most citedINT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation

4 citations · 4 across the 2 of their papers we have counts for

collaborators

2 papers

cs.AI2025

FlexQuant: Elastic Quantization Framework for Locally Hosted LLM on Edge Devices

Yuji Chai, Mujin Kwen, David Brooks +1

Deploying LLMs on edge devices presents serious technical challenges. Memory elasticity is crucial for edge devices with unified memory, where memory is shared and fluctuates dynam…

cs.CL2023★ 4 cited

INT2.1: Towards Fine-Tunable Quantized Large Language Models with Error Correction through Low-Rank Adaptation

Yuji Chai, John Gkountouras, Glenn G. Ko +2

We introduce a method that dramatically reduces fine-tuning VRAM requirements and rectifies quantization errors in quantized Large Language Models. First, we develop an extremely m…