61 citations · 133 across the 14 of their papers we have counts for
9 papers · 1 filter
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…
Probabilistic Regular Tree Priors for Scientific Symbolic Reasoning
Tim Schneider, Amin Totounferoush, Wolfgang Nowak +1
Symbolic Regression (SR) allows for the discovery of scientific equations from data. To limit the large search space of possible equations, prior knowledge has been expressed in te…
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…
The Role of Large Language Models in the Recognition of Territorial Sovereignty: An Analysis of the Construction of Legitimacy
Francisco Castillo-Eslava, Carlos Mougan, Alejandro Romero-Reche +1
We examine the potential impact of Large Language Models (LLM) on the recognition of territorial sovereignty and its legitimization. We argue that while technology tools, such as G…
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…
Emotional Framing in the Spreading of False and True Claims
Akram Sadat Hosseini, Steffen Staab
The explosive growth of online misinformation, such as false claims, has affected the social behavior of online users. In order to be persuasive and mislead the audience, false cla…
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…
Link Prediction with Attention Applied on Multiple Knowledge Graph Embedding Models
Cosimo Gregucci, Mojtaba Nayyeri, Daniel Hernández +1
Predicting missing links between entities in a knowledge graph is a fundamental task to deal with the incompleteness of data on the Web. Knowledge graph embeddings map nodes into a…
SCENE: Reasoning about Traffic Scenes using Heterogeneous Graph Neural Networks
Thomas Monninger, Julian Schmidt, Jan Rupprecht +5
Understanding traffic scenes requires considering heterogeneous information about dynamic agents and the static infrastructure. In this work we propose SCENE, a methodology to enco…