Papers by Cristian Rusu

1 papers
XMAD-Bench: Cross-Domain Multilingual Audio Deepfake Benchmark (2026.findings-eacl)

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Challenge: Recent advances in audio generation led to an increasing number of deepfakes . however, these methods are typically tested in an in-domain setup .
Approach: They propose a large-scale cross-domain audio deepfake benchmark comprising 668.8 hours of real and deepfak speech.
Outcome: The proposed benchmark compares audio deepfake detectors with existing methods in the wild . the results show that the proposed methods perform better in different languages than existing methods .

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