2023/06/02 by Mykola Trokhymovych, Muniza Aslam, Trokhymovych, Mykola +7 · 1 citation
Biochemistry, Genetics and Molecular Biology · Social Sciences · #Cancer-related gene regulation #FOS: Computer and information sciences #Machine Learning (cs.LG) #Protein Degradation and Inhibitors #Wikis in Education and Collaboration
paper · pdf · doi:10.48550/arxiv.2306.01650
openalex publication_date 2023/06/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
This paper presents a novel design of the system aimed at supporting the Wikipedia community in addressing vandalism on the platform. To achieve this, we collected a massive dataset of 47 languages, and applied advanced filtering and feature engineering techniques, including multilingual masked language modeling to build the training dataset from human-generated data. The performance of the system was evaluated through comparison with the one used in production in Wikipedia, known as ORES. Our research results in a significant increase in the number of languages covered, making Wikipedia patrolling more efficient to a wider range of communities. Furthermore, our model outperforms ORES, ensuring that the results provided are not only more accurate but also less biased against certain groups of contributors.