Sergey Senichev

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2025

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Gradient Flush at Slavic NLP 2025 Task: Leveraging Slavic BERT and Translation for Persuasion Techniques Classification
Sergey Senichev | Aleksandr Boriskin | Nikita Krayko | Daria Galimzianova
Proceedings of the 10th Workshop on Slavic Natural Language Processing (Slavic NLP 2025)

The task of persuasion techniques detection is limited by several challenges, such as insufficient training data and ambiguity in labels. In this paper, we describe a solution for the Slavic NLP 2025 Shared Task. It utilizes multilingual XLM-RoBERTa, that was trained on 100 various languages, and Slavic BERT, a model fine-tuned on four languages of the Slavic group. We suggest to augment the training dataset with related data from previous shared tasks, as well as some automatic translations from English and German. The resulting solutions are ranked among the top 3 for Russian in the Subtask 1 and for all languages in the Subtask 2. We release the code for our solution - https://github.com/ssenichev/ACL_SlavicNLP2025.
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