Graph Partner Neural Networks for Semi-Supervised Learning on Graphs. - Langzhang Liang; Cuiyun Gao 001; Shiyi Chen; Shishi Duan; Yu Pan 005; Junjin Zheng; Lei Wang; Zenglin Xu (CoRR, 2021)

Style Change Detection Based On Bert And Conv1d. - Qidi Lao; Li Ma 011; Wenyin Yang; Zexian Yang; Dong Yuan; Zhenlin Tan; Langzhang Liang (CLEF (Working Notes), 2022)

ResNorm: Tackling Long-tailed Degree Distribution Issue in Graph Neural Networks via Normalization. - Langzhang Liang; Zenglin Xu; Zixing Song; Irwin King; Jieping Ye (CoRR, 2022)

Predicting Global Label Relationship Matrix for Graph Neural Networks under Heterophily. - Langzhang Liang; Xiangjing Hu; Zenglin Xu; Zixing Song; Irwin King (NeurIPS, 2023)

Sign is Not a Remedy: Multiset-to-Multiset Message Passing for Learning on Heterophilic Graphs. - Langzhang Liang; Sunwoo Kim 006; Kijung Shin; Zenglin Xu; Shirui Pan; Yuan Qi 001 (ICML, 2024)

Tackling Long-Tailed Distribution Issue in Graph Neural Networks via Normalization. - Langzhang Liang; Zenglin Xu; Zixing Song; Irwin King; Yuan Qi 001; Jieping Ye (IEEE Trans. Knowl. Data Eng., 2024)

Mitigating Over-Squashing in Graph Neural Networks by Spectrum-Preserving Sparsification. - Langzhang Liang; Fanchen Bu; Zixing Song; Zenglin Xu; Shirui Pan; Kijung Shin (CoRR, 2025)