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AMXFP4: Taming Activation Outliers with Asymmetric Microscaling Floating-Point for 4-bit LLM Inference
Scaling Large Language Models (LLMs) with extended context lengths has increased the need for efficient low-bit quantization to manage their substantial computational demands.
The Sooner The Better: Investigating Structure of Early Winning Lottery Tickets
In the case of ResNet50 on ImageNet, this comes to the winning ticket of 75:02% Top-1 accuracy at 80% pruning rate in only 22% of the total epochs for iterative pruning.
Sparse-Complementary Convolution for Efficient Model Utilization on CNNs
By simply replacing the convolution of a CNN with our sparse-complementary convolution, at the same FLOPs and parameters, we can improve top-1 accuracy on ImageNet by 0. 33% and 0. 18% for ResNet-101 and ResNet-152, respectively.
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