The next model, R-MAT , a relative molecule self-attention transformer with 3D structure representations and minimal inductive biases set, was designed in aim of overcoming the humble pre-existing pre-training methods; to enhance the prediction outcomes despite the small available datasets. The self-attention techniques employed led to the noticed improvement in predicting molecular properties.