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Kseniia Petukhova

Kseniia Petukhova has 2 papers in our library, in 2025–2026, most of them on Language models & pretraining, Evaluation & benchmarks; often with Ekaterina Kochmar, Kaushal Kumar Maurya, Numaan Naeem.

2 papers in our library · 2025–2026

OpenAlex · h-index 3 · 27 works · 44 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 79 times in our library · 3 more in our library without a page yet · ⭐ Paper Stars ranking: #8915

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

🎓Mohamed bin Zayed University of Artificial IntelligenceAbu Dhabi · United Arab Emirates2022–2026 · 9 paperscurrent🎓Moscow Institute of Physics and TechnologyDolgoprudny · Russia2023–2025 · 3 papers

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine. 1 more institution on single bylines are not listed.

 Fields, topics and concepts

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

📚 Shelves 4The field of science this work belongs to (OpenAlex fields).Computer Science · 2 worksArtificial Intelligence · 2 worksInformation Systems · 2 worksComputer Science Applications · 1 work

🧭 Topics 2Research subjects and languages the work is about.Evaluation & benchmarks · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20261 paper20251 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Unifying AI Tutor Evaluation: An Evaluation Taxonomy for Pedagogical Ability Assessment of LLM-Powered AI Tutors (2025 · 53 citations)
    Evaluations of LLM-based tutors have so far used inconsistent, often subjective criteria. Definitions differ across studies, which makes systems hard to compare and progress hard to track. Standard NLG metrics are also a poor fit: they ignore pedagogy and usually need reference answers. The authors address this for…
  2. 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…

All works

5 works of theirs in our library, the most cited first; 2 with a page here, the others link their original until we summarise them.

  1. 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
  2. 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
  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 Remediation ↗Proceedings of the Fifteenth Language Resources and Evaluation Conference · no summary yetKseniia Petukhova, Ekaterina Kochmar2026 · 1 citation
  5. 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

3 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 79 times (of the 149,439 papers whose bibliographies we read); 8 citing papers with a page here →.

Updated

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