3 papers
cs.LG2026
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…
cs.SI2026
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…
cs.DL2025
How Deep Do Large Language Models Internalize Scientific Literature and Citation Practices?
Andres Algaba, Vincent Holst, Floriano Tori +4
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…