Yequan Zhao

QuZO: Quantized Zeroth-Order Fine-Tuning for Large Language Models

Large Language Models (LLMs) are often quantized to lower precision to reduce the memory cost and latency in inference. However, quantization often degrades model performance, thus fine-tuning is required for various downstream tasks. Traditional fine-tuning methods such as stochastic gradient desce