Publications (7)
Historically Relevant Event Structuring for Temporal Knowledge Graph Reasoning
Jinchuan Zhang, Ming Sun, Chong Mu +3
Temporal Knowledge Graph (TKG) reasoning focuses on predicting events through historical information within snapshots distributed on a timeline. Existing studies mainly concentrate…
MA-DAR: Manifold-Aligned Dynamic Adaptive Routing for Continual Temporal Knowledge Graph Reasoning
Xiangjun Shi, Chong Mu, Jinchuan Zhang +3
Continual temporal knowledge graph (TKG) reasoning aims to continuously incorporate newly emerging facts while preserving previously acquired knowledge. Replay-based continual lear…
Learning Multi-graph Structure for Temporal Knowledge Graph Reasoning
Jinchuan Zhang, Bei Hui, Chong Mu +1
Temporal Knowledge Graph (TKG) reasoning that forecasts future events based on historical snapshots distributed over timestamps is denoted as extrapolation and has gained significa…
Learning Granularity Representation for Temporal Knowledge Graph Completion
Jinchuan Zhang, Tianqi Wan, Chong Mu +2
Temporal Knowledge Graphs (TKGs) incorporate temporal information to reflect the dynamic structural knowledge and evolutionary patterns of real-world facts. Nevertheless, TKGs are…
FedWeave: Rethinking the Unit of Specialization in Heterogeneous Federated MoE-LoRA
Donghang Duan, Xu Zheng, Lizong Zhang +2
The paper introduces FedWeave, a federated learning framework that separates expert aggregation from router optimization to better handle heterogeneous tasks by using prototype-lev…
SAMA: Semantic Anchor-aligned Augmentation for Unified Low-Resource Multimodal Information Extraction
Quanjiang Guo, Chong Mu, Jiazhou Pan +4
Multimodal Information Extraction (MIE)-covering tasks such as Multimodal Named Entity Recognition (MNER), Relation Extraction (MRE), and Event Extraction (MEE)-is essential for un…