Edge 453: Distillation Across Different Modalities
Was this email forwarded to you? Sign up here Edge 453: Distillation Across Different ModalitiesCross modal distillation is one of the most interesting distillation methods of the new generation.
In this issue:
💡 ML Concept of the Day: Cross Modal DistillationMost of the distillation techniques explored during the course of this series have been focused on a single modality. However, the question of having distillation models in which the teacher transfers knowledge from one modality to a student primary built for another modality is an interesting one. Cross-modal distillation enables the transfer of knowledge between models operating on different data modalities. This approach extends the concept of knowledge distillation, originally proposed for model compression, to scenarios where the teacher and student models process fundamentally different types of input data. The core idea is to leverage the rich representations learned by a model in one modality (the teacher) to guide the learning process of a model in another modality (the student), even when paired data is scarce or unavailable... Subscribe to TheSequence to unlock the rest.Become a paying subscriber of TheSequence to get access to this post and other subscriber-only content. A subscription gets you:
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