DCU at SemEval-2023 Task 10: A Comparative Analysis of Encoder-only and Decoder-only Language Models with Insights into Interpretability
Kanishk Verma, Kolawole John Adebayo, Joachim Wagner, Brian P. Davis · 2023
We conduct a comparison of pre-trained encoder-only and decoder-only language models with and without continued pre-training, to detect online sexism.Our fine-tuning-based classifier system achieved the 16 th rank in the SemEval 2023 Shared Task 10 Subtask A that asks to distinguish sexist and non-sexist texts.Additionally, we conduct experiments aimed at enhancing the interpretability of systems designed to detect online sexism.Our findings provide insights into the features and decisionmaking processes underlying our classifier system, thereby contributing to a broader effort to develop explainable AI models to detect online sexism.