4 citations · 12 across the 12 of their papers we have counts for
3 papers · 1 filter
Squeeze10-LLM: Squeezing LLMs' Weights by 10 Times via a Staged Mixed-Precision Quantization Method
Qingcheng Zhu, Yangyang Ren, Linlin Yang +6
Deploying large language models (LLMs) is challenging due to their massive parameters and high computational costs. Ultra low-bit quantization can significantly reduce storage and…
Confidence Dimension for Deep Learning based on Hoeffding Inequality and Relative Evaluation
Runqi Wang, Linlin Yang, Baochang Zhang +3
Research on the generalization ability of deep neural networks (DNNs) has recently attracted a great deal of attention. However, due to their complex architectures and large number…
Cogradient Descent for Dependable Learning
Runqi Wang, Baochang Zhang, Li'an Zhuo +2
Conventional gradient descent methods compute the gradients for multiple variables through the partial derivative. Treating the coupled variables independently while ignoring the i…