4 papers
Superpose Task-specific Features for Model Merging
Haiquan Qiu, You Wu, Dong Li +2
Model merging enables powerful capabilities in neural networks without requiring additional training. In this paper, we introduce a novel perspective on model merging by leveraging…
Automated Decision-Making on Networks with LLMs through Knowledge-Guided Evolution
Xiaohan Zheng, Lanning Wei, Yong Li +1
Effective decision-making on networks often relies on learning from graph-structured data, where Graph Neural Networks (GNNs) play a central role, but they take efforts to configur…
Dual Reasoning: A GNN-LLM Collaborative Framework for Knowledge Graph Question Answering
Guangyi Liu, Yongqi Zhang, Yong Li +1
Large Language Models (LLMs) excel at intuitive, implicit reasoning. Guiding LLMs to construct thought chains can enhance their deliberate reasoning abilities, but also faces chall…
Generalizing Hyperedge Expansion for Hyper-relational Knowledge Graph Modeling
Yu Liu, Shu Yang, Jingtao Ding +2
By representing knowledge in a primary triple associated with additional attribute-value qualifiers, hyper-relational knowledge graph (HKG) that generalizes triple-based knowledge…