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Open-set attribution can now effectively identify and cluster unknown face generators, achieving 71.25% balanced accuracy in real-world scenarios where new models continuously emerge.
Supervised learning models can reliably outperform widely-used commercial AI text detectors, even across different languages and specialized domains like mental health.
