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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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