GenAI Content Detection Task 1: English and Multilingual Machine-Generated Text Detection: AI vs. Human
Yuxia Wang, Artem Shelmanov, Jonibek Mansurov, Akim Tsvigun, Vladislav, Mikhailov, Rui Xing, Zhuohan Xie, Jiahui Geng, Giovanni Puccetti, Ekaterina, Artemova, Jinyan Su, Minh Ngoc Ta, Mervat Abassy, Kareem Ashraf Elozeiri,, Saad El Dine Ahmed El Etter, Maiya Goloburda
TL;DR
This paper introduces a shared task on detecting machine-generated text in English and multilingual contexts, analyzing system performances and fostering advancements in AI-generated content detection.
Contribution
It presents the first comprehensive shared task for multilingual machine-generated text detection, including data, system descriptions, and performance analysis.
Findings
High variability in system performance
Multilingual detection remains challenging
Many teams participated, indicating strong community interest
Abstract
We present the GenAI Content Detection Task~1 -- a shared task on binary machine generated text detection, conducted as a part of the GenAI workshop at COLING 2025. The task consists of two subtasks: Monolingual (English) and Multilingual. The shared task attracted many participants: 36 teams made official submissions to the Monolingual subtask during the test phase and 26 teams -- to the Multilingual. We provide a comprehensive overview of the data, a summary of the results -- including system rankings and performance scores -- detailed descriptions of the participating systems, and an in-depth analysis of submissions. https://github.com/mbzuai-nlp/COLING-2025-Workshop-on-MGT-Detection-Task1
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Taxonomy
TopicsNatural Language Processing Techniques · Topic Modeling