A higher score indicates better step ordering (with a maximum score of 2). tab:coherencemetrics shows that our personalized models achieve average recipe-level coherence scores of 1.78-1.82, surpassing the baseline at 1.77. On average, human evaluators preferred personalized model outputs to baseline 63% of the time, confirming that personalized attention improves the semantic plausibility of generated recipes. 
 Question: What were their results on the new dataset?
average recipe-level coherence scores of 1.78-1.82 human evaluators preferred personalized model outputs to baseline 63% of the time