167 citations · 189 across the 13 of their papers we have counts for
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cs.LG2023
Efficient Stitchable Task Adaptation
Haoyu He, Zizheng Pan, Jing Liu +2
The paradigm of pre-training and fine-tuning has laid the foundation for deploying deep learning models. However, most fine-tuning methods are designed to meet a specific resource…
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…