mlsanityData to 14 Oct 2026

RuBioRoBERTa: a pre-trained biomedical language model for Russian language biomedical text mining

arXiv 2204.03951 ↗First posted 8 Apr 2022cs.CL cs.AIcited by 6

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Abstract (arXiv)

This paper presents several BERT-based models for Russian language biomedical text mining (RuBioBERT, RuBioRoBERTa). The models are pre-trained on a corpus of freely available texts in the Russian biomedical domain. With this pre-training, our models demonstrate state-of-the-art results on RuMedBench - Russian medical language understanding benchmark that covers a diverse set of tasks, including text classification, question answering, natural language inference, and named entity recognition.

Key facts. Cited by 6 papers in the map (data through 14 Oct 2026). Builds on 7 of its 7 references that are in the map. First posted on arXiv 8 Apr 2022.

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7 of 7 references.

References · 7

  1. 2018BERT: Pre-training of Deep Bidirectional Transformers for Language Understandingcited by 40,399
  2. 2019RoBERTa: A Robustly Optimized BERT Pretraining Approachcited by 13,372
  3. 2019BioBERT: a pre-trained biomedical language representation model for biomedical text miningcited by 1,947
  4. 2019Publicly Available Clinical BERT Embeddingscited by 1,002
  5. 2019Transfer Learning in Biomedical Natural Language Processing: An Evaluation of BERT and ELMo on Ten Benchmarking Datasetscited by 299
  6. 2019Adaptation of Deep Bidirectional Multilingual Transformers for Russian Languagecited by 109
  7. 2022RuMedBench: A Russian Medical Language Understanding Benchmarkcited by 10

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Cited by year (2026 to 14 Oct)

Citing papers per year: 2023: 1; 2024: 2; 2025: 2; 2026: 1.

6 papers.