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Ekaterina Kochmar

Ekaterina Kochmar has 4 papers in our library, in 2016–2026, most of them on Language models & pretraining, Grammatical error correction & learner language, English; often with Kaushal Kumar Maurya, Aurélie Herbelot, Bashar Alhafni.

4 papers in our library · 2016–2026

OpenAlex · ORCID · Wikidata · h-index 15 · 111 works · 1,019 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 253 times in our library · 11 more in our library without a page yet · ⭐ Paper Stars ranking: #5436

The profile is the library's match of the name; two people with one name are not always told apart.

Elsewhere: Google Scholar · Semantic Scholar · dblp · ACL Anthology

 Affiliations

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 6 more institutions on single bylines are not listed.

 Fields, topics and concepts

Of its works in our library, with the number of works on each.

 Works by year

2020s

2010s

 Papers

The most cited first (OpenAlex and our library).

  1. Text Readability Assessment for Second Language Learners (2016 · 222 citations)
    The paper addresses automatic readability grading for learners of English as a second language. The main obstacle is that almost all level-annotated corpora target native-speaking children, and their levels reflect native criteria. The authors build a small CEFR-graded set of reading passages from Cambridge English…
  2. ‘Calling on the classical phone': a distributional model of adjective-noun errors in learners' English (2016 · 5 citations)
    The paper tackles detecting wrong adjective choices in English written by learners, where an adjective is misused in its context of use (e.g.
  3. AITutor-EvalKit: Exploring the Capabilities of AI Tutors (2026 · 2 citations)
    AITutor-EvalKit is an open-source toolkit for judging the pedagogical quality of LLM-based tutors. Educators currently struggle to trust these systems, partly because no tool assesses tutor responses on the fly. The toolkit targets Student Mistake Remediation in middle-school math dialogues. It scores a tutor's reply…
  4. Opportunities and Challenges of LLMs in Education: An NLP Perspective (2026)
    This position-and-survey paper looks at how large language models are changing educational NLP. Earlier overviews were mostly aimed at education-technology readers or covered only narrow areas such as writing assessment. The authors instead write for NLP researchers and tie recent LLM work back to older lines of NLP…

All works

15 works of theirs in our library, the most cited first; 4 with a page here, the others link their original until we summarise them.

  1. Automated Personalized Feedback Improves Learning Gains in An Intelligent Tutoring System ↗Lecture Notes in Computer Science · no summary yetEkaterina Kochmar et al.2020 · 105 citations
  2. Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors ↗Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 1: Long Papers) · no summary yetKaushal Kumar Maurya et al.2025 · 53 citations
  3. The BEA 2023 Shared Task on Generating AI Teacher Responses in Educational Dialogues ↗Proceedings of the 18th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2023) · no summary yetAnaïs Tack et al.2023 · 51 citations
  4. Recursive Context-Aware Lexical Simplification ↗Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing and the 9th International Joint Conference on Natural Language Processing (EMNLP-IJCNLP) · no summary yetSian Gooding, Ekaterina Kochmar2019 · 45 citations
  5. Findings of the BEA 2025 Shared Task on Pedagogical Ability Assessment of AI-powered Tutors ↗Proceedings of the 20th Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2025) · no summary yetEkaterina Kochmar et al.2025 · 36 citations
  6. What Makes Math Word Problems Challenging for LLMs? ↗Findings of the Association for Computational Linguistics: NAACL 2024 · no summary yetKv Aditya Srivatsa, Ekaterina Kochmar2024 · 26 citations
  7. REFeREE: A REference-FREE Model-Based Metric for Text Simplification ↗Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024) · no summary yetYichen Huang, Ekaterina Kochmar2024 · 10 citations
  8. Cross-Lingual Lexico-Semantic Transfer in Language Learning ↗Proceedings of the 54th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers) · no summary yetEkaterina Kochmar, Ekaterina Shutova2016 · 2 citations
  9. Towards Reward Modeling for AI Tutors in Math Mistake Remediation ↗Proceedings of the Fifteenth Language Resources and Evaluation Conference · no summary yetKseniia Petukhova, Ekaterina Kochmar2026 · 1 citation
  10. ComplexityMT: Benchmarking the Interaction Between Text Complexity and Machine Translation ↗arXiv:2606.05421 · no summary yetJoseph Marvin Imperial et al.2026
  11. Towards Pedagogically Aligned LLM Tutors for Math Mistake Remediation ↗Proceedings of the 21st Workshop on Innovative Use of NLP for Building Educational Applications (BEA 2026) · no summary yetKseniia Petukhova, Tien Dat Nguyen, Ekaterina Kochmar2026

 Co-authors here

8 co-authors with a page, the most papers together first.

Venues

Where their works here were published, the most works first, with the editions of those that have a page.

 Cited by

Papers of our library cite their works 253 times (of the 149,439 papers whose bibliographies we read); 32 citing papers with a page here →.

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