Before revision:  We show that the I-VILA approach, which simply adds special tokens denoting boundaries between layout structures into model inputs, can lead to +1~4.5 F1 Score improvements in token classificationtasks .
After revision:  We show that the I-VILA approach, which simply adds special tokens denoting boundaries between layout structures into model inputs, can lead to 1.9\% Macro F1 Score improvements in token classificationtasks .