5 papers
Russian SuperGLUE 1.1: Revising the Lessons not Learned by Russian NLP models
Alena Fenogenova, Maria Tikhonova, Vladislav Mikhailov +6
In the last year, new neural architectures and multilingual pre-trained models have been released for Russian, which led to performance evaluation problems across a range of langua…
Morph Call: Probing Morphosyntactic Content of Multilingual Transformers
Vladislav Mikhailov, Oleg Serikov, Ekaterina Artemova
The outstanding performance of transformer-based language models on a great variety of NLP and NLU tasks has stimulated interest in exploring their inner workings. Recent research…
MOROCCO: Model Resource Comparison Framework
Valentin Malykh, Alexander Kukushkin, Ekaterina Artemova +3
The new generation of pre-trained NLP models push the SOTA to the new limits, but at the cost of computational resources, to the point that their use in real production environment…
RuSentEval: Linguistic Source, Encoder Force!
Vladislav Mikhailov, Ekaterina Taktasheva, Elina Sigdel +1
The success of pre-trained transformer language models has brought a great deal of interest on how these models work, and what they learn about language. However, prior research in…
Domain-Transferable Method for Named Entity Recognition Task
Vladislav Mikhailov, Tatiana Shavrina
Named Entity Recognition (NER) is a fundamental task in the fields of natural language processing and information extraction. NER has been widely used as a standalone tool or an es…