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 • 4 Jul 2023 • Nikita Remnev, Sergei Obiedkov, Ekaterina Rakhilina, Ivan Smirnov, Anastasia Vyrenkova
Grammatical error correction is one of the fundamental tasks in Natural Language Processing.
1 code implementation • 2 Jun 2023 • Elena Chistova, Ivan Smirnov
Our best model employing rhetorical distance between mentions has ranked 1st on the development set (74. 6% F1) and 2nd on the test set (73. 3% F1) of the Shared Task.
no code implementations • 26 Apr 2023 • Ivan Smirnov, Camelia Oprea, Markus Strohmaier
We find that toxic comments consistently reduce the activity of editors, leading to an estimated loss of 0. 5-2 active days per user in the short term.
1 code implementation • 8 Feb 2021 • Georg Ahnert, Ivan Smirnov, Florian Lemmerich, Claudia Wagner, Markus Strohmaier
The FairCeptron framework is an approach for studying perceptions of fairness in algorithmic decision making such as in ranking or classification.
no code implementations • 2 Nov 2020 • Charles Auguste, Sean Malory, Ivan Smirnov
Throughout the report, we mostly focus on the implementation of our methods that we made for the LightGBM library, even though they are general and could be implemented in any regression or classification tree.
1 code implementation • 13 Jun 2020 • Ivan Smirnov, Florian Lemmerich, Markus Strohmaier
The most common approach to this issue is debiasing, for example via the introduction of quotas that ensure proportional representation of groups with respect to a certain, often binary attribute.
no code implementations • 1 Dec 2019 • Ivan Smirnov
We build a model to predict academic performance from users' posts on VK and then apply it to a different context.
no code implementations • RANLP 2019 • Daniil Larionov, Artem Shelmanov, Elena Chistova, Ivan Smirnov
We build the first full pipeline for semantic role labelling of Russian texts.
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.