New EUPE method enables efficient AI models for edge devices by distilling knowledge from multiple vision encoders into a single compact model

EUPE (Efficient Universal Perception Encoder) solves the challenge of running AI on resource-limited smart edge devices while handling multiple tasks simultaneously

The approach distills knowledge from multiple domain-expert foundation vision encoders rather than directly scaling down from multiple teachers

Key innovation: scaling up to a large proxy teacher first, then scaling down to a single efficient encoder produces better results than previous agglomerative methods

EUPE achieves equal or better performance than individual domain experts of the same size across diverse task domains