On QM8, there is an average decrease in MAE of 19.23% across all tasks for SchNet, and all tasks are improved when using ABP. The most improved task is 'E2-PBE0/def2SVP' (25.07%), and the least is 'f2-CC2' (13.15%). When using DimeNet++, the average decrease in MAE due to ABP is of 2.31%, with the most improved task being 'E1-CAM' (7.69%). We observed slightly worse performance when using ABP for only two tasks: 'f2-CAM' (-1.11%) and 'f2-PBE0/def2TZVP' (-0.48%). In general, for both SchNet and DimeNet++, the least improved tasks when using ABP involve the oscillator strength f 2 .