A Multi-Strategy Approach for AI-Generated Text Detection

• URL: http://arxiv.org/abs/2509.00623v1
• Date: Sat, 30 Aug 2025 22:37:35 GMT
• Title: A Multi-Strategy Approach for AI-Generated Text Detection
• Authors: Ali Zain, Sareem Farooqui, Muhammad Rafi,
• Abstract summary: This paper presents three distinct systems developed for the M-DAIGT shared task on detecting AI generated content in news articles and academic abstracts.<n>The RoBERTa-based system emerged as the most performant, achieving near-perfect results on both development and test sets.
• Score: 0.5735035463793009
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: 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.

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