Liu, Zemin

20 publications

ICML 2025 Adapting Precomputed Features for Efficient Graph Condensation Yuan Li, Jun Hu, Zemin Liu, Bryan Hooi, Jia Chen, Bingsheng He

IJCAI 2025 Contrastive Cross-Course Knowledge Tracing via Concept Graph Guided Knowledge Transfer Wenkang Han, Wang Lin, Liya Hu, Zhenlong Dai, Yiyun Zhou, Mengze Li, Zemin Liu, Chang Yao, Jingyuan Chen

NeurIPS 2025 MS-Bench: Evaluating LMMs in Ancient Manuscript Study Through a Dunhuang Case Study Yuqing Zhang, Yue Han, Shuanghe Zhu, Haoxiang Wu, Hangqi Li, Shengyu Zhang, Junchi Yan, Zemin Liu, Kun Kuang, Huaiyong Dou, Yongquan Zhang, Fei Wu

ICLR 2025 Multi-Label Node Classification with Label Influence Propagation Yifei Sun, Zemin Liu, Bryan Hooi, Yang Yang, Rizal Fathony, Jia Chen, Bingsheng He

IJCAI 2025 One-Shot Federated Learning Methods: A Practical Guide Xiang Liu, Zhenheng Tang, Xia Li, Yijun Song, Sijie Ji, Zemin Liu, Bo Han, Linshan Jiang, Jialin Li

NeurIPS 2025 RAG4GFM: Bridging Knowledge Gaps in Graph Foundation Models Through Graph Retrieval Augmented Generation Xingliang Wang, Zemin Liu, Junxiao Han, Shuiguang Deng

ICLR 2024 Consistency Training with Learnable Data Augmentation for Graph Anomaly Detection with Limited Supervision Nan Chen, Zemin Liu, Bryan Hooi, Bingsheng He, Rizal Fathony, Jun Hu, Jia Chen

ICLR 2024 EX-Graph: A Pioneering Dataset Bridging Ethereum and X Qian Wang, Zhen Zhang, Zemin Liu, Shengliang Lu, Bingqiao Luo, Bingsheng He

AAAI 2024 HGPrompt: Bridging Homogeneous and Heterogeneous Graphs for Few-Shot Prompt Learning Xingtong Yu, Yuan Fang, Zemin Liu, Xinming Zhang

ICML 2024 Identifiability Matters: Revealing the Hidden Recoverable Condition in Unbiased Learning to Rank Mouxiang Chen, Chenghao Liu, Zemin Liu, Zhuo Li, Jianling Sun

ICLR 2024 Partitioning Message Passing for Graph Fraud Detection Wei Zhuo, Zemin Liu, Bryan Hooi, Bingsheng He, Guang Tan, Rizal Fathony, Jia Chen

NeurIPS 2024 Revisiting Score Propagation in Graph Out-of-Distribution Detection Longfei Ma, Yiyou Sun, Kaize Ding, Zemin Liu, Fei Wu

NeurIPS 2023 Evaluating Post-Hoc Explanations for Graph Neural Networks via Robustness Analysis Junfeng Fang, Wei Liu, Yuan Gao, Zemin Liu, An Zhang, Xiang Wang, Xiangnan He

AAAI 2023 Learning to Count Isomorphisms with Graph Neural Networks Xingtong Yu, Zemin Liu, Yuan Fang, Xinming Zhang

AAAI 2023 On Generalized Degree Fairness in Graph Neural Networks Zemin Liu, Trung-Kien Nguyen, Yuan Fang

NeurIPS 2022 LBD: Decouple Relevance and Observation for Individual-Level Unbiased Learning to Rank Mouxiang Chen, Chenghao Liu, Zemin Liu, Jianling Sun

IJCAI 2021 Node-Wise Localization of Graph Neural Networks Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

AAAI 2021 Relative and Absolute Location Embedding for Few-Shot Node Classification on Graph Zemin Liu, Yuan Fang, Chenghao Liu, Steven C. H. Hoi

AAAI 2018 Distance-Aware DAG Embedding for Proximity Search on Heterogeneous Graphs Zemin Liu, Vincent W. Zheng, Zhou Zhao, Fanwei Zhu, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying

AAAI 2017 Semantic Proximity Search on Heterogeneous Graph by Proximity Embedding Zemin Liu, Vincent W. Zheng, Zhou Zhao, Fanwei Zhu, Kevin Chen-Chuan Chang, Minghui Wu, Jing Ying