8 citations · 13 across the 7 of their papers we have counts for
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cs.CL2024★ 1 cited
SLEB: Streamlining LLMs through Redundancy Verification and Elimination of Transformer Blocks
Jiwon Song, Kyungseok Oh, Taesu Kim +3
Large language models (LLMs) have proven to be highly effective across various natural language processing tasks. However, their large number of parameters poses significant challe…
cs.CL2023★ 8 cited
OWQ: Outlier-Aware Weight Quantization for Efficient Fine-Tuning and Inference of Large Language Models
Changhun Lee, Jungyu Jin, Taesu Kim +2
Large language models (LLMs) with hundreds of billions of parameters require powerful server-grade GPUs for inference, limiting their practical deployment. To address this challeng…