7 citations · 8 across the 18 of their papers we have counts for
6 papers · 1 filter
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…
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…
TrustUQA: A Trustful Framework for Unified Structured Data Question Answering
Wen Zhang, Long Jin, Yushan Zhu +6
Natural language question answering (QA) over structured data sources such as tables and knowledge graphs have been widely investigated, especially with Large Language Models (LLMs…
InBox: Recommendation with Knowledge Graph using Interest Box Embedding
Zezhong Xu, Yincen Qu, Wen Zhang +2
Knowledge graphs (KGs) have become vitally important in modern recommender systems, effectively improving performance and interpretability. Fundamentally, recommender systems aim t…
Prompt-fused framework for Inductive Logical Query Answering
Zezhong Xu, Peng Ye, Lei Liang +2
Answering logical queries on knowledge graphs (KG) poses a significant challenge for machine reasoning. The primary obstacle in this task stems from the inherent incompleteness of…
Unleashing the Power of Imbalanced Modality Information for Multi-modal Knowledge Graph Completion
Yichi Zhang, Zhuo Chen, Lei Liang +2
Multi-modal knowledge graph completion (MMKGC) aims to predict the missing triples in the multi-modal knowledge graphs by incorporating structural, visual, and textual information…