Compositional Learning of Relation Paths Embedding for Knowledge Base Completion. - Xixun Lin; Yanchun Liang 001; Renchu Guan (CoRR, 2016)

A Knowledge Base Completion Model Based on Path Feature Learning. - Xixun Lin; Yanchun Liang 001; Limin Wang 011; Xu Wang; Mary Qu Yang; Renchu Guan (Int. J. Comput. Commun. Control, 2018)

Guiding Cross-lingual Entity Alignment via Adversarial Knowledge Embedding. - Xixun Lin; Hong Yang 003; Jia Wu 001; Chuan Zhou 001; Bin Wang 004 (ICDM, 2019)

Relation path embedding in knowledge graphs. - Xixun Lin; Yanchun Liang 001; Fausto Giunchiglia; Xiaoyue Feng; Renchu Guan (Neural Comput. Appl., 2019)

Exploratory Adversarial Attacks on Graph Neural Networks. - Xixun Lin; Chuan Zhou 001; Hong Yang 003; Jia Wu 001; Haibo Wang 004; Yanan Cao 001; Bin Wang 004 (ICDM, 2020)

Improving Cross-Domain Slot Filling with Common Syntactic Structure. - Luchen Liu; Xixun Lin; Peng Zhang 001; Bin Wang 004 (ICASSP, 2021)

Disentangled Deep Multivariate Hawkes Process for Learning Event Sequences. - Xixun Lin; Jiangxia Cao; Peng Zhang 001; Chuan Zhou 001; Zhao Li 007; Jia Wu 001; Bin Wang 004 (ICDM, 2021)

Deep Structural Point Process for Learning Temporal Interaction Networks. - Jiangxia Cao; Xixun Lin; Xin Cong; Shu Guo; Hengzhu Tang; Tingwen Liu; Bin Wang 004 (ECML/PKDD (1), 2021)

Bipartite Graph Embedding via Mutual Information Maximization. - Jiangxia Cao; Xixun Lin; Shu Guo; Luchen Liu; Tingwen Liu; Bin Wang 004 (WSDM, 2021)

Task-adaptive Neural Process for User Cold-Start Recommendation. - Xixun Lin; Jia Wu 001; Chuan Zhou 001; Shirui Pan; Yanan Cao 001; Bin Wang 004 (WWW, 2021)

Learning Common Dependency Structure for Unsupervised Cross-Domain Ner. - Luchen Liu; Xixun Lin; Peng Zhang 001; Lei Zhang 119; Bin Wang 004 (ICASSP, 2022)

DisenCDR: Learning Disentangled Representations for Cross-Domain Recommendation. - Jiangxia Cao; Xixun Lin; Xin Cong; Jing Ya; Tingwen Liu; Bin Wang 004 (SIGIR, 2022)

Exploratory Adversarial Attacks on Graph Neural Networks for Semi-Supervised Node Classification. - Xixun Lin; Chuan Zhou 001; Jia Wu 001; Hong Yang 003; Haibo Wang 004; Yanan Cao 001; Bin Wang 004 (Pattern Recognit., 2023)

CL4CO: A Curriculum Training Framework for Graph-Based Neural Combinatorial Optimization. - Yang Liu 320; Chuan Zhou 001; Peng Zhang 001; Zhao Li 007; Shuai Zhang; Xixun Lin; Xindong Wu 001 (ICDM, 2024)

Graph Neural Stochastic Diffusion for Estimating Uncertainty in Node Classification. - Xixun Lin; Wenxiao Zhang; Fengzhao Shi; Chuan Zhou 001; Lixin Zou; Xiangyu Zhao 001; Dawei Yin; Shirui Pan; Yanan Cao 001 (ICML, 2024)

Neural Jump-Diffusion Temporal Point Processes. - Shuai Zhang; Chuan Zhou 001; Yang Aron Liu; Peng Zhang 001; Xixun Lin; Zhi-Ming Ma (ICML, 2024)

Towards Flexible and Adaptive Neural Process for Cold-Start Recommendation. - Xixun Lin; Chuan Zhou 001; Jia Wu 001; Lixin Zou; Shirui Pan; Yanan Cao 001; Bin Wang 004; Shuaiqiang Wang; Dawei Yin (IEEE Trans. Knowl. Data Eng., 2024)

Structure-Aware Prototypical Neural Process for Few-Shot Graph Classification. - Xixun Lin; Zhao Li 007; Peng Zhang 001; Luchen Liu; Chuan Zhou 001; Bin Wang 004; Zhihong Tian (IEEE Trans. Neural Networks Learn. Syst., 2024)

VR-GNN: variational relation vector graph neural network for modeling homophily and heterophily. - Fengzhao Shi; Yanan Cao 001; Ren Li; Xixun Lin; Yanmin Shang; Chuan Zhou 001; Jia Wu 001; Shirui Pan (World Wide Web (WWW), 2024)

UniFORM: Towards Unified Framework for Anomaly Detection on Graphs. - Chuancheng Song; Xixun Lin; Hanyang Shen; Yanmin Shang; Yanan Cao 001 (AAAI, 2025)

Reliably Bounding False Positives: A Zero-Shot Machine-Generated Text Detection Framework via Multiscaled Conformal Prediction. - Xiaowei Zhu; Yubing Ren; Yanan Cao 001; Xixun Lin; Fang Fang 009; Yangxi Li (ACL (1), 2025)

Conformal Graph-level Out-of-distribution Detection with Adaptive Data Augmentation. - Xixun Lin; Yanan Cao 001; Nan Sun; Lixin Zou; Chuan Zhou 001; Peng Zhang 001; Shuai Zhang; Ge Zhang 002; Jia Wu 001 (WWW, 2025)

IBPL: Information Bottleneck-based Prompt Learning for graph out-of-distribution detection. - Yanan Cao 001; Fengzhao Shi; Qing Yu; Xixun Lin; Chuan Zhou 001; Lixin Zou; Peng Zhang 001; Zhao Li 007; Dawei Yin (Neural Networks, 2025)

Equivariant Hypergraph Diffusion for Crystal Structure Prediction. - Yang Liu 320; Chuan Zhou 001; Shuai Zhang; Peng Zhang 001; Xixun Lin; Shirui Pan (CoRR, 2025)

A data-centric framework of improving graph neural networks for knowledge graph embedding. - Yanan Cao 001; Xixun Lin; Yongxuan Wu; Fengzhao Shi; Yanmin Shang; Qingfeng Tan; Chuan Zhou 001; Peng Zhang 001 (World Wide Web (WWW), 2025)

BadMoE: Backdooring Mixture-of-Experts LLMs via Optimizing Routing Triggers and Infecting Dormant Experts. - Qingyue Wang; Qi Pang; Xixun Lin; Shuai Wang 011; Daoyuan Wu (CoRR, 2025)

Large Language Models for Planning: A Comprehensive and Systematic Survey. - Pengfei Cao; Tianyi Men; Wencan Liu; Jingwen Zhang; Xuzhao Li; Xixun Lin; Dianbo Sui; Yanan Cao; Kang Liu 001; Jun Zhao 001 (CoRR, 2025)

Contrastive Modality-Disentangled Learning for Multimodal Recommendation. - Xixun Lin; Rui Liu 032; Yanan Cao 001; Lixin Zou; Qian Li 003; Yongxuan Wu; Yang Liu 320; Dawei Yin; Guandong Xu (ACM Trans. Inf. Syst., 2025)

Evidential Spectrum-Aware Contrastive Learning for OOD Detection in Dynamic Graphs. - Nan Sun; Xixun Lin; Zhiheng Zhou; Yanmin Shang; Zhenlin Cheng; Yanan Cao 001 (CoRR, 2025)

RANA: Robust Active Learning for Noisy Network Alignment. - Yixuan Nan; Xixun Lin; Yanmin Shang; Zhuofan Li; Can Zhao; Yanan Cao 001 (CoRR, 2025)

Deep Graph Neural Point Process For Learning Temporal Interactive Networks. - Su Chen; Xiaohua Qi; Xixun Lin; Yanmin Shang; Xiaolin Xu; Yangxi Li (CoRR, 2025)