MasonTigers at SemEval-2024 Task 8: Performance Analysis of Transformer-based Models on Machine-Generated Text Detection

Sadiya Sayara Chowdhury Puspo, Nishat Raihan, Dhiman Goswami, Al Nahian Bin Emran, Amrita Ganguly, Özlem Uzuner

Abstract: This paper presents the MasonTigers entryto the SemEval-2024 Task 8 - Multigenerator, Multidomain, and Multilingual BlackBox Machine-Generated Text Detection. Thetask encompasses Binary Human-Written vs.Machine-Generated Text Classification (TrackA), Multi-Way Machine-Generated Text Classification (Track B), and Human-Machine MixedText Detection (Track C). Our best performing approaches utilize mainly the ensemble ofdiscriminator transformer models along withsentence transformer and statistical machinelearning approaches in specific cases. Moreover, Zero shot prompting and fine-tuning ofFLAN-T5 are used for Track A and B.