Qwen it detect machine-generated text?
Marchitan, Teodor-George, Creanga, Claudiu, Dinu, Liviu P.
–arXiv.org Artificial Intelligence
This paper describes the approach of the Unibuc - NLP team in tackling the Coling 2025 GenAI Workshop, Task 1: Binary Multilingual Machine-Generated Text Detection. We explored both masked language models and causal models. For Subtask A, our best model achieved first-place out of 36 teams when looking at F1 Micro (Auxiliary Score) of 0.8333, and second-place when looking at F1 Macro (Main Score) of 0.8301
arXiv.org Artificial Intelligence
Jan-16-2025
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