Dataset Card for OpenFake OpenFake is a dataset and benchmark for detecting AI generated images, with a focus on politically and socially salient content where misinformation risk is highest. It pairs real photographs with synthetic counterparts produced by a wide range of frontier proprietary generators, open source diffusion models, and community fine tunes. A separate in the wild test set is sourced from Reddit to evaluate detector performance on naturally circulated synthetic media. Versions This is the v2 release. The original v1 release remains accessible at the v1.0 tag: What changed in v2: New real image sources (Pexels added to training; DOCCI and ImageNet used for OOD test reals) Many new generators including frontier proprietary models (nano banana family, GPT Image 1.5 and 2.0) and recent open source releases (Flux.2, Z Image, HiDream variants, Chroma, etc.) Large addition of community fine tunes and LoRAs sourced from Civitai, including video generator outputs Restructured splits with a held out OOD model test set and a separate in the wild Reddit test config Standardized schema across all splits and configs A detailed changelog is at the bottom of this card. Configura…
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