Genetic programming evolves heterogeneous layer-specific scalar functions to approximate layer normalization in pre-trained ViTs, capturing 91.6% variance versus 70.2% for uniform baselines and recovering 84.25% ImageNet Top-1 accuracy after 20 epochs of adaptation.
Object detection based on cnn and vision-transformer: A survey.IET Computer Vision, 19(1):e70028, 2025
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Evolving Layer-Specific Scalar Functions for Hardware-Aware Transformer Adaptation
Genetic programming evolves heterogeneous layer-specific scalar functions to approximate layer normalization in pre-trained ViTs, capturing 91.6% variance versus 70.2% for uniform baselines and recovering 84.25% ImageNet Top-1 accuracy after 20 epochs of adaptation.