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Found 11 papers, 3 papers with code
Fake news detection for the Russian language
In this paper, we trained and compared different models for fake news detection in Russian.
A Language Model for Grammatical Error Correction in L2 Russian
Grammatical error correction is one of the fundamental tasks in Natural Language Processing.
Light Coreference Resolution for Russian with Hierarchical Discourse Features
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.
Toxic comments reduce the activity of volunteer editors on Wikipedia
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.
The FairCeptron: A Framework for Measuring Human Perceptions of Algorithmic Fairness
The FairCeptron framework is an approach for studying perceptions of fairness in algorithmic decision making such as in ranking or classification.
A better method to enforce monotonic constraints in regression and classification trees
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.
Quota-based debiasing can decrease representation of already underrepresented groups
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.
Generalizable prediction of academic performance from short texts on social media
We build a model to predict academic performance from users' posts on VK and then apply it to a different context.
Semantic Role Labeling with Pretrained Language Models for Known and Unknown Predicates
We build the first full pipeline for semantic role labelling of Russian texts.
Towards the Data-driven System for Rhetorical Parsing of Russian Texts
Results of the first experimental evaluation of machine learning models trained on Ru-RSTreebank {--} first Russian corpus annotated within RST framework {--} are presented.
