KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual
  Machine-Generated Text Detection
Michal Spiegel Dominik Macko
SemEval-2024 Task 8 is focused on multigenerator, multidomain, and
multilingual black-box machine-generated text detection. Such a detection is
important for preventing a potential misuse of large language models (LLMs),
the newest of which are very capable in generating multilingual human-like
texts. We have coped with this task in multiple ways, utilizing language
identification and parameter-efficient fine-tuning of smaller LLMs for text
classification. We have further used the per-language classification-threshold
calibration to uniquely combine fine-tuned models predictions with statistical
detection metrics to improve generalization of the system detection
performance. Our submitted method achieved competitive results, ranking at the
fourth place, just under 1 percentage point behind the winner.