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Evgeniia Razumovskaia

Evgeniia Razumovskaia has 2 papers in our library, in 2023–2025, most of them on Multilingual & cross-lingual NLP, Language models & pretraining, Dialogue systems; often with Anna Korhonen, Ivan Vulić, Edoardo Maria Ponti.

2 papers in our library · 2023–2025

OpenAlex · ORCID · h-index 7 · 31 works · 202 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 71 times in our library · 1 more in our library without a page yet · ⭐ Paper Stars ranking: #7410

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

🎓University of CambridgeCambridge · United Kingdom2022–2026 · 17 paperscurrent🏢Google DeepMindLondon · United Kingdom2026 · 1 papercurrent🎓Carnegie Mellon UniversityPittsburgh · United States2019 · 2 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).Artificial Intelligence · 2 worksArts and Humanities · 2 worksComputer Science · 2 worksLanguage and Linguistics · 2 works

🧭 Topics 3Research subjects and languages the work is about.Multilingual & cross-lingual NLP · 2 worksDialogue systems · 1 workLanguage models & pretraining · 1 work

 Works by year

2020s

20251 paper20231 paper

 Papers

The most cited first (OpenAlex and our library).

  1. Cross-Lingual Dialogue Dataset Creation via Outline-Based Generation (2023 · 51 citations)
    Multilingual task-oriented dialogue (ToD) systems lack good training and evaluation data. Datasets built from scratch tend to be small and cover few dialogue flows. Datasets translated from English often read unnaturally, miss local cultural context, and make cross-lingual scores look better than they really are. The…
  2. Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet? (2025 · 15 citations)
    Few-shot adaptation of NLP models to new languages can follow three paths: supervised fine-tuning (SFT) of compact multilingual models, supervised instruction tuning (SIT), or in-context learning (ICL) with large generative LLMs.

All works

3 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. Pretraining Methods for Dialog Context Representation Learning ↗Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics · no summary yetShikib Mehri et al.2019 · 111 citations
  2. Cross-Lingual Dialogue Dataset Creation via Outline-Based GenerationTransactions of the Association for Computational Linguistics (TACL)Olga Majewska, Evgeniia Razumovskaia, Edoardo M. Ponti, et al.2023 · 51 citations
  3. Analyzing and Adapting Large Language Models for Few-Shot Multilingual NLU: Are We There Yet?Transactions of the Association for Computational Linguistics (TACL)Evgeniia Razumovskaia, Ivan Vulić, Anna Korhonen2025 · 15 citations

 Co-authors here

4 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 71 times (of the 149,439 papers whose bibliographies we read); 9 citing papers with a page here →.

Updated

This page in Markdown → https://md.research.elamur.ai/free/en/authors/evgeniia-razumovskaia/