The proposed PP-ZSL framework combines anonymization, zero-shot LLM inference, RAG, and validation for privacy-preserving customer support, but lacks any empirical validation to support its claims.
In customer support, this often involves processing sensitive information, such as personally identifiable informa tion (PII), financial details, or contractual agreements
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Privacy-Preserving Customer Support: A Framework for Secure and Scalable Interactions
The proposed PP-ZSL framework combines anonymization, zero-shot LLM inference, RAG, and validation for privacy-preserving customer support, but lacks any empirical validation to support its claims.