AI-Monitors at GenAI Detection Task 1: Fast and Scalable Machine Generated Text Detection

Azad Singh, Vishnu Tripathi, Ravindra Kumar Pandey, Pragyanand Saho, Prakhar Joshi, Neel Mani, Richa Alagh, Pallaw Mishra, Piyush Arora


Abstract
We describe the work carried out by our team, AI-Monitors, on the Binary Multilingual Machine-Generated Text Detection (Human vs. Machine) task at COLING 2025. This task aims to determine whether a given text is generated by a machine or authored by a human. We propose a lightweight, simple, and scalable approach using encoder models such as RoBERTa and XLM-R We provide an in-depth analysis based on our experiments. Our study found that carefully exploring fine-tuned parameters such as i) no. of training epochs, ii) maximum input size, iii) handling class imbalance etc., plays an important role in building an effective system to achieve good results and can significantly impact the underlying tasks. We found the optimum setting of these parameters can lead to a difference of about 5-6% in absolute terms for measure such as accuracy and F1 measure. The paper presents crucial insights into optimal parameter selection for fine-tuning RoBERTa and XLM-R based models to detect whether a given text is generated by a machine or a human.
Anthology ID:
2025.genaidetect-1.25
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:
230–235
Language:
URL:
https://aclanthology.org/2025.genaidetect-1.25/
DOI:
Bibkey:
Cite (ACL):
Azad Singh, Vishnu Tripathi, Ravindra Kumar Pandey, Pragyanand Saho, Prakhar Joshi, Neel Mani, Richa Alagh, Pallaw Mishra, and Piyush Arora. 2025. AI-Monitors at GenAI Detection Task 1: Fast and Scalable Machine Generated Text Detection. In Proceedings of the 1stWorkshop on GenAI Content Detection (GenAIDetect), pages 230–235, Abu Dhabi, UAE. International Conference on Computational Linguistics.
Cite (Informal):
AI-Monitors at GenAI Detection Task 1: Fast and Scalable Machine Generated Text Detection (Singh et al., GenAIDetect 2025)
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PDF:
https://aclanthology.org/2025.genaidetect-1.25.pdf