To address oversmoothing and enhance the model's ability to learn long-range interactions across the molecular graph, we explored skip connection strategies. Specifically, we investigated two distinct approaches: DenseNet-inspired skip connections , where each layer within a dense block receives inputs from all preceding layers and outputs to all subsequent layers, and ResNet-inspired skip connections , where the input of a layer (or block of layers) is directly added to its output. Both strategies were integrated into the general architecture that utilized the best-performing operator, GINE.