Papers by Zhuotao Liu

1 papers
A Middle Path for On-Premises LLM Deployment: Preserving Privacy Without Sacrificing Model Confidentiality (2025.emnlp-main)

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Challenge: Privacy-sensitive users require deploying large language models within their own infrastructure (on-premises) vulnerabilities in local environments can lead to unauthorized access and potential model theft.
Approach: They propose a framework that secures a few bottom layers in a secure environment . they propose metric to optimize trade-off between protection and customization flexibility .
Outcome: The proposed framework outperforms baselines on five models with 1.3B to 70B parameters.

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