4 papers
UniHR: Hierarchical Representation Learning for Unified Knowledge Graph Link Prediction
Zhiqiang Liu, Yin Hua, Mingyang Chen +4
Real-world knowledge graphs (KGs) contain not only standard triple-based facts, but also more complex, heterogeneous types of facts, such as hyper-relational facts with auxiliary k…
ReSearch: Learning to Reason with Search for LLMs via Reinforcement Learning
Mingyang Chen, Linzhuang Sun, Tianpeng Li +10
Large Language Models (LLMs) have shown remarkable capabilities in reasoning, exemplified by the success of OpenAI-o1 and DeepSeek-R1. However, integrating reasoning with external…
Croppable Knowledge Graph Embedding
Yushan Zhu, Wen Zhang, Zhiqiang Liu +3
Knowledge Graph Embedding (KGE) is a common approach for Knowledge Graphs (KGs) in AI tasks. Embedding dimensions depend on application scenarios. Requiring a new dimension means t…
Beyond Completion: A Foundation Model for General Knowledge Graph Reasoning
Yin Hua, Zhiqiang Liu, Mingyang Chen +6
In natural language processing (NLP) and computer vision (CV), the successful application of foundation models across diverse tasks has demonstrated their remarkable potential. How…