72 citations · 300 across the 34 of their papers we have counts for
4 papers · 1 filter
LEAP: A closed-loop framework for perovskite precursor additive discovery
Xin-De Wang, Zhi-Rui Chen, Ze-Feng Gao +3
Efficient discovery of precursor additives is essential for improving the performance of perovskite solar cells, yet the large chemical space makes conventional trial-and-error scr…
Strategic Over-Parameterization for Generalizable Low-Rank Adaptation
Jing Gao, Zhong-Yi Lu, Pan Zhang +1
Adapting large language models (LLMs) to downstream tasks via full fine-tuning is increasingly impractical due to its computational and memory demands. Parameter-efficient fine-tun…
Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators
Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao +3
This paper presents a novel pre-trained language models (PLM) compression approach based on the matrix product operator (short as MPO) from quantum many-body physics. It can decomp…
Compressing deep neural networks by matrix product operators
Ze-Feng Gao, Song Cheng, Rong-Qiang He +4
A deep neural network is a parametrization of a multilayer mapping of signals in terms of many alternatively arranged linear and nonlinear transformations. The linear transformatio…