26 citations · 31 across the 4 of their papers we have counts for
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cs.CL2023★ 4 cited
Sparse Fine-tuning for Inference Acceleration of Large Language Models
Eldar Kurtic, Denis Kuznedelev, Elias Frantar +2
We consider the problem of accurate sparse fine-tuning of large language models (LLMs), that is, fine-tuning pretrained LLMs on specialized tasks, while inducing sparsity in their…
cs.CL2023★ 26 cited
SpQR: A Sparse-Quantized Representation for Near-Lossless LLM Weight Compression
Tim Dettmers, Ruslan Svirschevski, Vage Egiazarian +6
Recent advances in large language model (LLM) pretraining have led to high-quality LLMs with impressive abilities. By compressing such LLMs via quantization to 3-4 bits per paramet…