2 papers
cs.AI2026
How Does Bayesian Causal Discovery Fail? Characterising Structural Consequences in Linear Gaussian Networks under Latent Confounding
Debargha Ghosh, Silja Renooij, Anna V. Kononova
Bayesian causal discovery is widely used for its ability to quantify epistemic uncertainty over directed acyclic graphs (DAGs) through posterior inference. However, its behaviour u…
cs.AI2025
Parameterized Argumentation-based Reasoning Tasks for Benchmarking Generative Language Models
Cor Steging, Silja Renooij, Bart Verheij
Generative large language models as tools in the legal domain have the potential to improve the justice system. However, the reasoning behavior of current generative models is brit…