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Maria Tikhonova

Maria Tikhonova has 4 papers in our library, in 2022–2026, most of them on Language models & pretraining, Dialogue systems, Multilingual & cross-lingual NLP; often with Aleksandr Abramov, Alena Fenogenova, Artem Snegirev.

4 papers in our library · 2022–2026

OpenAlex · ORCID · h-index 4 · 31 works · 105 citations OpenAlex, 2026-10-14

📄 4 works in our library · 🔗 Cited 299 times in our library · ⭐ Paper Stars ranking: #5085

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

🎓National Research University Higher School of EconomicsMoscow · Russia2019–2026 · 28 paperscurrent🎓Skolkovo Institute of Science and TechnologySkolkovo · Russia2026 · 1 papercurrent

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 · 4 worksArts and Humanities · 4 worksComputer Science · 4 worksLanguage and Linguistics · 4 works

🧭 Topics 6Research subjects and languages the work is about.Language models & pretraining · 1 workLow-resource languages · 1 workMultilingual & cross-lingual NLP · 1 workEvaluation & benchmarks · 1 workDialogue systems · 1 workVision & language · 1 work

 Works by year

2020s

20261 paper20251 paper20241 paper20221 paper

 Papers

The most cited first (OpenAlex and our library).

  1. mGPT: Few-Shot Learners Go Multilingual (2022 · 203 citations)
    Most autoregressive language models capable of few-shot learning target English or a few high-resource languages.
  2. A Family of Pretrained Transformer Language Models for Russian (2024 · 60 citations)
    Openly available Transformer language models built specifically for Russian have been scarce. Researchers have mostly relied on massively multilingual models such as mBERT or XLM-R, plus a few monolingual releases like DeepPavlov's RuBERT. The authors describe a family of 13 Russian models across three architecture…
  3. The Russian-focused embedders' exploration: ruMTEB benchmark and Russian embedding model design (2025 · 19 citations)
    Russian has lacked modern, dedicated text embedding models and a broad evaluation suite. Popular Russian encoders such as rubert-tiny2 and the SBERT large-nlu-ru variants are several years old, monolingual, and trained on dated corpora. The only Russian embedding benchmark, enkodechka, is small and has no retrieval…
  4. From Standard Transformers to Modern LLMs: Bringing Dialogue Models, RAG, and Agents to the Classroom (2026)
    This TeachNLP 2026 paper describes the second edition of an open university course on Transformer-based LLMs and multimodal models, first presented by Nikishina et al.

 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 299 times (of the 149,439 papers whose bibliographies we read); 77 citing papers with a page here →.

Updated

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