16 citations · 26 across the 5 of their papers we have counts for
7 papers
Signal or Noise? Modality Contribution and Cooperation in Multimodal GraphRAG
Antonios Georgakopoulos, Paul Groth, Lise Stork
Multimodal knowledge graphs (KGs) integrate information from text, figures, tables, and other modalities into a unified structured representation, with the promise that richer evid…
Sound and Complete Neurosymbolic Reasoning with LLM-Grounded Interpretations
Bradley P. Allen, Prateek Chhikara, Thomas Macaulay Ferguson +2
Large language models (LLMs) have demonstrated impressive capabilities in natural language understanding and generation, but exhibit problems with logical consistency in their outp…
A Benchmark for the Detection of Metalinguistic Disagreements between LLMs and Knowledge Graphs
Bradley P. Allen, Paul T. Groth
Evaluating large language models (LLMs) for tasks like fact extraction in support of knowledge graph construction frequently involves computing accuracy metrics using a ground trut…
Evaluating Class Membership Relations in Knowledge Graphs using Large Language Models
Bradley P. Allen, Paul T. Groth
A backbone of knowledge graphs are their class membership relations, which assign entities to a given class. As part of the knowledge engineering process, we propose a new method f…
SHROOM-INDElab at SemEval-2024 Task 6: Zero- and Few-Shot LLM-Based Classification for Hallucination Detection
Bradley P. Allen, Fina Polat, Paul Groth
We describe the University of Amsterdam Intelligent Data Engineering Lab team's entry for the SemEval-2024 Task 6 competition. The SHROOM-INDElab system builds on previous work on…
From Data Creator to Data Reuser: Distance Matters
Christine L. Borgman, Paul T. Groth
Sharing research data is necessary, but not sufficient, for data reuse. Open science policies focus more heavily on data sharing than on reuse, yet both are complex, labor-intensiv…
Knowledge Engineering using Large Language Models
Bradley P. Allen, Lise Stork, Paul Groth
Knowledge engineering is a discipline that focuses on the creation and maintenance of processes that generate and apply knowledge. Traditionally, knowledge engineering approaches h…