collaborators

5 papers

cs.AI2026

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…

cs.LG2026

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…

cs.CY2026

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…

cs.LG2026

Ergodicity in reinforcement learning

Dominik Baumann, Erfaun Noorani, Arsenii Mustafin +5

In reinforcement learning, we typically aim to optimize the expected value of the sum of rewards an agent collects over a trajectory. However, if the process generating these rewar…

cs.LG2026

Model-Agnostic Solutions for Deep Reinforcement Learning in Non-Ergodic Contexts

Bert Verbruggen, Arne Vanhoyweghen, Vincent Ginis

Reinforcement Learning (RL) remains a central optimisation framework in machine learning. Although RL agents can converge to optimal solutions, the definition of ``optimality'' dep…