most citedQLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

11 citations · 11 across the 2 of their papers we have counts for

collaborators

2 papers

cs.CV2024

HQOD: Harmonious Quantization for Object Detection

Long Huang, Zhiwei Dong, Song-Lu Chen +4

Task inharmony problem commonly occurs in modern object detectors, leading to inconsistent qualities between classification and regression tasks. The predicted boxes with high clas…

cs.CL2023★ 11 cited

QLLM: Accurate and Efficient Low-Bitwidth Quantization for Large Language Models

Jing Liu, Ruihao Gong, Xiuying Wei +3

Large Language Models (LLMs) excel in NLP, but their demands hinder their widespread deployment. While Quantization-Aware Training (QAT) offers a solution, its extensive training c…