This paper presents presents three distinct systems developed for the M-DAIGT shared task on detecting AI generated content in news articles and academic abstracts. The systems includes: (1) A fine-tuned RoBERTa-base classifier, (2) A classical TF-IDF + Support Vector Machine (SVM) classifier , and (3) An Innovative ensemble model named Candace, leveraging probabilistic features extracted from multiple Llama-3.2 models processed by a customTransformer encoder.The RoBERTa-based system emerged as the most performant, achieving near-perfect results on both development and test sets.
@article{arxiv.2509.00623,
title = {A Multi-Strategy Approach for AI-Generated Text Detection},
author = {Ali Zain and Sareem Farooqui and Muhammad Rafi},
journal= {arXiv preprint arXiv:2509.00623},
year = {2025}
}