Ze-Feng Gao

According to our database, Ze-Feng Gao authored at least 22 papers between 2019 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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, July, 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, June, 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, May, 2025

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, January, 2025

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

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

Discovering symbolic expressions with parallelized tree search.

Kai Ruan, Ze-Feng Gao, Yike Guo, Hao Sun, Ji-Rong Wen, Yang Liu

CoRR, 2024

YuLan: An Open-source Large Language Model.

Yutao Zhu, Kun Zhou, Kelong Mao, Wentong Chen, Yiding Sun, Zhipeng Chen, Qian Cao, Yihan Wu, Yushuo Chen, Feng Wang, Lei Zhang, Junyi Li, Xiaolei Wang, Lei Wang, Beichen Zhang, Zican Dong, Xiaoxue Cheng, Yuhan Chen, Xinyu Tang, Yupeng Hou, Qiangqiang Ren, Xincheng Pang, Shufang Xie, Wayne Xin Zhao, Zhicheng Dou, Jiaxin Mao, Yankai Lin, Ruihua Song, Jun Xu, Xu Chen, Rui Yan, Zhewei Wei, Di Hu, Wenbing Huang, Ze-Feng Gao, Yueguo Chen, Weizheng Lu, Ji-Rong Wen

CoRR, 2024

Over-parameterized Student Model via Tensor Decomposition Boosted Knowledge Distillation.

Yu-Liang Zhan, Zhong-Yi Lu, Hao Sun, Ze-Feng Gao

Proceedings of the Advances in Neural Information Processing Systems 38: Annual Conference on Neural Information Processing Systems 2024, 2024

Compression Image Dataset Based on Multiple Matrix Product States.

Ze-Feng Gao, Peiyu Liu, Wayne Xin Zhao, Zhi-Yuan Xie, Ji-Rong Wen, Zhong-Yi Lu

Proceedings of the Advances in Information and Communication, 2024

Do Emergent Abilities Exist in Quantized Large Language Models: An Empirical Study.

Peiyu Liu, Zikang Liu, Ze-Feng Gao, Dawei Gao, Wayne Xin Zhao, Yaliang Li, Bolin Ding, Ji-Rong Wen

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Enhancing Parameter-efficient Fine-tuning with Simple Calibration Based on Stable Rank.

Peiyu Liu, Ze-Feng Gao, Xiao Zhang, Wayne Xin Zhao, Ji-Rong Wen

Proceedings of the 2024 Joint International Conference on Computational Linguistics, 2024

Unlocking Data-free Low-bit Quantization with Matrix Decomposition for KV Cache Compression.

Peiyu Liu, Ze-Feng Gao, Xin Zhao, Yipeng Ma, Tao Wang, Ji-Rong Wen

Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2024

2023

AI-accelerated Discovery of Altermagnetic Materials.

Ze-Feng Gao, Shuai Qu, Bocheng Zeng, Yang Liu, Ji-Rong Wen, Hao Sun, Peng-Jie Guo, Zhong-Yi Lu

CoRR, 2023

Scaling Pre-trained Language Models to Deeper via Parameter-efficient Architecture.

Peiyu Liu, Ze-Feng Gao, Yushuo Chen, Wayne Xin Zhao, Ji-Rong Wen

CoRR, 2023

Enhancing Scalability of Pre-trained Language Models via Efficient Parameter Sharing.

Peiyu Liu, Ze-Feng Gao, Yushuo Chen, Xin Zhao, Ji-Rong Wen

Proceedings of the Findings of the Association for Computational Linguistics: EMNLP 2023, 2023

Small Pre-trained Language Models Can be Fine-tuned as Large Models via Over-Parameterization.

Ze-Feng Gao, Kun Zhou, Peiyu Liu, Wayne Xin Zhao, Ji-Rong Wen

Proceedings of the 61st Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), 2023

2022

Parameter-Efficient Mixture-of-Experts Architecture for Pre-trained Language Models.

Ze-Feng Gao, Peiyu Liu, Wayne Xin Zhao, Zhong-Yi Lu, Ji-Rong Wen

Proceedings of the 29th International Conference on Computational Linguistics, 2022

2021

Enabling Lightweight Fine-tuning for Pre-trained Language Model Compression based on Matrix Product Operators.

Peiyu Liu, Ze-Feng Gao, Wayne Xin Zhao, Zhi-Yuan Xie, Zhong-Yi Lu, Ji-Rong Wen

Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, 2021

2020

A Model Compression Method With Matrix Product Operators for Speech Enhancement.

Xingwei Sun, Ze-Feng Gao, Zhong-Yi Lu, Junfeng Li, Yonghong Yan

IEEE ACM Trans. Audio Speech Lang. Process., 2020

Compressing LSTM Networks by Matrix Product Operators.

Ze-Feng Gao, Xingwei Sun, Lan Gao, Junfeng Li, Zhong-Yi Lu

CoRR, 2020

2019

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

CoRR, 2019