AI Networking Cookbook: Practical recipes for AI-assisted network automation and development
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This paper introduces the Sensitive Entity Alias Generator (SEAG), a privacy-preserving framework that empowers users to utilize powerful third-party generators without disclosing sensitive information and demonstrates the success of the SEAG framework.
Results on the UC Merced (UCM) and NWPU benchmarks indicate that SE-CLIP significantly outperforms existing semi-supervised approaches and provides a viable solution for adapting VLMs to the remote sensing domain with minimal human intervention.
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