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X-WR-CALNAME:GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
X-ORIGINAL-URL:https://www.greyc.fr
X-WR-CALDESC:évènements pour GREYC UMR CNRS 6072 - Groupe de Recherche en Informatique, Image, et Instrumentation de Caen
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TZID:Europe/Paris
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DTSTART:20250330T010000
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DTSTART:20251026T010000
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DTSTART;TZID=Europe/Paris:20250703T140000
DTEND;TZID=Europe/Paris:20250703T150000
DTSTAMP:20260419T074545
CREATED:20250519T083955Z
LAST-MODIFIED:20250519T083955Z
UID:11863-1751551200-1751554800@www.greyc.fr
SUMMARY:Séminaire Image : "Toward Frugal Multimodal Models: Leveraging Prior Knowledge for Efficient Learning"\,  Bilal Faye
DESCRIPTION:Nous aurons le plaisir d’écouter Bilal Faye\, doctorant au LIPN : Laboratoire d’Informatique de Paris Nord – Université Sorbonne Paris Nord.\nIl donnera un séminaire IMAGE le jeudi 3 juillet 2025 à 14h en salle de séminaire F-200. \nTitre : « Toward Frugal Multimodal Models: Leveraging Prior Knowledge for Efficient Learning » \nRésumé :\nIncorporating prior knowledge can significantly reduce the need for large-scale training data and heavy parameterization\, while preserving high performance. Within a multimodal framework\, this principle enables the design of lightweight and efficient models. Two key examples illustrate this idea: OneEncoder\, a frugal multimodal encoder based on contrastive learning that aligns diverse modalities (text\, image\, audio\, video) without relying on massive paired datasets; and LightMDETR\, a streamlined adaptation of the MDETR model for open-vocabulary object detection\, which enables efficient generalization to unseen categories with reduced computational demands.
URL:https://www.greyc.fr/event/seminaire-image-toward-frugal-multimodal-models-leveraging-prior-knowledge-for-efficient-learning-bilal-faye/
LOCATION:ENSICAEN – Batiment F – Salle F-200\, 6 Bd Maréchal Juin\, Caen\, 14050\, France
CATEGORIES:General,Image,News,Seminaire Image
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