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DeepSafe Wild Test Set

A held-out set used to check DeepSafe against media it was never tuned on.

What is in it

Source Files Type
DeepAction v1 1,966 AI-generated video across several generators
Gary Stafford audio 1,011 synthetic and real speech
Defactify 17 mixed

Why it is separate

The main evaluation dataset trained the ensemble meta-learners. Measuring on it alone would report in-distribution performance and overstate what the detectors do in the wild. This set exists to be the part nothing was fitted to.

The gap between the two is the finding: across 411 generators the ensemble catches 66% of fakes overall, and only 7% of Sora video. Full results in BENCHMARK.md.

Takedown

If you hold rights to any included material, open an issue at https://github.com/deepsafehq/deepsafe-bench. Removal within 48 hours.

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