no code implementations • RDSM (COLING) 2020 • Gleb Kuzmin, Daniil Larionov, Dina Pisarevskaya, Ivan Smirnov
In this paper, we trained and compared different models for fake news detection in Russian.
no code implementations • SemEval (NAACL) 2022 • Dina Pisarevskaya, Arkaitz Zubiaga
This paper describes the participation of the team “dina” in the Multilingual News Similarity task at SemEval 2022.
no code implementations • 17 Apr 2022 • Dina Pisarevskaya, Tatiana Shavrina
The General QA field has been developing the methodology referencing the Stanford Question answering dataset (SQuAD) as the significant benchmark.
no code implementations • WS 2019 • Artem Shelmanov, Dina Pisarevskaya, Elena Chistova, Svetlana Toldova, Maria Kobozeva, Ivan Smirnov
Results of the first experimental evaluation of machine learning models trained on Ru-RSTreebank {--} first Russian corpus annotated within RST framework {--} are presented.
no code implementations • WS 2017 • Dina Pisarevskaya
The classification task in the first experiment is solved better by SVMs (rbf kernel) (f-measure 0. 65).
no code implementations • RANLP 2017 • Dina Pisarevskaya, Tatiana Litvinova, Olga Litvinova
The field of automated deception detection in written texts is methodologically challenging.