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Aleksandr Abramov

Aleksandr Abramov has 2 papers in our library, in 2024–2025, most of them on Language models & pretraining, Evaluation & benchmarks; often with Artem Snegirev, Maria Tikhonova, Alena Fenogenova.

2 papers in our library · 2024–2025

OpenAlex · ORCID · h-index 3 · 19 works · 36 citations OpenAlex, 2026-10-14

📄 2 works in our library · 🔗 Cited 54 times in our library · ⭐ Paper Stars ranking: #7159

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

🎓Peoples' Friendship University of RussiaMoscow · Russia2018–2025 · 6 paperscurrent🔬National Medical Research Center of CardiologyMoscow · Russia2024–2025 · 3 paperscurrent🏛️Ministry of Health of the Russian FederationMoscow · Russia2025 · 1 papercurrent

From the bylines of their papers (OpenAlex, 2026-10-14), ORCID and Wikidata; institutions on papers are matched by machine.

 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 2Research subjects and languages the work is about.Language models & pretraining · 1 workEvaluation & benchmarks · 1 work

 Works by year

2020s

20251 paper20241 paper

 Papers

The most cited first (OpenAlex and our library).

  1. 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…
  2. 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…

 Co-authors here

6 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 54 times (of the 149,439 papers whose bibliographies we read); 13 citing papers with a page here →.

Updated

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