期刊/会议论文：

[1]Zhang Y, Kong X, Ye K, et al. Tackling sparse facts for temporal knowledge graph completion[C]//Proceedings of the ACM on Web Conference 2025. 2025: 3561-3570.（WWW`2025, CCF-A类会议）

[2]Zhang Y,Kong X,Ye K, et al. DSTAG: A Semantic Tag-Enhanced Dual-Graph Convolutional Network for Temporal Knowledge Graph Completion[C]//Proceedings of the ACM Web Conference 2026. 2026: 3645-3655.（WWW`2026, CCF-A类会议，oral）

[3]Zhang Y,Kong X, Shen Z, et al. A survey on temporal knowledge graph embedding: Models and applications[J]. Knowledge-Based Systems, 2024, 304: 112454.（中科院1区，IF=7.6）

[4]Zhang Y, Kong X, Liu Y, et al. LDCL: Large language model-driven dual-view contrastive learning for temporal knowledge graph completion[J]. Information Sciences, 2026: 123273.（CCF-B类期刊，IF=6.8）

[5]Zhang Y, Kong X, Ye K, et al. A context-aware temporal knowledge graph completion method based on logical paths[J]. Neurocomputing, 2026: 133049.（中科院2区，IF=6.5）

[6]Ye K, Kong X,Zhang Y, et al. Dual history enhancement with hybrid hypergraph-graph networks for temporal knowledge graph reasoning[C]//Proceedings of the ACM Web Conference 2026. 2026: 3800-3810.（WWW`2026, CCF-A类会议）

[7]Zheng S, Zhu Y,Zhang Y, et al. Multi-hop reasoning with fine-grained entity representations and LLM-augmented actions over few-shot knowledge graphs[J]. Knowledge and Information Systems, 2026, 68(1): 86.（CCF-B类期刊，IF=2.8）

[8]Zheng, S., Nie, X., Yuan, W., Qu, L., Kong, X.,Zhang, Y., & Hou, J. Context-aware adaptive reinforcement learning for multi-hop knowledge graph reasoning in few-shot scenarios[J]. Knowledge-Based Systems, 2025: 114799.（中科院1区，IF=7.6）