PetKaz at SemEval-2024 Task 8: Can Linguistics Capture the Specifics of LLM-generated Text?
Petukhova, Kseniia, Kazakov, Roman, Kochmar, Ekaterina
–arXiv.org Artificial Intelligence
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.
arXiv.org Artificial Intelligence
Apr-8-2024
- Country:
- North America
- Mexico > Mexico City (0.14)
- United States > Michigan (0.14)
- North America
- Genre:
- Research Report > New Finding (0.87)
- Industry:
- Technology: