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VGGSounder: Audio-Visual Evaluations for Foundation Models

Fuente: arXiv

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Détails bibliographiques
Auteurs principaux:	Zverev, Daniil, Wiedemer, Thaddäus, Prabhu, Ameya, Bethge, Matthias, Brendel, Wieland, Koepke, A. Sophia
Format:	Preprint
Publié:	2025
Sujets:	Multimedia Artificial Intelligence Computer Vision and Pattern Recognition Sound Audio and Speech Processing
Accès en ligne:	Acceder al recurso
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