49 citations · 92 across the 8 of their papers we have counts for
7 papers · 1 filter
A Family of Pretrained Transformer Language Models for Russian
Dmitry Zmitrovich, Alexander Abramov, Andrey Kalmykov +10
Transformer language models (LMs) are fundamental to NLP research methodologies and applications in various languages. However, developing such models specifically for the Russian…
Findings of the The RuATD Shared Task 2022 on Artificial Text Detection in Russian
Tatiana Shamardina, Vladislav Mikhailov, Daniil Chernianskii +7
We present the shared task on artificial text detection in Russian, which is organized as a part of the Dialogue Evaluation initiative, held in 2022. The shared task dataset includ…
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…
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…
RussianSuperGLUE: A Russian Language Understanding Evaluation Benchmark
Tatiana Shavrina, Alena Fenogenova, Anton Emelyanov +7
In this paper, we introduce an advanced Russian general language understanding evaluation benchmark -- RussianGLUE. Recent advances in the field of universal language models and tr…
DaNetQA: a yes/no Question Answering Dataset for the Russian Language
Taisia Glushkova, Alexey Machnev, Alena Fenogenova +3
DaNetQA, a new question-answering corpus, follows (Clark et. al, 2019) design: it comprises natural yes/no questions. Each question is paired with a paragraph from Wikipedia and an…
AGRR-2019: A Corpus for Gapping Resolution in Russian
Maria Ponomareva, Kira Droganova, Ivan Smurov +1
This paper provides a comprehensive overview of the gapping dataset for Russian that consists of 7.5k sentences with gapping (as well as 15k relevant negative sentences) and compri…