20 citations · 23 across the 3 of their papers we have counts for
3 papers
cs.CL2023★ 20 cited
RPTQ: Reorder-based Post-training Quantization for Large Language Models
Zhihang Yuan, Lin Niu, Jiawei Liu +7
Large-scale language models (LLMs) have demonstrated impressive performance, but their deployment presents challenges due to their significant memory usage. This issue can be allev…
cs.CV2023★ 2 cited
Improving Post-Training Quantization on Object Detection with Task Loss-Guided Lp Metric
Lin Niu, Jiawei Liu, Zhihang Yuan +3
Efficient inference for object detection networks is a major challenge on edge devices. Post-Training Quantization (PTQ), which transforms a full-precision model into low bit-width…
cs.CV2022★ 1 cited
Improve Ranking Correlation of Super-net through Training Scheme from One-shot NAS to Few-shot NAS
Jiawei Liu, Kaiyu Zhang, Weitai Hu +1
The algorithms of one-shot neural architecture search(NAS) have been widely used to reduce computation consumption. However, because of the interference among the subnets in which…