17 citations · 34 across the 6 of their papers we have counts for
6 papers
Automatic Evaluation Metrics for Artificially Generated Scientific Research
Niklas Höpner, Leon Eshuijs, Dimitrios Alivanistos +2
Foundation models are increasingly used in scientific research, but evaluating AI-generated scientific work remains challenging. While expert reviews are costly, large language mod…
Approximate Answering of Graph Queries
Michael Cochez, Dimitrios Alivanistos, Erik Arakelyan +6
Knowledge graphs (KGs) are inherently incomplete because of incomplete world knowledge and bias in what is the input to the KG. Additionally, world knowledge constantly expands and…
BioBLP: A Modular Framework for Learning on Multimodal Biomedical Knowledge Graphs
Daniel Daza, Dimitrios Alivanistos, Payal Mitra +3
Knowledge graphs (KGs) are an important tool for representing complex relationships between entities in the biomedical domain. Several methods have been proposed for learning embed…
Prompting as Probing: Using Language Models for Knowledge Base Construction
Dimitrios Alivanistos, Selene Báez Santamaría, Michael Cochez +3
Language Models (LMs) have proven to be useful in various downstream applications, such as summarisation, translation, question answering and text classification. LMs are becoming…
Query Embedding on Hyper-relational Knowledge Graphs
Dimitrios Alivanistos, Max Berrendorf, Michael Cochez +1
Multi-hop logical reasoning is an established problem in the field of representation learning on knowledge graphs (KGs). It subsumes both one-hop link prediction as well as other m…
Approximate Knowledge Graph Query Answering: From Ranking to Binary Classification
Ruud van Bakel, Teodor Aleksiev, Daniel Daza +2
Large, heterogeneous datasets are characterized by missing or even erroneous information. This is more evident when they are the product of community effort or automatic fact extra…