Deepfake Lab
1 February 01, 2026

Além do Desempenho: Um Estudo da Confiabilidade de Detectores de Deepfakes

Evidence Level
2/5

How much verified proof exists for this claim

One strong evidence source: arxiv

Mystery Factor
2/5

How intriguing or unexplained this claim is

The claim presents some gaps in the story, particularly regarding the comprehensive evaluation methods for deepfake detection, indicating an emerging narrative with minor uncertainties about the effectiveness and reliability of these techniques.

Deepfakes are synthetic media generated by artificial intelligence, with positive applications in education and creativity, but also serious negative impacts such as fraud, misinformation, and privacy violations. Although detection techniques have advanced, comprehensive evaluation methods that go beyond classification performance remain lacking. This paper proposes a reliability assessment framework based on four pillars: transferability, robustness, interpretability, and computational effic...

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