CIC-NLP at GenAI Detection Task 1: Advancing Multilingual Machine-Generated Text Detection

Tolulope Olalekan Abiola, Tewodros Achamaleh Bizuneh, Fatima Uroosa, Nida Hafeez, Grigori Sidorov, Olga Kolesnikova, Olumide Ebenezer Ojo


Abstract
Machine-written texts are gradually becoming indistinguishable from human-generated texts, leading to the need to use sophisticated methods to detect them. Team CIC-NLP presents work in the Gen-AI Content Detection Task 1 at COLING 2025 Workshop: the focus of our work is on Subtask B of Task 1, which is the classification of text written by machines and human authors, with particular attention paid to identifying multilingual binary classification problem. Usng mBERT, we addressed the binary classification task using the dataset provided by the GenAI Detection Task team. mBERT acchieved a macro-average F1-score of 0.72 as well as an accuracy score of 0.73.
Anthology ID:
2025.genaidetect-1.28
Volume:
Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect)
Month:
January
Year:
2025
Address:
Abu Dhabi, UAE
Editors:
Firoj Alam, Preslav Nakov, Nizar Habash, Iryna Gurevych, Shammur Chowdhury, Artem Shelmanov, Yuxia Wang, Ekaterina Artemova, Mucahid Kutlu, George Mikros
Venues:
GenAIDetect | WS
SIG:
Publisher:
International Conference on Computational Linguistics
Note:
Pages:
262–270
Language:
URL:
https://aclanthology.org/2025.genaidetect-1.28/
DOI:
Bibkey:
Cite (ACL):
Tolulope Olalekan Abiola, Tewodros Achamaleh Bizuneh, Fatima Uroosa, Nida Hafeez, Grigori Sidorov, Olga Kolesnikova, and Olumide Ebenezer Ojo. 2025. CIC-NLP at GenAI Detection Task 1: Advancing Multilingual Machine-Generated Text Detection. In Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect), pages 262–270, Abu Dhabi, UAE. International Conference on Computational Linguistics.
Cite (Informal):
CIC-NLP at GenAI Detection Task 1: Advancing Multilingual Machine-Generated Text Detection (Abiola et al., GenAIDetect 2025)
Copy Citation:
PDF:
https://aclanthology.org/2025.genaidetect-1.28.pdf
Optionalsupplementarymaterial:
 2025.genaidetect-1.28.OptionalSupplementaryMaterial.zip