57 citations · 178 across the 16 of their papers we have counts for
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cs.CL2023★ 4 cited
Privacy-Preserving Parameter-Efficient Fine-Tuning for Large Language Model Services
Yansong Li, Zhixing Tan, Paula Branco +1
Parameter-Efficient Fine-Tuning (PEFT) provides a practical way for users to customize Large Language Models (LLMs) with their private data in LLM service scenarios. However, the i…
cs.CL2023★ 9 cited
Black-box Prompt Tuning with Subspace Learning
Yuanhang Zheng, Zhixing Tan, Peng Li +1
Black-box prompt tuning employs derivative-free optimization algorithms to learn prompts within low-dimensional subspaces rather than back-propagating through the network of Large…