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cs.CL2025
Training-Free Activation Sparsity in Large Language Models
James Liu, Pragaash Ponnusamy, Tianle Cai +3
Activation sparsity can enable practical inference speedups in large language models (LLMs) by reducing the compute and memory-movement required for matrix multiplications during t…
cs.CL2024
LQ-LoRA: Low-rank Plus Quantized Matrix Decomposition for Efficient Language Model Finetuning
Han Guo, Philip Greengard, Eric P. Xing +1
We propose a simple approach for memory-efficient adaptation of pretrained language models. Our approach uses an iterative algorithm to decompose each pretrained matrix into a high…