In general, the Transformer architectures are capable of generating attention scores through their attention layers, which reflect the degree of attention the model pays to input features for a given task. These attention scores can be utilized as a tool for feature importance analysis. Figure presents the attention scores of representative COF structures, such as COF-1 , CTF-1 , and COF-LZU1 . In these scores, the larger size of atoms represents higher attention scores, which in turn can be considered as more influential factors in determining band gap. It is important to note that these structures are composed of benzene rings as linkers and are distinct from their corresponding centers. The analysis of attention scores reveals that the centers have higher attention scores than the linkers, indicating that they play a more prominent role in determining the band gaps. The 2D COFs are known for their ability to extend the π-conjugation system, which leads to greater emphasis being placed on centers that have more than two connection points, as compared to linkers that only have two connection points. Moreover, it is noteworthy that the πconjugation ability of C-N bonds is a significant aspect to consider. The analysis of attention scores for CTF-1 and COF-LZU-1 indicates that nitrogen atoms within the structures' centers exhibit higher attention scores compared to other atoms. In contrast, the oxygen atoms in the B3O3 rings of COF-1 have relatively lower attention scores among their centers, primarily due to the absence of π-conjugation. This analysis demonstrates the utility of attention scores in providing insights into the underlying factors that determine the band gap of COF structures, thereby facilitating the development of more efficient and accurate models for porous materials.