2025
ACL
ACL 2025
Gradient Flush at Slavic NLP 2025 Task: Leveraging Slavic BERT and Translation for Persuasion Techniques Classification
Abstract
AbstractThe 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.
🌉
Interdisciplinary Bridge
— Artificial Intelligence and Deep Learning and Machine Learning and Natural Language Processing
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Cross-Pollinator
— Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Healthcare & Medicine, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning, Robotics, Security & Privacy, Speech & Audio
Authors
Topics
Artificial Intelligence > Learning Paradigms > Transfer Learning
Machine Learning > Core Methods > Classification
Deep Learning > Architectures > Transformers
Natural Language Processing > Applications > Text Classification
Natural Language Processing > Resources & Methods > Multilingual NLP
Machine Learning > Learning Types > Few-Shot Learning
Machine Learning > Learning Types > Transfer Learning
Deep Learning > Techniques > Transfer Learning
Deep Learning > Learning Types > Transfer Learning
Deep Learning > Models > Multi-Modal Learning