Can performance be enhanced with architectural strategies only

Hello, I am using deep learning in genomics. I work on a topic in which the dataset is inherently imbalanced and long range context is highly needed, I cannot perform data augmentation since DNA sequences are highly sensitive to changes. The actual SOTA architecture is ResNet. I wanted to enhance performances by experimenting with other architectures but looking at current research the go to strategy is bring more data which is very difficult in my case.

So my question is …

architecture augmentation context data dataset deep learning deeplearning dna genomics hello performance performances resnet sota strategies work