Published August 11, 2024 | Version v1
Conference paper Open

KInIT at SemEval-2024 Task 8: Fine-tuned LLMs for Multilingual Machine-Generated Text Detection

  • 1. Kempelen Institute of Intelligent Technologies
  • 2. ROR icon Masaryk University

Description

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.

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Additional details

Funding

AI-CODE – AI-CODE - AI services for COntinuous trust in emerging Digital Environments 101135437
European Commission
VIGILANT – Vital IntelliGence to Investigate ILlegAl DisiNformaTion 101073921
European Commission