Electronic transport of a large scale system studied by renormalized transfer matrix method: Application to armchair graphene nanoribbons between quantum wires. - Miao Gao; Gui-Ping Zhang; Zhong-Yi Lu (Comput. Phys. Commun., 2014)

Accelerating optimization by tracing valley. - Qing-Xiao Li; Rong-Qiang He; Zhong-Yi Lu (Comput. Phys. Commun., 2016)

Compressing deep neural networks by matrix product operators. - Ze-Feng Gao; Song Cheng; Rong-Qiang He; Zhi-Yuan Xie; Hui-Hai Zhao; Zhong-Yi Lu; Tao Xiang 004 (CoRR, 2019)

Compressing LSTM Networks by Matrix Product Operators. - Ze-Feng Gao; Xingwei Sun; Lan Gao; Junfeng Li; Zhong-Yi Lu (CoRR, 2020)

A Model Compression Method With Matrix Product Operators for Speech Enhancement. - Xingwei Sun; Ze-Feng Gao; Zhong-Yi Lu; Junfeng Li; Yonghong Yan 002 (IEEE ACM Trans. Audio Speech Lang. Process., 2020)

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators. - Peiyu Liu 002; Ze-Feng Gao; Wayne Xin Zhao; Zhi-Yuan Xie; Zhong-Yi Lu; Ji-Rong Wen (ACL/IJCNLP (1), 2021)

Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models. - Ze-Feng Gao; Peiyu Liu 002; Wayne Xin Zhao; Zhong-Yi Lu; Ji-Rong Wen (COLING, 2022)

A simple framework for contrastive learning phases of matter. - Xiao-Qi Han; Sheng-Song Xu; Zhen Feng; Rong-Qiang He; Zhong-Yi Lu (CoRR, 2022)

Variational optimization of the amplitude of neural-network quantum many-body ground states. - Jia-Qi Wang; Rong-Qiang He; Zhong-Yi Lu (CoRR, 2023)

AI-accelerated Discovery of Altermagnetic Materials. - Ze-Feng Gao; Shuai Qu; Bocheng Zeng; Yang Liu 005; Ji-Rong Wen; Hao Sun 002; Peng-Jie Guo; Zhong-Yi Lu (CoRR, 2023)

Compression Image Dataset Based on Multiple Matrix Product States. - Ze-Feng Gao; Peiyu Liu 002; Wayne Xin Zhao; Zhi-Yuan Xie; Ji-Rong Wen; Zhong-Yi Lu (FICC (2), 2024)

Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation. - Yu-Liang Zhan; Zhong-Yi Lu; Hao Sun; Ze-Feng Gao (NeurIPS, 2024)

AI-accelerated discovery of high critical temperature superconductors. - Xiao-Qi Han; Zhenfeng Ouyang; Peng-Jie Guo; Hao Sun; Ze-Feng Gao; Zhong-Yi Lu (CoRR, 2024)

AI-driven inverse design of materials: Past, present and future. - Xiao-Qi Han; Xin-De Wang; Meng-Yuan Xu; Zhen Feng; Bo-Wen Yao; Peng-Jie Guo; Ze-Feng Gao; Zhong-Yi Lu (CoRR, 2024)

Strong phonon-mediated high temperature superconductivity in Li2AuH6 under ambient pressure. - Zhenfeng Ouyang; Bo-Wen Yao; Xiao-Qi Han; Peng-Jie Guo; Ze-Feng Gao; Zhong-Yi Lu (CoRR, 2025)

Generalized Lanczos method for systematic optimization of neural-network quantum states. - Jia-Qi Wang; Rong-Qiang He; Zhong-Yi Lu (CoRR, 2025)

InvDesFlow-AL: Active Learning-based Workflow for Inverse Design of Functional Materials. - Xiao-Qi Han; Peng-Jie Guo; Ze-Feng Gao; Hao Sun; Zhong-Yi Lu (CoRR, 2025)

HTSC-2025: A Benchmark Dataset of Ambient-Pressure High-Temperature Superconductors for AI-Driven Critical Temperature Prediction. - Xiao-Qi Han; Ze-Feng Gao; Xin-De Wang; Zhenfeng Ouyang; Peng-Jie Guo; Zhong-Yi Lu (CoRR, 2025)

Perovskite-R1: A Domain-Specialized LLM for Intelligent Discovery of Precursor Additives and Experimental Design. - Xin-De Wang; Zhi-Rui Chen; Peng-Jie Guo; Ze-Feng Gao; Cheng Mu; Zhong-Yi Lu (CoRR, 2025)