Consistency Improvements. Adding KL divergence loss led to notable improvements in consistency across all models and tasks. Specifically, for forward reaction prediction and retrosynthesis, false consistency increased, and the gap between overall and false consistency narrowed, contrasting with the trends observed when increasing dataset size. These results confirm that KL divergence loss enhances consistency by aligning predictions across input representations.