33 citations · 91 across the 14 of their papers we have counts for
14 papers
SEMMA: A Semantic Aware Knowledge Graph Foundation Model
Arvindh Arun, Sumit Kumar, Mojtaba Nayyeri +4
Knowledge Graph Foundation Models (KGFMs) have shown promise in enabling zero-shot reasoning over unseen graphs by learning transferable patterns. However, most existing KGFMs rely…
From Tokens to Lattices: Emergent Lattice Structures in Language Models
Bo Xiong, Steffen Staab
Pretrained masked language models (MLMs) have demonstrated an impressive capability to comprehend and encode conceptual knowledge, revealing a lattice structure among concepts. Thi…
NestE: Modeling Nested Relational Structures for Knowledge Graph Reasoning
Bo Xiong, Mojtaba Nayyeri, Linhao Luo +3
Reasoning with knowledge graphs (KGs) has primarily focused on triple-shaped facts. Recent advancements have been explored to enhance the semantics of these facts by incorporating…
ChatRule: Mining Logical Rules with Large Language Models for Knowledge Graph Reasoning
Linhao Luo, Jiaxin Ju, Bo Xiong +3
Logical rules are essential for uncovering the logical connections between relations, which could improve reasoning performance and provide interpretable results on knowledge graph…
A Survey on Temporal Knowledge Graph Completion: Taxonomy, Progress, and Prospects
Jiapu Wang, Boyue Wang, Meikang Qiu +8
Temporal characteristics are prominently evident in a substantial volume of knowledge, which underscores the pivotal role of Temporal Knowledge Graphs (TKGs) in both academia and i…
Shrinking Embeddings for Hyper-Relational Knowledge Graphs
Bo Xiong, Mojtaba Nayyer, Shirui Pan +1
Link prediction on knowledge graphs (KGs) has been extensively studied on binary relational KGs, wherein each fact is represented by a triple. A significant amount of important kno…
Towards Expressive Spectral-Temporal Graph Neural Networks for Time Series Forecasting
Ming Jin, Guangsi Shi, Yuan-Fang Li +7
Time series forecasting has remained a focal point due to its vital applications in sectors such as energy management and transportation planning. Spectral-temporal graph neural ne…
Geometric Relational Embeddings: A Survey
Bo Xiong, Mojtaba Nayyeri, Ming Jin +4
Geometric relational embeddings map relational data as geometric objects that combine vector information suitable for machine learning and structured/relational information for str…
HiPrompt: Few-Shot Biomedical Knowledge Fusion via Hierarchy-Oriented Prompting
Jiaying Lu, Jiaming Shen, Bo Xiong +3
Medical decision-making processes can be enhanced by comprehensive biomedical knowledge bases, which require fusing knowledge graphs constructed from different sources via a unifor…
Modeling Relational Patterns for Logical Query Answering over Knowledge Graphs
Yunjie He, Mojtaba Nayyeri, Bo Xiong +3
Answering first-order logical (FOL) queries over knowledge graphs (KG) remains a challenging task mainly due to KG incompleteness. Query embedding approaches this problem by comput…
Ultrahyperbolic Knowledge Graph Embeddings
Bo Xiong, Shichao Zhu, Mojtaba Nayyeri +4
Recent knowledge graph (KG) embeddings have been advanced by hyperbolic geometry due to its superior capability for representing hierarchies. The topological structures of real-wor…
Faithiful Embeddings for EL++ Knowledge Bases
Bo Xiong, Nico Potyka, Trung-Kien Tran +2
Recently, increasing efforts are put into learning continual representations for symbolic knowledge bases (KBs). However, these approaches either only embed the data-level knowledg…
Pseudo-Riemannian Graph Convolutional Networks
Bo Xiong, Shichao Zhu, Nico Potyka +3
Graph convolutional networks (GCNs) are powerful frameworks for learning embeddings of graph-structured data. GCNs are traditionally studied through the lens of Euclidean geometry.…
MOFA: Modular Factorial Design for Hyperparameter Optimization
Bo Xiong, Yimin Huang, Hanrong Ye +2
This paper presents a novel and lightweight hyperparameter optimization (HPO) method, MOdular FActorial Design (MOFA). MOFA pursues several rounds of HPO, where each round alternat…