To what extent does the integration of secure multi-party computation protocols affect the zero-shot text clas

Abstract

Abstract: Transformer models (e.g., Bert and GPT) have shown their dominance in machine learning tasks. Many cloud companies have begun to provide services based on Transformer models, examples include translation and text-speech conversion. However, such a service inevitably requires access to the client's data, which might contain sensitive information. Theoretically, running the services under secure multi-party computation (MPC) could protect clients' privacy. However, current MPC frameworks are still limited in terms of model performance, efficiency, deployment, and functionality, especially when f

Research Question

To what extent does the integration of secure multi-party computation protocols affect the zero-shot text classification accuracy on the SetFit/llm-benchmark-suite?

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