Multi-Camera-Based Universal Measurement Method for 6-DOF of Rigid Bodies in World Coordinate System. - Zuoxi Zhao; Yuchang Zhu; Yuanhong Li; Zhi Qiu; Yangfan Luo; Chaoshi Xie; Zhuangzhuang Zhang (Sensors, 2020)

AutoMine: An Unmanned Mine Dataset. - Yuchen Li 004; Zixuan Li; Siyu Teng; Yu Zhang 109; Yuhang Zhou; Yuchang Zhu; Dongpu Cao; Bin Tian 003; Yunfeng Ai; Zhe Xuanyuan; Long Chen 005 (CVPR, 2022)

A Smartphone-Based Six-DOF Measurement Method With Marker Detector. - Yuchang Zhu; Yuan Huang; Yuanhong Li; Zhi Qiu; Zuoxi Zhao (IEEE Trans. Instrum. Meas., 2022)

Scaling Up, Scaling Deep: Blockwise Graph Contrastive Learning. - Jintang Li; Wangbin Sun; Ruofan Wu; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2023)

Hetero$^2$Net: Heterophily-aware Representation Learning on Heterogenerous Graphs. - Jintang Li; Zheng Wei; Jiawang Dan; Jing Zhou; Yuchang Zhu; Ruofan Wu; Baokun Wang; Zhang Zhen; Changhua Meng; Hong Jin; Zibin Zheng; Liang Chen 001 (CoRR, 2023)

LasTGL: An Industrial Framework for Large-Scale Temporal Graph Learning. - Jintang Li; Jiawang Dan; Ruofan Wu; Jing Zhou; Sheng Tian; Yunfei Liu; Baokun Wang; Changhua Meng; Weiqiang Wang 002; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2023)

CLA: A self-supervised contrastive learning method for leaf disease identification with domain adaptation. - Ruzhun Zhao; Yuchang Zhu; Yuanhong Li (Comput. Electron. Agric., 2023)

Lane Detection Method Based on Deformable Linear Convolution. - Yuchang Zhu; Nanfeng Xiao (IJCNN, 2024)

Comprehensive Teacher-based Multi-task Model Train Using a Small Amount of Data. - Yuchang Zhu; Nanfeng Xiao (IJCNN, 2024)

One Fits All: Learning Fair Graph Neural Networks for Various Sensitive Attributes. - Yuchang Zhu; Jintang Li; Yatao Bian; Zibin Zheng; Liang Chen 001 (KDD, 2024)

The Devil is in the Data: Learning Fair Graph Neural Networks via Partial Knowledge Distillation. - Yuchang Zhu; Jintang Li; Liang Chen 001; Zibin Zheng (WSDM, 2024)

Fair Graph Representation Learning via Sensitive Attribute Disentanglement. - Yuchang Zhu; Jintang Li; Zibin Zheng; Liang Chen 001 (WWW, 2024)

Revisiting and Benchmarking Graph Autoencoders: A Contrastive Learning Perspective. - Jintang Li; Ruofan Wu; Yuchang Zhu; Huizhe Zhang; Xinzhou Jin; Guibin Zhang; Zulun Zhu; Zibin Zheng; Liang Chen 001 (CoRR, 2024)

Simple Scalable Multimodal Semantic Segmentation Model. - Yuchang Zhu; Nanfeng Xiao (Sensors, 2024)

FairAGG: Toward Fair Graph Neural Networks via Fair Aggregation. - Yuchang Zhu; Jintang Li; Liang Chen 001; Zibin Zheng (IEEE Trans. Comput. Soc. Syst., 2024)

FairDLA: Improving the fairness-utility trade-off in graph neural networks via dual-level alignment. - Ying Zhen; Yuchang Zhu; Jintang Li; Liang Chen 001 (Knowl. Based Syst., 2025)

Measuring Diversity in Synthetic Datasets. - Yuchang Zhu; Huizhe Zhang; Bingzhe Wu; Jintang Li; Zibin Zheng; Peilin Zhao; Liang Chen 001; Yatao Bian (CoRR, 2025)

Are Large Language Models In-Context Graph Learners? - Jintang Li; Ruofan Wu; Yuchang Zhu; Huizhe Zhang; Liang Chen 001; Zibin Zheng (CoRR, 2025)

GT-SVQ: A Linear-Time Graph Transformer for Node Classification Using Spiking Vector Quantization. - Huizhe Zhang; Jintang Li; Yuchang Zhu; Liang Chen 001; Zibin Zheng (CoRR, 2025)

SaGIF: Improving Individual Fairness in Graph Neural Networks via Similarity Encoding. - Yuchang Zhu; Jintang Li; Huizhe Zhang; Liang Chen 001; Zibin Zheng (CoRR, 2025)

What Matters in LLM-generated Data: Diversity and Its Effect on Model Fine-Tuning. - Yuchang Zhu; Huazhen Zhong; Qunshu Lin; Haotong Wei; Xiaolong Sun; Zixuan Yu; Minghao Liu; Zibin Zheng; Liang Chen 001 (CoRR, 2025)

Heterophily-Aware Representation Learning on Heterogeneous Graphs. - Jintang Li; Zheng Wei; Yuchang Zhu; Ruofan Wu; Huizhe Zhang; Liang Chen 001; Zibin Zheng (IEEE Trans. Pattern Anal. Mach. Intell., 2025)