8 citations · 12 across the 6 of their papers we have counts for
9 papers
Big-Big-SycoBench: A Benchmark to Detect Sycophancy Through Model Responses to Valid vs. Invalid Arguments
Marthe Ballon, Arne Vanhoyweghen, Seorin Kim +11
Sycophancy in large language models risks amplifying unsupported claims or beliefs across the knowledge ecosystem as these systems increasingly contribute to research synthesis, ev…
One in Eight OpenAlex Abstracts Has Integrity Issues
Seorin Kim, Vincent Holst, Vincent Ginis
Scientific abstracts are increasingly used as primary data in computational metascience research, yet the quality of these abstracts in widely used bibliographic databases has not…
Human-in-the-Loop LLM Grading for Handwritten Mathematics Assessments
Arne Vanhoyweghen, Vincent Holst, Melika Mobini +10
Providing timely and individualised feedback on handwritten student work is highly beneficial for learning but difficult to achieve at scale. This challenge has become more pressin…
Structurally Human, Semantically Biased: Detecting LLM-Generated References with Embeddings and GNNs
Melika Mobini, Vincent Holst, Floriano Tori +2
Large language models are increasingly used to curate bibliographies, raising the question: are their reference lists distinguishable from human ones? We build paired citation grap…
Turning Citation Networks Inside Out: Studying Science Using Content-Based Knowledge Graphs from LLM-Derived Taxonomies
Seorin Kim, Vincent Holst, Vincent Ginis
Scientific fields are often mapped using citations and metadata, despite knowledge being transmitted primarily through content. We introduce an 'inside-out' approach that reconstru…
How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices?
Andres Algaba, Vincent Holst, Floriano Tori +5
The spread of scientific knowledge depends on how researchers discover and cite previous work. The adoption of large language models (LLMs) in the scientific research process intro…
The Effectiveness of Curvature-Based Rewiring and the Role of Hyperparameters in GNNs Revisited
Floriano Tori, Vincent Holst, Vincent Ginis
Message passing is the dominant paradigm in Graph Neural Networks (GNNs). The efficiency of message passing, however, can be limited by the topology of the graph. This happens when…
Large Language Models Reflect Human Citation Patterns with a Heightened Citation Bias
Andres Algaba, Carmen Mazijn, Vincent Holst +3
Citation practices are crucial in shaping the structure of scientific knowledge, yet they are often influenced by contemporary norms and biases. The emergence of Large Language Mod…
Dataset Artefacts are the Hidden Drivers of the Declining Disruptiveness in Science
Vincent Holst, Andres Algaba, Floriano Tori +2
Park et al. [1] reported a decline in the disruptiveness of scientific and technological knowledge over time. Their main finding is based on the computation of CD indices, a measur…