All similarity metrics between IS-DOS and RS-DOS were found to be significantly lower than the baseline errors (Fig. ). From the qualitative and quantitative comparisons, we confirmed that DOS shapes and properties of initial and relaxed structures are similar, suggesting that IS-DOS could be proper crystal representations of ML models for IS2RE task. On the other hand, we note that bond distance information, which has been mainly utilized as inputs in various GNN models, changed significantly during the DFT relaxations, suggesting that it is inadequate to use distance-based features for IS2RE task (Supplementary Fig. ) . Through CBAM self-attention and residual connection, input feature maps autonomously learn weighted features. Each convolutional block is connected through average pooling.