1 citations · 1 across the 3 of their papers we have counts for
4 papers
A Systematic Evaluation Protocol of Graph-Derived Signals for Tabular Machine Learning
Mario Heidrich, Jeffrey Heidemann, Rüdiger Buchkremer +1
While graph-derived signals are widely used in tabular learning, existing studies typically rely on limited experimental setups and average performance comparisons, leaving the sta…
Performance and Practical Considerations of Large and Small Language Models in Clinical Decision Support in Rheumatology
Sabine Felde, Rüdiger Buchkremer, Gamal Chehab +4
Large language models (LLMs) show promise for supporting clinical decision-making in complex fields such as rheumatology. Our evaluation shows that smaller language models (SLMs),…
Unraveling Media Perspectives: A Comprehensive Methodology Combining Large Language Models, Topic Modeling, Sentiment Analysis, and Ontology Learning to Analyse Media Bias
Orlando Jähde, Thorsten Weber, Rüdiger Buchkremer
Biased news reporting poses a significant threat to informed decision-making and the functioning of democracies. This study introduces a novel methodology for scalable, minimally b…
ffstruc2vec: Flat, Flexible and Scalable Learning of Node Representations from Structural Identities
Mario Heidrich, Jeffrey Heidemann, Rüdiger Buchkremer +1
Node embedding refers to techniques that generate low-dimensional vector representations of nodes in a graph while preserving specific properties of the nodes. A key challenge in t…