It is worth noting that the overall screening performance of GGAP-CPI-IntEns is slightly lower than that of BIND on benchmarks such as DUD-E and LIT-PCBA. This outcome stems from our intentional exclusion of generated decoys during model training-a strategy adopted to prevent the inclusion of misleading false negative samples that could undermine precise affinity prediction and risk data leakage. As a result, our model excels in accurately predicting the affinities of true binders while maintaining a robust, if relatively comparable, ability to differentiate binders from non-binders.