28 citations · 35 across the 8 of their papers we have counts for
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cs.LG2023★ 5 cited
FlexRound: Learnable Rounding based on Element-wise Division for Post-Training Quantization
Jung Hyun Lee, Jeonghoon Kim, Se Jung Kwon +1
Post-training quantization (PTQ) has been gaining popularity for the deployment of deep neural networks on resource-limited devices since unlike quantization-aware training, neithe…
cs.LG2023★ 28 cited
Memory-Efficient Fine-Tuning of Compressed Large Language Models via sub-4-bit Integer Quantization
Jeonghoon Kim, Jung Hyun Lee, Sungdong Kim +4
Large language models (LLMs) face the challenges in fine-tuning and deployment due to their high memory demands and computational costs. While parameter-efficient fine-tuning (PEFT…