17 citations · 37 across the 23 of their papers we have counts for
6 papers · 1 filter
Investigating self-supervised representations for audio-visual deepfake detection
Dragos-Alexandru Boldisor, Stefan Smeu, Dan Oneata +1
Self-supervised representations excel at many vision and speech tasks, but their potential for audio-visual deepfake detection remains underexplored. Unlike prior work that uses th…
Not All Splits Are Equal: Rethinking Attribute Generalization Across Unrelated Categories
Liviu Nicolae Fircă, Antonio Bărbălau, Dan Oneata +1
Can models generalize attribute knowledge across semantically and perceptually dissimilar categories? While prior work has addressed attribute prediction within narrow taxonomic or…
The mutual exclusivity bias of bilingual visually grounded speech models
Dan Oneata, Leanne Nortje, Yevgen Matusevych +1
Mutual exclusivity (ME) is a strategy where a novel word is associated with a novel object rather than a familiar one, facilitating language learning in children. Recent work has f…
Seeing What Tastes Good: Revisiting Multimodal Distributional Semantics in the Billion Parameter Era
Dan Oneata, Desmond Elliott, Stella Frank
Human learning and conceptual representation is grounded in sensorimotor experience, in contrast to state-of-the-art foundation models. In this paper, we investigate how well such…
Unmasking real-world audio deepfakes: A data-centric approach
David Combei, Adriana Stan, Dan Oneata +2
The growing prevalence of real-world deepfakes presents a critical challenge for existing detection systems, which are often evaluated on datasets collected just for scientific pur…
TADA: Training-free Attribution and Out-of-Domain Detection of Audio Deepfakes
Adriana Stan, David Combei, Dan Oneata +1
Deepfake detection has gained significant attention across audio, text, and image modalities, with high accuracy in distinguishing real from fake. However, identifying the exact so…