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ZENODO
Report . 2026
License: CC BY
Data sources: ZENODO
ZENODO
Report . 2026
License: CC BY
Data sources: Datacite
ZENODO
Report . 2026
License: CC BY
Data sources: Datacite
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Deepfake Detector Robustness Under Social-Media Re-encoding

descriptionPublicationkeyboard_double_arrow_right Report 21 Jun 2026Publisher:Zenodo
Authors: Babalola, Daniel;

doi: 10.5281/zenodo.20781389 , 10.5281/zenodo.20781388

Deepfake Detector Robustness Under Social-Media Re-encoding

Abstract

A two-phase evaluation of fourteen open-source deepfake detectors on an SDXL + InstantID benchmark, with a robustness study against four social-media ingest pipelines. This white paper is written and sponsored by Margen. Go to margensoftware.com to learn more about similar benchmarks.

Keywords

model evaluation, binary classification, deepfake detection, deepfake, stable diffusion

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    popularity
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    influence
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
Green