Preprint Open access
Coupling Noisy Pairwise Knowledge to the DAG Posterior for Causal Discovery
External causal reports can improve structure learning from limited observations, but their reliability varies across sources and variable pairs. We introduce HB-NoisyKG, a Bayesian framework that combines observational data with repeated causal reports from sources such as large language models. Each report is a noisy …