23 citations · 39 across the 20 of their papers we have counts for
13 papers · 1 filter
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…
Shorter Reasoning, Earlier Answers? An Evaluation of Reasoning Interfaces
Francesca Carlon, Vincent Ginis, Andres Algaba
Large language models often reason at length before answering, increasing cost and latency. Prompts and trained settings can shorten this reasoning, but a shorter trace may only sh…
How Much Does a Reasoning Summary Reveal? An Observability Ladder for Large Language Models
Andres Algaba, Francesca Carlon, Lynn Delcon +3
Large language models often show users a final response and a short reasoning summary while the full reasoning trace stays hidden. We introduce an observability ladder that holds e…
Geometric Configurations of Perturbed Jailbreak Prompts
Lynn Delcon, Andres Algaba, Vincent Ginis
Perturbation techniques that turn unsuccessful jailbreak prompts into successful ones are continuously evolving, constituting a major security threat to LLM safety. In this paper,…
Rebuttals Move Peer-Review Scores, but Initial-Review Structure Bounds the Movement
Mathieu Louis, Tibo Vanleke, Vincent Ginis +1
Author rebuttals are the main post-submission window in peer review, but their effect on reviewer scores remains hard to measure because score updates mix rebuttal content with ini…
Thinking Like a Scientist? A Structural Study of LLM-Generated Research Methods
Francesca Carlon, Brecht Verbeken, Brecht F. Verbeken +2
Large Language Models (LLMs) are increasingly used to guide research methodology, yet their default methodological tendencies under minimal prompting remain unclear. Here, we promp…
On the Spectral Region of 4-Cycle Stochastic Matrices
Brando Vagenende, Brecht Verbeken, Brecht F. Verbeken +2
We study the spectrum of 4-cycle row-stochastic matrices. For real eigenvalues the spectral region is [-1,1]. For nonreal eigenvalues a+ib we derive necessary conditions in terms o…
Scalable Classification of Course Information Sheets Using Large Language Models: A Reusable Institutional Method for Academic Quality Assurance
Brecht F. Verbeken, Brecht Verbeken, Joke Van den Broeck +5
Purpose: Higher education institutions face increasing pressure to audit course designs for generative AI (GenAI) integration. This paper presents an end-to-end method for using la…
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…
Early Evidence of Vibe-Proving with Consumer LLMs: A Case Study on Spectral Region Characterization with ChatGPT-5.2 (Thinking)
Brecht Verbeken, Brecht F. Verbeken, Brando Vagenende +3
Large Language Models (LLMs) are increasingly used as scientific copilots, but evidence on their role in research-level mathematics remains limited, especially for workflows access…
Probing the Trajectories of Reasoning Traces in Large Language Models
Marthe Ballon, Brecht Verbeken, Brecht F. Verbeken +2
Large language models (LLMs) increasingly solve difficult problems by producing "reasoning traces" before emitting a final response. However, it remains unclear how accuracy and de…
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…
Benchmarks Saturate When The Model Gets Smarter Than The Judge
Marthe Ballon, Andres Algaba, Brecht Verbeken +2
Benchmarks are important tools to track progress in the development of Large Language Models (LLMs), yet inaccuracies in datasets and evaluation methods consistently undermine thei…