Qwen it detect machine-generated text?
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Abstract (arXiv)
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
Key facts. No citing papers in the map yet (data through 14 Oct 2026). First posted on arXiv 16 Jan 2025.
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