Abstract: Quantization has become a key method for enabling deep learning (DL) inference on resource-constrained embedded systems. As the demand for privacy-preserving, low-latency, and ...
Abstract: Federated learning (FL) with parameter-efficient fine-tuning (PEFT) methods, such as Low-Rank Adaptation (LoRA), offers a privacy-preserving solution for fine-tuning large language models ...
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