Tutors](https://md.research.elamur.ai/free/en/papers/naeem-2026-aitutor-evalkit-exploring-capabilities-ai/) [Conference of the European Chapter of the Association for Computational Linguistics (EACL)](https://md.research.elamur.ai/free/en/venues/eacl/)**Numaan Naeem, Kaushal Kumar Maurya, Kseniia Petukhova, et al.*2026 · 2 citations*
25. **[Glite at BEA 2026 Shared Task 1: Holistic Difficulty Models Dominate, Feature Engineering Closes the Gap in L1-Aware Vocabulary Difficulty Prediction](https://md.research.elamur.ai/free/en/papers/philippov-2026-glite-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Vassili Philippov, Dmitrii Andreev, Pavel Katunin, et al.*2026 · 2 citations*
26. **[BoostedCats at BEA 2026 Shared Task 1: What Makes a Word Hard to Learn? Modeling L1 Influence on English Vocabulary Difficulty](https://md.research.elamur.ai/free/en/papers/martins-2026-boostedcats-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Jonas Mayer Martins, Zhuojing Huang, Aaricia Herygers, et al.*2026 · 1 citation*
27. **[Evaluating Answer Leakage Robustness of LLM Tutors against Adversarial Student Attacks](https://md.research.elamur.ai/free/en/papers/zhao-2026-evaluating-answer-leakage-robustness-llm/) [Annual Meeting of the Association for Computational Linguistics (ACL)](https://md.research.elamur.ai/free/en/venues/acl/)**Jin Zhao, Marta Knežević, Tanja Käser*2026 · 1 citation*
28. **[RETUYT-INCO at BEA 2026 Shared Task 1: Feature-Enriched mDeBERTa for Word Difficulty Prediction](https://md.research.elamur.ai/free/en/papers/robaina-2026-retuyt-inco-bea-2026-shared/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Santiago Robaina, Aiala Rosá, Luis Chiruzzo*2026 · 1 citation*
29. **[SAAKTH at BEA 2026 Shared Task 1: L1-Aware English Vocabulary Difficulty Prediction with Hybrid Transformer and Psycholinguistic Features](https://md.research.elamur.ai/free/en/papers/mattu-2026-saakth-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Karthik Mattu, Adit Dhall, Arshad Naguru, et al.*2026 · 1 citation*
30. **[Sakura at BEA 2026 Shared Task 1: What Makes Vocabulary Difficult?](https://md.research.elamur.ai/free/en/papers/nohejl-2026-sakura-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Adam Nohejl, Xuanxin Wu, Yusuke Ide, et al.*2026 · 1 citation*
31. **[Towards Reward Modeling for AI Tutors in Math Mistake Remediation](https://md.research.elamur.ai/free/en/papers/petukhova-2026-reward-modeling-ai-tutors-math/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Kseniia Petukhova, Ekaterina Kochmar*2026 · 1 citation*
32. **[uogal at BEA 2026 Shared Task 1: Ensemble of Multilingual Encoders with NMT Augmentation for L1-Aware Vocabulary Difficulty Prediction](https://md.research.elamur.ai/free/en/papers/stearns-2026-uogal-bea-2026-shared-task/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Bernardo Stearns, John P. McCrae, Thomas Gaillat, et al.*2026 · 1 citation*
33. **[To What Extent Can English-as-a-Second Language Learners Read Economic News Texts?](https://md.research.elamur.ai/free/en/papers/ehara-2021-what-extent-can-english-as/) [Workshop on Economics and Natural Language Processing](https://md.research.elamur.ai/free/en/venues/econlp/)**Yo Ehara*2021 · 1 citation*
34. **[A Comparative Study of Multilingual Fine-tuning and Prompting for Automatic Text Readability Classification in Galician](https://md.research.elamur.ai/free/en/papers/rey-2026-comparative-study-multilingual-fine-tuning/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Sandra Rodríguez Rey, Marcos Garcia*2026*
35. **[Automated Essay Scoring and Language Certification: Assessing Generalizability, Agreement and Validity for French](https://md.research.elamur.ai/free/en/papers/wilkens-2026-automated-essay-scoring-language-certification/) [Transactions of the Association for Computational Linguistics (TACL)](https://md.research.elamur.ai/free/en/venues/tacl/)**Rodrigo Wilkens, Rémi Cardon, Vincent Folny, et al.*2026*
36. **[Automatic Extraction of Textual and Phonemic Complexity for French Cued Speech](https://md.research.elamur.ai/free/en/papers/norre-2026-automatic-extraction-textual-phonemic-complexity/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Magali Norré, Brigitte Bigi, Núria Gala, et al.*2026*
37. **[From Metrics to Meaning: Rule-Grounded LLM Explanations for Data Literacy in the Case of Youth Football](https://md.research.elamur.ai/free/en/papers/pilka-2026-metrics-meaning-rule-grounded-llm/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Tomasz Piłka, Tomasz Kuczyński, Mateusz Czajka*2026*
38. **[GerVLPro: A CEFR-Graded Vocabulary List of L2 Learners' Productive Vocabulary in German](https://md.research.elamur.ai/free/en/papers/michael-2026-gervlpro-cefr-graded-vocabulary-list/) [Language Resources and Evaluation Conference (LREC)](https://md.research.elamur.ai/free/en/venues/lrec/)**Noah-Manuel Michael, Anna Hülsing, Andrea Horbach*2026*
39. **[Opportunities and Challenges of LLMs in Education: An NLP Perspective](https://md.research.elamur.ai/free/en/papers/vajjala-2026-opportunities-challenges-llms-education-nlp/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Sowmya Vajjala, Bashar Alhafni, Stefano Banno, et al.*2026*
40. **[Portho: A Corpus-Based Resource of Orthographic Neighbors in European Portuguese](https://md.research.elamur.ai/free/en/papers/ribeiro-2026-portho-corpus-based-resource-orthographic/) [International Conference on Computational Processing of Portuguese](https://md.research.elamur.ai/free/en/venues/propor/)**Eugénio Ribeiro, David Antunes, Nuno Mamede, et al.*2026*
41. **[Revisiting German Complex Word Identification: Contextualized LLMs and Feature Injection](https://md.research.elamur.ai/free/en/papers/schomacker-2026-revisiting-german-complex-word-identification/) [Joint Workshop on Readability and Text Simplification (READIxTSAR) @ LREC](https://md.research.elamur.ai/free/en/venues/readi/)**Thorben Schomacker, Seid Muhie Yimam, Chris Biemann, et al.*2026*
42. **[The Aftermath of DrawEduMath: Vision Language Models Underperform with Struggling Students and Misdiagnose Errors](https://md.research.elamur.ai/free/en/papers/lucy-2026-aftermath-drawedumath-vision-language-models/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Li Lucy, Albert Zhang, Nathan Anderson, et al.*2026*
43. **[Towards Pedagogically Aligned LLM Tutors for Math Mistake Remediation](https://md.research.elamur.ai/free/en/papers/petukhova-2026-pedagogically-aligned-llm-tutors-math/) [Workshop on Innovative Use of NLP for Building Educational Applications (BEA)](https://md.research.elamur.ai/free/en/venues/bea/)**Kseniia Petukhova, Tien Dat Nguyen, Ekaterina Kochmar*2026*
44. [**LangLingual: A Personalised, Exercise-oriented English Language Learning Tool Leveraging Large Language Models arXiv:2510.23011**Sammriddh Gupta, Sonit Singh, Aditya Joshi, et al.*2025*](https://md.research.elamur.ai/free/en/papers/gupta-2025-langlingual-personalised-exercise-oriented-english/)
45. **[Leveraging AI to Bridge Classical Arabic and Modern Standard Arabic for Text Simplification](https://md.research.elamur.ai/free/en/papers/altammami-2025-leveraging-ai-bridge-classical-arabic/) [New Horizons in Computational Linguistics for Religious Texts](https://md.research.elamur.ai/free/en/venues/clrel/)**Shatha Altammami*2025*
46. **[Modelling French readability for adults with low literacy (Modélisation de la lisibilité en français pour les personnes en situation d'illettrisme)](https://md.research.elamur.ai/free/en/papers/aissa-2025-modelisation-de-la-lisibilite-en/) [JEP-TALN-RECITAL (the French-speaking conferences on speech and natural language processing)](https://md.research.elamur.ai/free/en/venues/jeptalnrecital/)**Wafa Aissa, Thibault Bañeras-Roux, Elodie Vanzeveren, et al.*2025*

234 more citing papers of our library have no page here yet.

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