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Yunlong Mao

2 accepted papers

2025

ObfusLM: Privacy-preserving Language Model Service against Embedding Inversion Attacks

ACL 2025long

As the rapid expansion of Machine Learning as a Service (MLaaS) for language models, concerns over the privacy of client inputs during inference or fine-tuning have correspondingly escalated. Recently, solutions have been proposed to safeguard client privacy by obfuscation techniques. However, the s…

2025

SAP: Privacy-Preserving Fine-Tuning on Language Models with Split-and-Privatize Framework

IJCAI 2025

Pre-trained Language Models (PLM) have enabled a cost-effective approach to handling various downstream applications via Parameter-Efficient-Fine-Tuning (PEFT) techniques. In this context, service providers have introduced a popular fine-tuning-based product service known as Model-as-a-Service (MaaS

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