25 citations · 179 across the 54 of their papers we have counts for
54 papers
Chimaera: A Mixture-of-Graph-Experts Architecture for Cross-Task and Cross-Dataset Graph Learning
Jonathan Frank, David Richerby, Ansgar Scherp
Designing foundation models for graphs is challenging due to the irregular structure of graphs and the different sizes and characteristics of embeddings. Chimaera integrates mixtur…
Are Researchers Being Replaced by Artificial Intelligence?
Angelo A. Salatino, Ansgar Scherp, Christin Katharina Kreutz +1
A Nature survey from 2023 involving 1,600 researchers shows that scientists are ``concerned, as well as excited, by the increasing use of artificial-intelligence tools in research.…
Do Language Models Encode Semantic Relations? Probing and Sparse Feature Analysis
Andor Diera, Ansgar Scherp
Understanding whether large language models (LLMs) capture structured meaning requires examining how they represent concept relationships. In this work, we study three models of in…
Gumbel-MPNN: Graph Rewiring with Gumbel-Softmax
Marcel Hoffmann, Lukas Galke, Ansgar Scherp
Graph homophily has been considered an essential property for message-passing neural networks (MPNN) in node classification. Recent findings suggest that performance is more closel…
Semantic Source Code Segmentation using Small and Large Language Models
Abdelhalim Dahou, Ansgar Scherp, Sebastian Kurten +2
Source code segmentation, dividing code into functionally coherent segments, is crucial for knowledge retrieval and maintenance in software development. While enabling efficient na…
iN2V: Bringing Transductive Node Embeddings to Inductive Graphs
Nicolas Lell, Ansgar Scherp
Shallow node embeddings like node2vec (N2V) can be used for nodes without features or to supplement existing features with structure-based information. Embedding methods like N2V a…