PACZero achieves zero mutual information privacy for LLM fine-tuning via sign-quantized zeroth-order gradients, delivering near-non-private accuracy on SST-2 and SQuAD at I=0.
Smooth sensitivity and sampling in private data analysis
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PACZero: PAC-Private Fine-Tuning of Language Models via Sign Quantization
PACZero achieves zero mutual information privacy for LLM fine-tuning via sign-quantized zeroth-order gradients, delivering near-non-private accuracy on SST-2 and SQuAD at I=0.