Sentinel-Guided Zero-Shot Learning: A Collaborative Paradigm without Real Data Exposure

arXiv:2403.09363v1 Announce Type: new
Abstract: With increasing concerns over data privacy and model copyrights, especially in the context of collaborations between AI service providers and data owners, an innovative SG-ZSL paradigm is proposed in this work. SG-ZSL is designed to foster efficient collaboration without the need to exchange models or sensitive data. It consists of a teacher model, a student model and a generator that links both model entities. The teacher model serves as a sentinel on behalf of the …

abstract arxiv collaboration collaborations collaborative concerns context copyrights cs.cv data data privacy paradigm privacy real data sentinel service service providers type work zero-shot