7 citations · 9 across the 3 of their papers we have counts for
5 papers
Detecting Generated Scientific Papers using an Ensemble of Transformer Models
Anna Glazkova, Maksim Glazkov
The paper describes neural models developed for the DAGPap22 shared task hosted at the Third Workshop on Scholarly Document Processing. This shared task targets the automatic detec…
MIPT-NSU-UTMN at SemEval-2021 Task 5: Ensembling Learning with Pre-trained Language Models for Toxic Spans Detection
Mikhail Kotyushev, Anna Glazkova, Dmitry Morozov
This paper describes our system for SemEval-2021 Task 5 on Toxic Spans Detection. We developed ensemble models using BERT-based neural architectures and post-processing to combine…
g2tmn at Constraint@AAAI2021: Exploiting CT-BERT and Ensembling Learning for COVID-19 Fake News Detection
Anna Glazkova, Maksim Glazkov, Timofey Trifonov
The COVID-19 pandemic has had a huge impact on various areas of human life. Hence, the coronavirus pandemic and its consequences are being actively discussed on social media. Howev…
UTMN at SemEval-2020 Task 11: A Kitchen Solution to Automatic Propaganda Detection
Elena Mikhalkova, Nadezhda Ganzherli, Anna Glazkova +1
The article describes a fast solution to propaganda detection at SemEval-2020 Task 11, based onfeature adjustment. We use per-token vectorization of features and a simple Logistic…
A Comparison of Synthetic Oversampling Methods for Multi-class Text Classification
Anna Glazkova
The authors compared oversampling methods for the problem of multi-class topic classification. The SMOTE algorithm underlies one of the most popular oversampling methods. It consis…