Chu-Xin Xiao

Causal deconfounding for robust link prediction in multimodal knowledge networks

Sensitivity analysis shows that the gains are mainly attributable to background-dominated prototypes, supporting the proposed visual-confounder assumption within its stated limits, and MKGC-CSR remains more robust than noise-augmented baselines under Gaussian corruption.