  In this paper, we present our submission to the SemEval-2024 Task 8
"Multigenerator, Multidomain, and Multilingual Black-Box Machine-Generated Text
Detection", focusing on the detection of machine-generated texts (MGTs) in
English. Specifically, our approach relies on combining embeddings from the
RoBERTa-base with diversity features and uses a resampled training set. We
score 12th from 124 in the ranking for Subtask A (monolingual track), and our
results show that our approach is generalizable across unseen models and
domains, achieving an accuracy of 0.91.
